2021 |
Koya Sato, Katsuya Suto, Kei Inage, Koichi Adachi, Takeo Fujii Space-Frequency-Interpolated Radio Map Journal Article IEEE Transactions on Vehicular Technology, 70 (1), pp. 714-725, 2021. Abstract | Links | BibTeX | タグ: DSA @article{2021SatoTVT, title = {Space-Frequency-Interpolated Radio Map}, author = {Koya Sato, Katsuya Suto, Kei Inage, Koichi Adachi, Takeo Fujii}, doi = {10.1109/TVT.2021.3049894}, year = {2021}, date = {2021-01-08}, journal = {IEEE Transactions on Vehicular Technology}, volume = {70}, number = {1}, pages = {714-725}, abstract = {This paper presents a novel method for radio map construction that simultaneously interpolates the received signal power values over space and frequency domains. Radio maps can be used to improve spectrum management and for localization systems, which are related to wireless systems in general such as cellular systems, Internet of Things (IoT) networks, and vehicular communications. Researchers have shown that crowdsourcing using spatial interpolation techniques can be used to accurately construct a radio map to improve these applications; however, because of the limitation in the spatial domain, conventional methods can build a radio map for only those frequencies at which sensing can be performed. Our proposed method focuses on the fact that the shadowing values show strong correlation over a wide range of frequency domains. The main idea is to treat the shadowing values obtained over various frequencies as the ones over target frequency. Using the actual datasets obtained over 870, 2115, and 3500 MHz in a cellular system, we show that the proposed method can accurately generate a radio map, even if no (or few) datasets are available in the target frequency.}, keywords = {DSA}, pubstate = {published}, tppubtype = {article} } This paper presents a novel method for radio map construction that simultaneously interpolates the received signal power values over space and frequency domains. Radio maps can be used to improve spectrum management and for localization systems, which are related to wireless systems in general such as cellular systems, Internet of Things (IoT) networks, and vehicular communications. Researchers have shown that crowdsourcing using spatial interpolation techniques can be used to accurately construct a radio map to improve these applications; however, because of the limitation in the spatial domain, conventional methods can build a radio map for only those frequencies at which sensing can be performed. Our proposed method focuses on the fact that the shadowing values show strong correlation over a wide range of frequency domains. The main idea is to treat the shadowing values obtained over various frequencies as the ones over target frequency. Using the actual datasets obtained over 870, 2115, and 3500 MHz in a cellular system, we show that the proposed method can accurately generate a radio map, even if no (or few) datasets are available in the target frequency. |
Katsuya Suto, Shinsuke Bannai, Koya Sato, Kei Inage, Koichi Adachi, Takeo Fujii Image-Driven Spatial Interpolation with Deep Learning for Radio Map Construction Journal Article IEEE Wireless Communications Letters, 10 (6), pp. 1222-1226, 2021. Abstract | Links | BibTeX | タグ: DSA @article{2021SutoLWC, title = {Image-Driven Spatial Interpolation with Deep Learning for Radio Map Construction}, author = {Katsuya Suto, Shinsuke Bannai, Koya Sato, Kei Inage, Koichi Adachi and Takeo Fujii}, doi = {10.1109/LWC.2021.3062666}, year = {2021}, date = {2021-03-01}, journal = {IEEE Wireless Communications Letters}, volume = {10}, number = {6}, pages = {1222-1226}, abstract = {Radio maps are a promising technology that can boost the capability of wireless networks by enhancing spectrum efficiency. Since spatial interpolation is a critical challenge to construct a precise radio map, the latest works have proposed deep learning (DL)-based interpolation methods. However, a DL model that achieves enough estimation accuracy for practical uses has not yet been established due to the complexity of radio propagation characteristics. Therefore, we propose a novel DL framework that transforms the spatial interpolation problem into a shadowing adjustment problem suitable for DL-based approaches. We evaluate the performance using real measurement data in urban and suburban areas to show that the proposed framework outperforms the state-of-the-art deep learning models.}, keywords = {DSA}, pubstate = {published}, tppubtype = {article} } Radio maps are a promising technology that can boost the capability of wireless networks by enhancing spectrum efficiency. Since spatial interpolation is a critical challenge to construct a precise radio map, the latest works have proposed deep learning (DL)-based interpolation methods. However, a DL model that achieves enough estimation accuracy for practical uses has not yet been established due to the complexity of radio propagation characteristics. Therefore, we propose a novel DL framework that transforms the spatial interpolation problem into a shadowing adjustment problem suitable for DL-based approaches. We evaluate the performance using real measurement data in urban and suburban areas to show that the proposed framework outperforms the state-of-the-art deep learning models. |
Takeru Terauchi, Katsuya Suto, Masashi Wakaiki Harvest-Then-Transmit-Based TDMA Protocol with Statistical Channel State Information for Wireless Powered Sensor Networks Conference in Proc. VTC2021-Spring, 2021. BibTeX | タグ: Green Networks @conference{Terauchi_VTC2021S, title = {Harvest-Then-Transmit-Based TDMA Protocol with Statistical Channel State Information for Wireless Powered Sensor Networks}, author = {Takeru Terauchi, Katsuya Suto, Masashi Wakaiki}, year = {2021}, date = {2021-04-25}, booktitle = {in Proc. VTC2021-Spring}, keywords = {Green Networks}, pubstate = {published}, tppubtype = {conference} } |
Kohei Kato, Katsuya Suto, Koya Sato Deterministic Video Streaming with Deep Learning Enabled Base Station Intervention for Stable Remote Driving System Conference in Proc. ICC2021 workshop - TsDN, 2021. @conference{Kato_ICC2021, title = {Deterministic Video Streaming with Deep Learning Enabled Base Station Intervention for Stable Remote Driving System}, author = {Kohei Kato, Katsuya Suto, Koya Sato}, year = {2021}, date = {2021-05-14}, booktitle = {in Proc. ICC2021 workshop - TsDN}, keywords = {ITS}, pubstate = {published}, tppubtype = {conference} } |
2020 |
Tiago Koketsu Rodrigues, Katsuya Suto, Hiroki Nishiyama, Jiajia Liu, Nei Kato Machine Learning meets Computation and Communication Control in Evolving Edge and Cloud Journal Article IEEE Communications Surveys and Tutorials, 22 (1), pp. 38-67, 2020. Abstract | Links | BibTeX | タグ: MEC @article{Tiago2019Machine, title = {Machine Learning meets Computation and Communication Control in Evolving Edge and Cloud}, author = {Tiago Koketsu Rodrigues and Katsuya Suto and Hiroki Nishiyama and Jiajia Liu and Nei Kato}, doi = {10.1109/COMST.2019.2943405}, year = {2020}, date = {2020-01-01}, journal = {IEEE Communications Surveys and Tutorials}, volume = {22}, number = {1}, pages = {38-67}, abstract = {Mobile Edge Computing (MEC) is considered an essential future service for the implementation of 5G networks and the Internet of Things, as it is the best method of delivering computation and communication resources to mobile devices. It is based on the connection of the users to servers located on the edge of the network, which is especially relevant for real-time applications that demand minimal latency. In order to guarantee a resource-efficient MEC (which, for example, could mean improved Quality of Service for users or lower costs for service providers), it is important to consider certain aspects of the service model, such as where to offload the tasks generated by the devices, how many resources to allocate to each user (specially in the wired or wireless device-server communication) and how to handle inter-server communication. However, in the MEC scenarios with many and varied users, servers and applications, these problems are characterized by parameters with exceedingly high levels of dimensionality, resulting in too much data to be processed and complicating the task of finding efficient configurations. This will be particularly troublesome when 5G networks and Internet of Things roll out, with their massive amounts of devices. To address this concern, the best solution is to utilize Machine Learning (ML) algorithms, which enable the computer to draw conclusions and make predictions based on existing data without human supervision, leading to quick near-optimal solutions even in problems with high dimensionality. Indeed, in scenarios with too much data and too many parameters, ML algorithms are often the only feasible alternative. In this paper, a comprehensive survey on the use of ML in MEC systems is provided, offering an insight into the current progress of this research area. Furthermore, helpful guidance is supplied by pointing out which MEC challenges can be solved by ML solutions, what are the current trending algorithms in frontier ML research and how they could be used in MEC. These pieces of information should prove fundamental in encouraging future research that combines ML and MEC.}, keywords = {MEC}, pubstate = {published}, tppubtype = {article} } Mobile Edge Computing (MEC) is considered an essential future service for the implementation of 5G networks and the Internet of Things, as it is the best method of delivering computation and communication resources to mobile devices. It is based on the connection of the users to servers located on the edge of the network, which is especially relevant for real-time applications that demand minimal latency. In order to guarantee a resource-efficient MEC (which, for example, could mean improved Quality of Service for users or lower costs for service providers), it is important to consider certain aspects of the service model, such as where to offload the tasks generated by the devices, how many resources to allocate to each user (specially in the wired or wireless device-server communication) and how to handle inter-server communication. However, in the MEC scenarios with many and varied users, servers and applications, these problems are characterized by parameters with exceedingly high levels of dimensionality, resulting in too much data to be processed and complicating the task of finding efficient configurations. This will be particularly troublesome when 5G networks and Internet of Things roll out, with their massive amounts of devices. To address this concern, the best solution is to utilize Machine Learning (ML) algorithms, which enable the computer to draw conclusions and make predictions based on existing data without human supervision, leading to quick near-optimal solutions even in problems with high dimensionality. Indeed, in scenarios with too much data and too many parameters, ML algorithms are often the only feasible alternative. In this paper, a comprehensive survey on the use of ML in MEC systems is provided, offering an insight into the current progress of this research area. Furthermore, helpful guidance is supplied by pointing out which MEC challenges can be solved by ML solutions, what are the current trending algorithms in frontier ML research and how they could be used in MEC. These pieces of information should prove fundamental in encouraging future research that combines ML and MEC. |
Riku Hashimoto, Katsuya Suto SICNN: Spatial Interpolation with Convolutional Neural Networks for Radio Environment Mapping Conference in Proc. ICAIIC 2020, 2020. @conference{2019HashimotoICAIIC, title = {SICNN: Spatial Interpolation with Convolutional Neural Networks for Radio Environment Mapping}, author = {Riku Hashimoto and Katsuya Suto}, year = {2020}, date = {2020-02-19}, booktitle = {in Proc. ICAIIC 2020}, pages = {6}, keywords = {DSA}, pubstate = {published}, tppubtype = {conference} } |
Shinsuke Bannai, Katsuya Suto Spatial Extrapolation with Generative Adversarial Networks for Radio Map Construction Conference in Proc. ICETC 2020, 2020. @conference{Bannai_ICETC2020, title = {Spatial Extrapolation with Generative Adversarial Networks for Radio Map Construction}, author = {Shinsuke Bannai, Katsuya Suto}, year = {2020}, date = {2020-12-02}, booktitle = {in Proc. ICETC 2020}, keywords = {DSA}, pubstate = {published}, tppubtype = {conference} } |
RIku Hashimoto, Katsuya Suto On Radio Propagation Estimation based on Deep Learning withConvolution and Self-attention Conference in Proc. ICETC 2020, 2020. @conference{Hashimoto_ICETC2020, title = {On Radio Propagation Estimation based on Deep Learning withConvolution and Self-attention}, author = {RIku Hashimoto, Katsuya Suto}, year = {2020}, date = {2020-12-02}, booktitle = {in Proc. ICETC 2020}, keywords = {DSA}, pubstate = {published}, tppubtype = {conference} } |
須藤克弥, 坂内信允 電波伝搬推定システム、電波伝搬推定方法および生成部の製造方法 Patent 特願2020-204831, 2020. @patent{2020SutoPat, title = {電波伝搬推定システム、電波伝搬推定方法および生成部の製造方法}, author = {須藤克弥 and 坂内信允}, year = {2020}, date = {2020-12-10}, journal = {特願2020-204831}, number = {特願2020-204831}, keywords = {DSA}, pubstate = {published}, tppubtype = {patent} } |
2019 |
Masashi Wakaiki, Katsuya Suto, Kenta Koiwa, Kang-Zhi Liu, Tadanao Zanma A Control-Theoretic Approach for Cell Zooming of Energy Harvesting Small Cell Networks Journal Article IEEE Transactions on Green Communications and Networking, 3 (2), pp. 329 - 342, 2019. Abstract | Links | BibTeX | タグ: Green Networks @article{Wakaiki_2018, title = {A Control-Theoretic Approach for Cell Zooming of Energy Harvesting Small Cell Networks}, author = {Masashi Wakaiki and Katsuya Suto and Kenta Koiwa and Kang-Zhi Liu and Tadanao Zanma}, doi = {10.1109/TGCN.2018.2889897}, year = {2019}, date = {2019-06-01}, journal = {IEEE Transactions on Green Communications and Networking}, volume = {3}, number = {2}, pages = {329 - 342}, abstract = {Dense deployment of small cell base stations (SBSs) powered by renewable energy is spotlighted as a solution of the increasing demand of communication services. How to utilize renewable energy efficiently under the temporal change of traffic loads is a brand new challenge. In this paper, we design real-time controllers for cell zooming, that is, to determine transmission power and activation/deactivation of energy harvesting SBSs. The proposed method maximizes the total number of accommodated users, considering the remaining energies of batteries. First, we solve a problem of finding a number of active SBSs that maximizes energy efficiency with full accommodation of active users. Then, we apply model predictive control to the real-time computation of an optimal transmission power. Moreover, we present an explicit formula of an approximate optimal transmission power, by simplifying the proposed method. Numerical simulations illustrate that the proposed method achieves high performance on energy efficiency with low computational effort, compared with a Q-learning-based approach.}, keywords = {Green Networks}, pubstate = {published}, tppubtype = {article} } Dense deployment of small cell base stations (SBSs) powered by renewable energy is spotlighted as a solution of the increasing demand of communication services. How to utilize renewable energy efficiently under the temporal change of traffic loads is a brand new challenge. In this paper, we design real-time controllers for cell zooming, that is, to determine transmission power and activation/deactivation of energy harvesting SBSs. The proposed method maximizes the total number of accommodated users, considering the remaining energies of batteries. First, we solve a problem of finding a number of active SBSs that maximizes energy efficiency with full accommodation of active users. Then, we apply model predictive control to the real-time computation of an optimal transmission power. Moreover, we present an explicit formula of an approximate optimal transmission power, by simplifying the proposed method. Numerical simulations illustrate that the proposed method achieves high performance on energy efficiency with low computational effort, compared with a Q-learning-based approach. |
Tiago Koketsu Rodrigues, Katsuya Suto, Nei Kato Edge Cloud Server Deployment with Transmission Power Control through Machine Learning for 6G Internet of Things Journal Article IEEE Transactions on Emerging Topics in Computing, 2019. Abstract | Links | BibTeX | タグ: MEC @article{2019TiagoEdge, title = {Edge Cloud Server Deployment with Transmission Power Control through Machine Learning for 6G Internet of Things}, author = {Tiago Koketsu Rodrigues and Katsuya Suto and Nei Kato }, doi = {10.1109/TETC.2019.2963091}, year = {2019}, date = {2019-12-31}, journal = {IEEE Transactions on Emerging Topics in Computing}, abstract = {Cloud computing is an important technology for bringing a big pool of elastic resources to client devices. Their main drawback has long been the long distance between users and servers, but this has been remedied by Edge Cloud Computing, where the cloud servers are located in the network edge. Edge Cloud Computing is regarded as essential for future networks and consequently, there is plenty of research on how to optimize its operation. However, the vast majority of them ignore the decision of where the edge servers should be deployed, despite how severely this can affect the performance of the system. Furthermore, future networks must also deal with massive amounts of clients and servers, such as the ones characteristic of the Internet of Things and 6G Networks. This demands solutions that are scalable. Given these two points, we propose a Machine Learning-based server deployment policy in 6G Internet of Things environments. Our solution is proven to approach optimality while being feasible. Furthermore, we also prove that our proposal leads to lower latency and higher resource efficiency than conventional Edge Cloud Computing server deployment solutions.}, keywords = {MEC}, pubstate = {published}, tppubtype = {article} } Cloud computing is an important technology for bringing a big pool of elastic resources to client devices. Their main drawback has long been the long distance between users and servers, but this has been remedied by Edge Cloud Computing, where the cloud servers are located in the network edge. Edge Cloud Computing is regarded as essential for future networks and consequently, there is plenty of research on how to optimize its operation. However, the vast majority of them ignore the decision of where the edge servers should be deployed, despite how severely this can affect the performance of the system. Furthermore, future networks must also deal with massive amounts of clients and servers, such as the ones characteristic of the Internet of Things and 6G Networks. This demands solutions that are scalable. Given these two points, we propose a Machine Learning-based server deployment policy in 6G Internet of Things environments. Our solution is proven to approach optimality while being feasible. Furthermore, we also prove that our proposal leads to lower latency and higher resource efficiency than conventional Edge Cloud Computing server deployment solutions. |
Tiago Gama Rodrigues, Katsuya Suto, Nei Kato Hyperparameter Study of Machine Learning Solutions for the Edge Server Deployment Problem Conference in Proc. IEEE 90th VTC2019-Fall, 2019. @conference{Tiago2019VTC, title = {Hyperparameter Study of Machine Learning Solutions for the Edge Server Deployment Problem}, author = {Tiago Gama Rodrigues and Katsuya Suto and Nei Kato}, year = {2019}, date = {2019-09-01}, booktitle = {in Proc. IEEE 90th VTC2019-Fall}, keywords = {MEC}, pubstate = {published}, tppubtype = {conference} } |
Masashi Wakaiki, Katsuya Suto, Izumi Masubuchi Privacy-preserved Cell Zooming with Distributed Optimization in Green Networks Conference in Proc. IEEE 90th VTC2019-Fall, 2019. BibTeX | タグ: Green Networks @conference{Wakaiki2019VTC, title = {Privacy-preserved Cell Zooming with Distributed Optimization in Green Networks}, author = {Masashi Wakaiki and Katsuya Suto and Izumi Masubuchi}, year = {2019}, date = {2019-09-30}, booktitle = {in Proc. IEEE 90th VTC2019-Fall}, keywords = {Green Networks}, pubstate = {published}, tppubtype = {conference} } |
Katsuya Suto, Riku Hashimoto Crowdsensing Based Spectrum Database with Total Variation Regularization Conference in Proc. IEEE DySPAN 2019 Workshop on Data-Driven Dynamic Spectrum Sharing, 2019. @conference{SUTO2019Crowd, title = {Crowdsensing Based Spectrum Database with Total Variation Regularization}, author = {Katsuya Suto and Riku Hashimoto}, year = {2019}, date = {2019-11-14}, booktitle = {in Proc. IEEE DySPAN 2019 Workshop on Data-Driven Dynamic Spectrum Sharing}, pages = {1-6}, keywords = {DSA}, pubstate = {published}, tppubtype = {conference} } |
2018 |
Katsuya Suto, Hiroki Nishiyama, Nei Kato, Toshiaki Kuri Model Predictive Joint Transmit Power Control for Improving System Availability in Energy-Harvesting Wireless Mesh Networks Journal Article IEEE Communications Letters, 22 (10), pp. 2112-2115, 2018. Abstract | Links | BibTeX | タグ: Green Networks @article{Suto2018Model, title = {Model Predictive Joint Transmit Power Control for Improving System Availability in Energy-Harvesting Wireless Mesh Networks}, author = {Katsuya Suto and Hiroki Nishiyama and Nei Kato and Toshiaki Kuri}, doi = {10.1109/LCOMM.2018.2860005}, year = {2018}, date = {2018-08-01}, journal = {IEEE Communications Letters}, volume = {22}, number = {10}, pages = {2112-2115}, abstract = {This letter explores energy-efficient transmit power control in wireless mesh networks (WMNs) with energy harvesting sources, where both users and WMN links are considered to decide an optimal energy utilization scheme. Specifically, a model predictive control algorithm is proposed based on user distribution and harvested energy predictions. Extensive simulation results show that the proposed algorithm outperforms the static and current information-based transmit power control schemes in high user density environments.}, keywords = {Green Networks}, pubstate = {published}, tppubtype = {article} } This letter explores energy-efficient transmit power control in wireless mesh networks (WMNs) with energy harvesting sources, where both users and WMN links are considered to decide an optimal energy utilization scheme. Specifically, a model predictive control algorithm is proposed based on user distribution and harvested energy predictions. Extensive simulation results show that the proposed algorithm outperforms the static and current information-based transmit power control schemes in high user density environments. |
Tiago Gama Rodrigues, Katsuya Suto, Hiroki Nishiyama, Nei Kato Cloudlets Activation Scheme for Scalable Mobile Edge Computing with Transmission Power Control and Virtual Machine Migration Journal Article IEEE Transactions on Computers, 67 (9), pp. 1287-1300, 2018. Abstract | Links | BibTeX | タグ: MEC @article{TIago2018Cloudlets, title = {Cloudlets Activation Scheme for Scalable Mobile Edge Computing with Transmission Power Control and Virtual Machine Migration}, author = {Tiago Gama Rodrigues and Katsuya Suto and Hiroki Nishiyama and Nei Kato}, doi = {10.1109/TC.2018.2818144}, year = {2018}, date = {2018-09-01}, journal = {IEEE Transactions on Computers}, volume = {67}, number = {9}, pages = {1287-1300}, abstract = {Mobile devices have several restrictions due to design choices that guarantee their mobility. A way of surpassing such limitations is to utilize cloud servers called cloudlets on the edge of the network through Mobile Edge Computing. However, as the number of clients and devices grows, the service must also increase its scalability in order to guarantee a latency limit and quality threshold. This can be achieved by deploying and activating more cloudlets, but this solution is expensive due to the cost of the physical servers. The best choice is to optimize the resources of the cloudlets through an intelligent choice of configuration that lowers delay and raises scalability. Thus, in this paper we propose an algorithm that utilizes Virtual Machine Migration and Transmission Power Control, together with a mathematical model of delay in Mobile Edge Computing and a heuristic algorithm called Particle Swarm Optimization, to balance the workload between cloudlets and consequently maximize cost-effectiveness. Our proposal is the first to consider simultaneously communication, computation, and migration in our assumed scale and, due to that, manages to outperform other conventional methods in terms of number of serviced users.}, keywords = {MEC}, pubstate = {published}, tppubtype = {article} } Mobile devices have several restrictions due to design choices that guarantee their mobility. A way of surpassing such limitations is to utilize cloud servers called cloudlets on the edge of the network through Mobile Edge Computing. However, as the number of clients and devices grows, the service must also increase its scalability in order to guarantee a latency limit and quality threshold. This can be achieved by deploying and activating more cloudlets, but this solution is expensive due to the cost of the physical servers. The best choice is to optimize the resources of the cloudlets through an intelligent choice of configuration that lowers delay and raises scalability. Thus, in this paper we propose an algorithm that utilizes Virtual Machine Migration and Transmission Power Control, together with a mathematical model of delay in Mobile Edge Computing and a heuristic algorithm called Particle Swarm Optimization, to balance the workload between cloudlets and consequently maximize cost-effectiveness. Our proposal is the first to consider simultaneously communication, computation, and migration in our assumed scale and, due to that, manages to outperform other conventional methods in terms of number of serviced users. |
Kai Fan, Xin Wang, Katsuya Suto, Hui Li, Yintang Yang Secure and Efficient Privacy-Preserving Ciphertext Retrieval in Connected Vehicular Cloud Computing Journal Article IEEE Network, 32 (3), pp. 52-57, 2018. Abstract | Links | BibTeX | タグ: Security and Privacy @article{Fan2018Secure, title = {Secure and Efficient Privacy-Preserving Ciphertext Retrieval in Connected Vehicular Cloud Computing}, author = {Kai Fan and Xin Wang and Katsuya Suto and Hui Li and Yintang Yang}, doi = {10.1109/MNET.2018.1700327}, year = {2018}, date = {2018-05-01}, journal = {IEEE Network}, volume = {32}, number = {3}, pages = {52-57}, abstract = {As vehicular equipment is becoming more and more intelligent, the vehicular information service, as the main means of capturing information, has been far from able to meet the needs of occupants [1, 2]. Cloud computing, with its powerful computing and storage capabilities, convenient network access, energy saving and excellent scalability, reliability, availability, and other advantages, can be an effective solution to the limitations of existing automotive information services. Connected vehicular cloud computing, which combines cloud computing and VANETs, has the characteristics of both a cloud platform and a mobile ad hoc network, including autonomy and no fixed structure, good scalability, and so on. However, during the information retrieval, high-density node distribution and high-speed mobile nodes may directly affect the information transmission capacity of a VANET by information tampering, transmission delay, and other issues. In this article, we propose a ciphertext-based search system that exploits RSUs as super peers for connected vehicular cloud computing. The proposed system supports ciphertext retrieval for related documents. In the proposed system, all the computations and retrieval operations are handled by super stationary peers, while documents are stored in the cloud to achieve high efficiency and security of the index structure. We can also reduce the impact of vehicle dynamics on the information retrieval process in this way. In our system, the indexing efficiency is also improved by utilizing a hybrid indexing structure in which binary trees are nested in a B+ tree. Through security analysis and performance evaluation, we demonstrate that our proposal can achieve acceptable security and efficiency.}, keywords = {Security and Privacy}, pubstate = {published}, tppubtype = {article} } As vehicular equipment is becoming more and more intelligent, the vehicular information service, as the main means of capturing information, has been far from able to meet the needs of occupants [1, 2]. Cloud computing, with its powerful computing and storage capabilities, convenient network access, energy saving and excellent scalability, reliability, availability, and other advantages, can be an effective solution to the limitations of existing automotive information services. Connected vehicular cloud computing, which combines cloud computing and VANETs, has the characteristics of both a cloud platform and a mobile ad hoc network, including autonomy and no fixed structure, good scalability, and so on. However, during the information retrieval, high-density node distribution and high-speed mobile nodes may directly affect the information transmission capacity of a VANET by information tampering, transmission delay, and other issues. In this article, we propose a ciphertext-based search system that exploits RSUs as super peers for connected vehicular cloud computing. The proposed system supports ciphertext retrieval for related documents. In the proposed system, all the computations and retrieval operations are handled by super stationary peers, while documents are stored in the cloud to achieve high efficiency and security of the index structure. We can also reduce the impact of vehicle dynamics on the information retrieval process in this way. In our system, the indexing efficiency is also improved by utilizing a hybrid indexing structure in which binary trees are nested in a B+ tree. Through security analysis and performance evaluation, we demonstrate that our proposal can achieve acceptable security and efficiency. |
Shan Zhang, Peter He, Katsuya Suto, Peng Yang, Lian Zhao, Sherman Shen Cooperative Edge Caching in User-Centric Clustered Mobile Networks Journal Article IEEE Transactions on Mobile Computing, 17 (8), pp. 1791-1805, 2018. Abstract | Links | BibTeX | タグ: MEC @article{Zhang2018Cooperative, title = {Cooperative Edge Caching in User-Centric Clustered Mobile Networks}, author = {Shan Zhang and Peter He and Katsuya Suto and Peng Yang and Lian Zhao and Sherman Shen}, doi = {10.1109/TMC.2017.2780834}, year = {2018}, date = {2018-08-01}, journal = {IEEE Transactions on Mobile Computing}, volume = {17}, number = {8}, pages = {1791-1805}, abstract = {With files proactively stored at base stations (BSs), mobile edge caching enables direct content delivery without remote file fetching, which can reduce the end-to-end delay while relieving backhaul pressure. To effectively utilize the limited cache size in practice, cooperative caching can be leveraged to exploit caching diversity, by allowing users served by multiple base stations under the emerging user-centric network architecture. This paper explores delay-optimal cooperative edge caching in large-scale user-centric mobile networks, where the content placement and cluster size are optimized based on the stochastic information of network topology, traffic distribution, channel quality, and file popularity. Specifically, a greedy content placement algorithm is proposed based on the optimal bandwidth allocation, which can achieve (1 - 1/e)-optimality with linear computational complexity. In addition, the optimal user-centric cluster size is studied, and a condition constraining the maximal cluster size is presented in explicit form, which reflects the tradeoff between caching diversity and spectrum efficiency. Extensive simulations are conducted for analysis validation and performance evaluation. Numerical results demonstrate that the proposed greedy content placement algorithm can reduce the average file transmission delay up to 45 percent compared with the non-cooperative and hit-ratio-maximal schemes. Furthermore, the optimal clustering is also discussed considering the influences of different system parameters.}, keywords = {MEC}, pubstate = {published}, tppubtype = {article} } With files proactively stored at base stations (BSs), mobile edge caching enables direct content delivery without remote file fetching, which can reduce the end-to-end delay while relieving backhaul pressure. To effectively utilize the limited cache size in practice, cooperative caching can be leveraged to exploit caching diversity, by allowing users served by multiple base stations under the emerging user-centric network architecture. This paper explores delay-optimal cooperative edge caching in large-scale user-centric mobile networks, where the content placement and cluster size are optimized based on the stochastic information of network topology, traffic distribution, channel quality, and file popularity. Specifically, a greedy content placement algorithm is proposed based on the optimal bandwidth allocation, which can achieve (1 - 1/e)-optimality with linear computational complexity. In addition, the optimal user-centric cluster size is studied, and a condition constraining the maximal cluster size is presented in explicit form, which reflects the tradeoff between caching diversity and spectrum efficiency. Extensive simulations are conducted for analysis validation and performance evaluation. Numerical results demonstrate that the proposed greedy content placement algorithm can reduce the average file transmission delay up to 45 percent compared with the non-cooperative and hit-ratio-maximal schemes. Furthermore, the optimal clustering is also discussed considering the influences of different system parameters. |
Masashi Wakaiki, Katsuya Suto, Kenta Koiwa, Kang-Zhi Liu, Tadanao Zanma Model Predictive Cell Zooming for Energy-harvesting Small Cell Networks Conference in Proc. IEEE ICC 2018, 2018. Links | BibTeX | タグ: Green Networks @conference{Wakaiki2018ICC, title = {Model Predictive Cell Zooming for Energy-harvesting Small Cell Networks}, author = {Masashi Wakaiki and Katsuya Suto and Kenta Koiwa and Kang-Zhi Liu and Tadanao Zanma}, url = {https://ieeexplore.ieee.org/document/8422093}, year = {2018}, date = {2018-05-24}, booktitle = {in Proc. IEEE ICC 2018}, keywords = {Green Networks}, pubstate = {published}, tppubtype = {conference} } |
2017 |
Tiago Gama Rodrigues, Katsuya Suto, Hiroki Nishiyama, Nei Kato Hybrid Method for Minimizing Service Delay in Edge Cloud Computing through VM Migration and Transmission Power Control Journal Article IEEE Transactions on Computers, 66 (5), pp. 810-819, 2017. Abstract | Links | BibTeX | タグ: MEC @article{Tiago2017Hybrid, title = {Hybrid Method for Minimizing Service Delay in Edge Cloud Computing through VM Migration and Transmission Power Control}, author = {Tiago Gama Rodrigues and Katsuya Suto and Hiroki Nishiyama and Nei Kato}, doi = {10.1109/TC.2016.2620469}, year = {2017}, date = {2017-05-01}, journal = {IEEE Transactions on Computers}, volume = {66}, number = {5}, pages = {810-819}, abstract = {Due to physical limitations, mobile devices are restricted in memory, battery, processing, among other characteristics. This results in many applications that cannot be run in such devices. This problem is fixed by Edge Cloud Computing, where the users offload tasks they cannot run to cloudlet servers in the edge of the network. The main requirement of such a system is having a low Service Delay, which would correspond to a high Quality of Service. This paper presents a method for minimizing Service Delay in a scenario with two cloudlet servers. The method has a dual focus on computation and communication elements, controlling Processing Delay through virtual machine migration and improving Transmission Delay with Transmission Power Control. The foundation of the proposal is a mathematical model of the scenario, whose analysis is used on a comparison between the proposed approach and two other conventional methods; these methods have single focus and only make an effort to improve either Transmission Delay or Processing Delay, but not both. As expected, the proposal presents the lowest Service Delay in all study cases, corroborating our conclusion that a dual focus approach is the best way to tackle the Service Delay problem in Edge Cloud Computing.}, keywords = {MEC}, pubstate = {published}, tppubtype = {article} } Due to physical limitations, mobile devices are restricted in memory, battery, processing, among other characteristics. This results in many applications that cannot be run in such devices. This problem is fixed by Edge Cloud Computing, where the users offload tasks they cannot run to cloudlet servers in the edge of the network. The main requirement of such a system is having a low Service Delay, which would correspond to a high Quality of Service. This paper presents a method for minimizing Service Delay in a scenario with two cloudlet servers. The method has a dual focus on computation and communication elements, controlling Processing Delay through virtual machine migration and improving Transmission Delay with Transmission Power Control. The foundation of the proposal is a mathematical model of the scenario, whose analysis is used on a comparison between the proposed approach and two other conventional methods; these methods have single focus and only make an effort to improve either Transmission Delay or Processing Delay, but not both. As expected, the proposal presents the lowest Service Delay in all study cases, corroborating our conclusion that a dual focus approach is the best way to tackle the Service Delay problem in Edge Cloud Computing. |
Hiroki Nishiyama, Katsuya Suto, Hideki Kuribayashi Cyber Physical Systems for Intelligent Disaster Response Networks: Conceptual Proposal and Field Experiment Journal Article IEEE Network, 31 (4), pp. 120-128, 2017. Abstract | Links | BibTeX | タグ: Disaster Recovery Networks @article{Nishiyama2017Cyber, title = {Cyber Physical Systems for Intelligent Disaster Response Networks: Conceptual Proposal and Field Experiment}, author = {Hiroki Nishiyama and Katsuya Suto and Hideki Kuribayashi}, doi = {10.1109/MNET.2017.1600222}, year = {2017}, date = {2017-07-01}, journal = {IEEE Network}, volume = {31}, number = {4}, pages = {120-128}, abstract = {After large-scale natural disasters, such as the Great East Japan Earthquake of 2011, the demand for communication increases and continuously changes due to fluctuating environmental factors and demand from people, seeking to confirm the safety of others and intending to organize forces to react to the disaster situation. However, it is likely that reaching the communication service is difficult because the communication infrastructure may be damaged or out of use. To provide information communication technology (ICT) services in such circumstances, we propose an ICT system with intelligence, which can adapt to continuously changing conditions in disaster situations. This system is realized by the implementation of the cyber physical system (CPS) to networks, and we explain its capabilities to provide ICT services in disaster situations. Moreover, we explain the field experiment in which we constructed a CPS-equipped network in the Philippines. The successful results demonstrate the effectiveness and the feasibility of disaster-resilient CPS.}, keywords = {Disaster Recovery Networks}, pubstate = {published}, tppubtype = {article} } After large-scale natural disasters, such as the Great East Japan Earthquake of 2011, the demand for communication increases and continuously changes due to fluctuating environmental factors and demand from people, seeking to confirm the safety of others and intending to organize forces to react to the disaster situation. However, it is likely that reaching the communication service is difficult because the communication infrastructure may be damaged or out of use. To provide information communication technology (ICT) services in such circumstances, we propose an ICT system with intelligence, which can adapt to continuously changing conditions in disaster situations. This system is realized by the implementation of the cyber physical system (CPS) to networks, and we explain its capabilities to provide ICT services in disaster situations. Moreover, we explain the field experiment in which we constructed a CPS-equipped network in the Philippines. The successful results demonstrate the effectiveness and the feasibility of disaster-resilient CPS. |
Katsuya Suto, Hiroki Nishiyama, Nei Kato Post-Disaster User Location Maneuvering Method for Improving the QoE Guaranteed Service Time in Energy Harvesting Small Cell Networks Journal Article IEEE Transactions on Vehicular Technology, 66 (10), pp. 9410-9420, 2017. Abstract | Links | BibTeX | タグ: Disaster Recovery Networks, QoE @article{Suto2017Post, title = {Post-Disaster User Location Maneuvering Method for Improving the QoE Guaranteed Service Time in Energy Harvesting Small Cell Networks}, author = {Katsuya Suto and Hiroki Nishiyama and Nei Kato}, doi = {10.1109/TVT.2017.2702750}, year = {2017}, date = {2017-10-01}, journal = {IEEE Transactions on Vehicular Technology}, volume = {66}, number = {10}, pages = {9410-9420}, abstract = {The concept of energy harvesting small cell networks (EH-SCNs) has attracted a great deal of attention due to their potential to meet the exponential growth of mobile data traffic with low capital expenditure and operating expenditure. In addition, they are expected to work as a postdisaster wireless access network since exploiting green energy sources to power small cell base stations can overcome the power disruption caused by disasters. However, since the amount of harvested power is not enough for the stable network operation, the networks need to equipped with energy-efficient networking techniques. Additionally, in order to share the accurate postdisaster information, the networks should satisfy a certain quality of experience (QoE) of users in disaster areas. To deal with these challenges, we propose a user location maneuvering method, which advisory controls user's movement to improve the service time of EH-SCNs while guaranteeing a certain QoE level. We also propose an algorithm based on particle swarm optimization, which is configured with appropriate settings to find the best location of users efficiently. Extensive computer simulations show that the proposed maneuvering method can improve the QoE guaranteed service ratio, compared with the existing network operation approaches.}, keywords = {Disaster Recovery Networks, QoE}, pubstate = {published}, tppubtype = {article} } The concept of energy harvesting small cell networks (EH-SCNs) has attracted a great deal of attention due to their potential to meet the exponential growth of mobile data traffic with low capital expenditure and operating expenditure. In addition, they are expected to work as a postdisaster wireless access network since exploiting green energy sources to power small cell base stations can overcome the power disruption caused by disasters. However, since the amount of harvested power is not enough for the stable network operation, the networks need to equipped with energy-efficient networking techniques. Additionally, in order to share the accurate postdisaster information, the networks should satisfy a certain quality of experience (QoE) of users in disaster areas. To deal with these challenges, we propose a user location maneuvering method, which advisory controls user's movement to improve the service time of EH-SCNs while guaranteeing a certain QoE level. We also propose an algorithm based on particle swarm optimization, which is configured with appropriate settings to find the best location of users efficiently. Extensive computer simulations show that the proposed maneuvering method can improve the QoE guaranteed service ratio, compared with the existing network operation approaches. |
Shan Zhang, Peter He, Katsuya Suto, Peng Yang, Lian Zhao, Sherman Shen Traffic Steering Assisted Mobile Edge Caching: Exploiting Spatial Content Diversity Gain Conference in Proc. IEEE GLOBECOM 2017, 2017. @conference{Shan2018Traffic, title = {Traffic Steering Assisted Mobile Edge Caching: Exploiting Spatial Content Diversity Gain}, author = {Shan Zhang and Peter He and Katsuya Suto and Peng Yang and Lian Zhao and Sherman Shen}, url = {https://ieeexplore.ieee.org/document/8254676}, year = {2017}, date = {2017-12-04}, booktitle = {in Proc. IEEE GLOBECOM 2017}, keywords = {MEC}, pubstate = {published}, tppubtype = {conference} } |
Tiago Gama Rodrigues, Katsuya Suto, Hiroki Nishiyama, Nei Kato A PSO Model with VM Migration and Transmission Power Control for Low Service Delay in the Multiple Cloudlets ECC Scenario Conference in Proc. IEEE ICC2017, 2017. @conference{Tiago2017ICC, title = {A PSO Model with VM Migration and Transmission Power Control for Low Service Delay in the Multiple Cloudlets ECC Scenario}, author = {Tiago Gama Rodrigues and Katsuya Suto and Hiroki Nishiyama and Nei Kato}, year = {2017}, date = {2017-05-01}, booktitle = {in Proc. IEEE ICC2017}, keywords = {MEC}, pubstate = {published}, tppubtype = {conference} } |
2016 |
Hideki Kuribayashi, Katsuya Suto, Hiroki Nishiyama, Nei Kato, Kimihiro Mizutani, Takeru Inoue, Osamu Akashi A Mobility-Based Mode Selection Technique for Fair Spatial Dissemination of Data in Multi-Channel Device-to-Device Communication Conference in Proc. IEEE ICC 2016, 2016. BibTeX | タグ: Disaster Recovery Networks @conference{Kuribayashi2016ICC, title = {A Mobility-Based Mode Selection Technique for Fair Spatial Dissemination of Data in Multi-Channel Device-to-Device Communication}, author = {Hideki Kuribayashi and Katsuya Suto and Hiroki Nishiyama and Nei Kato and Kimihiro Mizutani and Takeru Inoue and Osamu Akashi}, year = {2016}, date = {2016-05-01}, booktitle = {in Proc. IEEE ICC 2016}, keywords = {Disaster Recovery Networks}, pubstate = {published}, tppubtype = {conference} } |
Tiago Gama Rodrigues, Katsuya Suto, Hiroki Nishiyama, Nei Kato, Kimihiro Mizutani, Takeru Inoue, Osamu Akashi Towards a Low-Delay Edge Cloud Computing Through a Combined Communication and Computation Approach Conference in Proc. IEEE 84th VTC2016-Fall, 2016. @conference{Tiago2016VTC, title = {Towards a Low-Delay Edge Cloud Computing Through a Combined Communication and Computation Approach}, author = {Tiago Gama Rodrigues and Katsuya Suto and Hiroki Nishiyama and Nei Kato and Kimihiro Mizutani and Takeru Inoue and Osamu Akashi}, year = {2016}, date = {2016-09-01}, booktitle = {in Proc. IEEE 84th VTC2016-Fall}, keywords = {MEC}, pubstate = {published}, tppubtype = {conference} } |
Katsuya Suto, Tiago Gama Rodrigues, Hiroki Nishiyama, Nei Kato, Hirotaka Ujikawa, Ken-Ichi Suzuki QoE-Guaranteed and Sustainable User Position Guidance for Post-Disaster Cloud Radio Access Network Conference in Proc. IEEE GLOBECOM 2016, 2016. BibTeX | タグ: Disaster Recovery Networks, QoE @conference{Suto2016GCOM, title = {QoE-Guaranteed and Sustainable User Position Guidance for Post-Disaster Cloud Radio Access Network}, author = {Katsuya Suto and Tiago Gama Rodrigues and Hiroki Nishiyama and Nei Kato and Hirotaka Ujikawa and Ken-Ichi Suzuki}, year = {2016}, date = {2016-12-01}, booktitle = {in Proc. IEEE GLOBECOM 2016}, keywords = {Disaster Recovery Networks, QoE}, pubstate = {published}, tppubtype = {conference} } |
2015 |
Katsuya Suto, Hiroki Nishiyama, Nei Kato,, Chih-Wei Huang An Energy-Efficient and Delay-Aware Wireless Computing System for Industrial Wireless Sensor Networks Journal Article IEEE Access, 3 , pp. 1026-1035, 2015. Abstract | Links | BibTeX | タグ: WSN @article{Suto2015An, title = {An Energy-Efficient and Delay-Aware Wireless Computing System for Industrial Wireless Sensor Networks}, author = {Katsuya Suto and Hiroki Nishiyama and Nei Kato, and Chih-Wei Huang}, doi = {10.1109/ACCESS.2015.2443171}, year = {2015}, date = {2015-06-15}, journal = {IEEE Access}, volume = {3}, pages = {1026-1035}, abstract = {Industrial wireless sensor networks have attracted much attention as a cornerstone to making the smart factories real. Utilizing industrial wireless sensor networks as a base for smart factories makes it possible to optimize the production line without human resources, since it provides industrial Internet of Things service, where various types of data are collected from sensors and mined to control the machines based on the analysis result. On the other hand, a fog computing node, which executes such real-time feedback control, should be capable of real-time data collection, management, and processing. To achieve these requirements, in this paper, we introduce wireless computing system (WCS) as a fog computing node. Since there are a lot of servers and each server has 60 GHz antennas to connect to other servers and sensors, WCS has high collecting and processing capabilities. However, in order to fulfill a demand for real-time feedback control, WCS needs to satisfy an acceptable delay for data collection. In addition, lower power consumption is required in order to reduce the cost for the factory operation. Therefore, we propose an energy-efficient and delay-aware WCS. Since there is a tradeoff relationship between the power consumption and the delay for data collection, our proposed system controls the sleep schedule and the number of links to minimize the power consumption while satisfying an acceptable delay constraint. Furthermore, the effectiveness of our proposed system is evaluated through extensive computer simulations.}, keywords = {WSN}, pubstate = {published}, tppubtype = {article} } Industrial wireless sensor networks have attracted much attention as a cornerstone to making the smart factories real. Utilizing industrial wireless sensor networks as a base for smart factories makes it possible to optimize the production line without human resources, since it provides industrial Internet of Things service, where various types of data are collected from sensors and mined to control the machines based on the analysis result. On the other hand, a fog computing node, which executes such real-time feedback control, should be capable of real-time data collection, management, and processing. To achieve these requirements, in this paper, we introduce wireless computing system (WCS) as a fog computing node. Since there are a lot of servers and each server has 60 GHz antennas to connect to other servers and sensors, WCS has high collecting and processing capabilities. However, in order to fulfill a demand for real-time feedback control, WCS needs to satisfy an acceptable delay for data collection. In addition, lower power consumption is required in order to reduce the cost for the factory operation. Therefore, we propose an energy-efficient and delay-aware WCS. Since there is a tradeoff relationship between the power consumption and the delay for data collection, our proposed system controls the sleep schedule and the number of links to minimize the power consumption while satisfying an acceptable delay constraint. Furthermore, the effectiveness of our proposed system is evaluated through extensive computer simulations. |
Keisuke Miyanabe, Katsuya Suto, Zubair Md. Fadlullah, Hiroki Nishiyama, Nei Kato, Hirotaka Ujikawa, Ken-Ichi Suzuki A Cloud Radio Access Network with Power over Fiber toward 5G Network: QoE-Guaranteed Design and Operation Journal Article IEEE Wireless Communications, 22 (4), pp. 58-64, 2015. Abstract | Links | BibTeX | タグ: FiWi, Green Networks, QoE @article{Miyanabe2015A, title = {A Cloud Radio Access Network with Power over Fiber toward 5G Network: QoE-Guaranteed Design and Operation}, author = {Keisuke Miyanabe and Katsuya Suto and Zubair Md. Fadlullah and Hiroki Nishiyama and Nei Kato and Hirotaka Ujikawa and Ken-Ichi Suzuki}, doi = {10.1109/MWC.2015.7224728}, year = {2015}, date = {2015-08-01}, journal = {IEEE Wireless Communications}, volume = {22}, number = {4}, pages = {58-64}, abstract = {While the concept of Cloud Radio Access Networks (C-RANs) presents a promising solution to provide required quality of service (QoS) for the future network environment, i.e., more than 10 Gbps capacity, less than 1 ms latency, and connectivity for numerous devices, it is still susceptible to quality of experience (QoE) problems. Until now, only a few researchers considered the design and operation of C-RANs based on QoE. In this article we describe our envisioned C-RAN based on passive optical networks (PONs) exploiting power over fiber (PoF), which can be installed with low installation cost and is capable of providing communication services without external power supply for remote radio head (RRH), and describe QoE requirement on the envisioned network. For all users in the envisioned network to satisfy their QoE, effective network design and operation approaches are then presented. Our proposed design and operation approaches demonstrate how to construct the envisioned network, i.e. the numbers of RRHs and optical line terminals (OLTs), and sleep scheduling of RRHs for an energy-efficient optical power transmission.}, keywords = {FiWi, Green Networks, QoE}, pubstate = {published}, tppubtype = {article} } While the concept of Cloud Radio Access Networks (C-RANs) presents a promising solution to provide required quality of service (QoS) for the future network environment, i.e., more than 10 Gbps capacity, less than 1 ms latency, and connectivity for numerous devices, it is still susceptible to quality of experience (QoE) problems. Until now, only a few researchers considered the design and operation of C-RANs based on QoE. In this article we describe our envisioned C-RAN based on passive optical networks (PONs) exploiting power over fiber (PoF), which can be installed with low installation cost and is capable of providing communication services without external power supply for remote radio head (RRH), and describe QoE requirement on the envisioned network. For all users in the envisioned network to satisfy their QoE, effective network design and operation approaches are then presented. Our proposed design and operation approaches demonstrate how to construct the envisioned network, i.e. the numbers of RRHs and optical line terminals (OLTs), and sleep scheduling of RRHs for an energy-efficient optical power transmission. |
Katsuya Suto, Keisuke Miyanabe, Hiroki Nishiyama, Nei Kato, Hirotaka Ujikawa, Ken-Ichi Suzuki QoE-Guaranteed and Power-Efficient Network Operation for Cloud Radio Access Network with Power over Fiber Journal Article IEEE Transactions on Computational Social Systems, 2 (4), pp. 127-136, 2015. Abstract | Links | BibTeX | タグ: Green Networks, QoE @article{Suto2016QoE, title = {QoE-Guaranteed and Power-Efficient Network Operation for Cloud Radio Access Network with Power over Fiber}, author = {Katsuya Suto and Keisuke Miyanabe and Hiroki Nishiyama and Nei Kato and Hirotaka Ujikawa and Ken-Ichi Suzuki}, doi = {10.1109/TCSS.2016.2518208}, year = {2015}, date = {2015-12-01}, journal = {IEEE Transactions on Computational Social Systems}, volume = {2}, number = {4}, pages = {127-136}, abstract = {A concept of cloud radio access networks (C-RANs) is becoming a popular solution to support the required communication quality for new emerging service in the future network environment, i.e., more than 10 Gbps capacity, less than 1 ms latency, and connectivity for numerous devices. In this paper, we envision a C-RAN based on passive optical network (PON) exploiting power over fiber (PoF), which achieves low installation and operation costs since it is capable of providing communication services without external power supply for large amount of remote radio heads (RRHs). This network, however, needs to reduce the optical transmission power of PoF due to the fiber fuse issue. Additionally, the diversification of services, devices, and personality indicates the need to improve user satisfaction, i.e., quality of experience (QoE), based on the user's perspective, which is different from previous approaches that aim to guarantee quality of services (QoS). Therefore, we propose a QoE-guaranteed and power-efficient network operation strategy. Our proposed operation is able to reduce the transmission power while satisfying the QoE constraint by controlling both the schedule of RRH's sleep and optical transmission power of PoF. Furthermore, the effectiveness of our proposed operation scheme is evaluated through extensive computer simulations.}, keywords = {Green Networks, QoE}, pubstate = {published}, tppubtype = {article} } A concept of cloud radio access networks (C-RANs) is becoming a popular solution to support the required communication quality for new emerging service in the future network environment, i.e., more than 10 Gbps capacity, less than 1 ms latency, and connectivity for numerous devices. In this paper, we envision a C-RAN based on passive optical network (PON) exploiting power over fiber (PoF), which achieves low installation and operation costs since it is capable of providing communication services without external power supply for large amount of remote radio heads (RRHs). This network, however, needs to reduce the optical transmission power of PoF due to the fiber fuse issue. Additionally, the diversification of services, devices, and personality indicates the need to improve user satisfaction, i.e., quality of experience (QoE), based on the user's perspective, which is different from previous approaches that aim to guarantee quality of services (QoS). Therefore, we propose a QoE-guaranteed and power-efficient network operation strategy. Our proposed operation is able to reduce the transmission power while satisfying the QoE constraint by controlling both the schedule of RRH's sleep and optical transmission power of PoF. Furthermore, the effectiveness of our proposed operation scheme is evaluated through extensive computer simulations. |
Katsuya Suto, Hiroki Nishiyama, Nei Kato, Takayuki Nakachi, Toshikazu Sakano, Atsushi Takahara A Failure-Tolerant and Spectrum-Efficient Wireless Data Center Network Design for Improving Performance of Big Date Mining Conference in Proc. IEEE 81th VTC 2015-Spring, 2015. BibTeX | タグ: MEC, Overlay Networks @conference{Suto2015VTC, title = {A Failure-Tolerant and Spectrum-Efficient Wireless Data Center Network Design for Improving Performance of Big Date Mining}, author = {Katsuya Suto and Hiroki Nishiyama and Nei Kato and Takayuki Nakachi and Toshikazu Sakano and Atsushi Takahara}, year = {2015}, date = {2015-05-01}, booktitle = {in Proc. IEEE 81th VTC 2015-Spring}, keywords = {MEC, Overlay Networks}, pubstate = {published}, tppubtype = {conference} } |
Yunseong Lee, Katsuya Suto, Hiroki Nishiyama, Nei Kato, Hirotaka Ujikawa, Ken-Ichi Suzuki A Novel Network Design and Operation for Reducing Transmission Power in Cloud Radio Access Network with Power over Fiber Conference in Proc. IEEE/CIC ICCC 2015, 2015. BibTeX | タグ: FiWi, Green Networks @conference{Lee2015ICCC, title = {A Novel Network Design and Operation for Reducing Transmission Power in Cloud Radio Access Network with Power over Fiber}, author = {Yunseong Lee and Katsuya Suto and Hiroki Nishiyama and Nei Kato and Hirotaka Ujikawa and Ken-Ichi Suzuki}, year = {2015}, date = {2015-11-01}, booktitle = {in Proc. IEEE/CIC ICCC 2015}, keywords = {FiWi, Green Networks}, pubstate = {published}, tppubtype = {conference} } |
2014 |
Katsuya Suto, Hiroki Nishiyama, Nei Kato, Takayuki Nakachi, Tatsuya Fujii, Atsushi Takahara Toward Integrating Overlay and Physical Networks for Robust Parallel Processing Architecture Journal Article IEEE Network, 28 (4), pp. 40-45, 2014. Abstract | Links | BibTeX | タグ: Overlay Networks @article{Suto2014Toward, title = {Toward Integrating Overlay and Physical Networks for Robust Parallel Processing Architecture}, author = {Katsuya Suto and Hiroki Nishiyama and Nei Kato and Takayuki Nakachi and Tatsuya Fujii and Atsushi Takahara}, doi = {10.1109/JSAC.2013.SUP.0513022}, year = {2014}, date = {2014-07-31}, journal = {IEEE Network}, volume = {28}, number = {4}, pages = {40-45}, abstract = {Hierarchical unstructured peer-to-peer (P2P) networks for file sharing systems such as Gnutella and Kazaa have made a tremendous achievement in the last decade. However, while these P2P networks can be tolerant to churn, i.e., the dynamics of peer participation and departure (or fault), there still remains the issue of vulnerability to Denial of Service (DoS) attacks, i.e., when the highest degree peers are removed. In order to overcome this shortcoming, we focus on a bimodal degree distribution, which is tolerant to both churn and DoS attacks. However, the network topology affects the network stability that was not taken into considered in the previous works. Therefore, we analyze the optimal network topology for DoS attack tolerance, and accordingly develop the peer joining procedure to construct and maintain the proposed network topology. Our proposed scheme is dubbed THUP (churn/DoS Tolerant, Hierarchical, Unstructured, P2P network). Performance evaluation conducted through computer simulations shows that THUP substantially improves the stability and communication efficiency compared with other existing P2P networking structures.}, keywords = {Overlay Networks}, pubstate = {published}, tppubtype = {article} } Hierarchical unstructured peer-to-peer (P2P) networks for file sharing systems such as Gnutella and Kazaa have made a tremendous achievement in the last decade. However, while these P2P networks can be tolerant to churn, i.e., the dynamics of peer participation and departure (or fault), there still remains the issue of vulnerability to Denial of Service (DoS) attacks, i.e., when the highest degree peers are removed. In order to overcome this shortcoming, we focus on a bimodal degree distribution, which is tolerant to both churn and DoS attacks. However, the network topology affects the network stability that was not taken into considered in the previous works. Therefore, we analyze the optimal network topology for DoS attack tolerance, and accordingly develop the peer joining procedure to construct and maintain the proposed network topology. Our proposed scheme is dubbed THUP (churn/DoS Tolerant, Hierarchical, Unstructured, P2P network). Performance evaluation conducted through computer simulations shows that THUP substantially improves the stability and communication efficiency compared with other existing P2P networking structures. |
Katsuya Suto, Hiroki Nishiyama, Nei Kato, Kimihiro Mizutani, Osamu Akashi, Atsushi Takahara An Overlay-based Data Mining Architecture Tolerant to Physical Network Disruptions Journal Article IEEE Transactions on Emerging Topics in Computing, 2 (3), pp. 292-301, 2014. Abstract | Links | BibTeX | タグ: Overlay Networks @article{Suto2014An, title = {An Overlay-based Data Mining Architecture Tolerant to Physical Network Disruptions}, author = {Katsuya Suto and Hiroki Nishiyama and Nei Kato and Kimihiro Mizutani and Osamu Akashi and Atsushi Takahara}, doi = {10.1109/TETC.2014.2330517}, year = {2014}, date = {2014-09-01}, journal = {IEEE Transactions on Emerging Topics in Computing}, volume = {2}, number = {3}, pages = {292-301}, abstract = {Management scheme for highly scalable big data mining has not been well studied in spite of the fact that big data mining provides many valuable and important information for us. An overlay-based parallel data mining architecture, which executes fully distributed data management and processing by employing the overlay network, can achieve high scalability. However, the overlay-based parallel mining architecture is not capable of providing data mining services in case of the physical network disruption that is caused by router/communication line breakdowns because numerous nodes are removed from the overlay network. To cope with this issue, this paper proposes an overlay network construction scheme based on node location in physical network, and a distributed task allocation scheme using overlay network technology. The numerical analysis indicates that the proposed schemes considerably outperform the conventional schemes in terms of service availability against physical network disruption.}, keywords = {Overlay Networks}, pubstate = {published}, tppubtype = {article} } Management scheme for highly scalable big data mining has not been well studied in spite of the fact that big data mining provides many valuable and important information for us. An overlay-based parallel data mining architecture, which executes fully distributed data management and processing by employing the overlay network, can achieve high scalability. However, the overlay-based parallel mining architecture is not capable of providing data mining services in case of the physical network disruption that is caused by router/communication line breakdowns because numerous nodes are removed from the overlay network. To cope with this issue, this paper proposes an overlay network construction scheme based on node location in physical network, and a distributed task allocation scheme using overlay network technology. The numerical analysis indicates that the proposed schemes considerably outperform the conventional schemes in terms of service availability against physical network disruption. |
Katsuya Suto, Hiroki Nishiyama, Nei Kato, Takayuki Nakachi, Tatsuya Fujii, Atsushi Takahara An Overlay Network Construction Technique for Minimizing the Impact of Physical Network Disruption in Cloud Storage Systems Conference in proc. ICNC 2014, 2014. BibTeX | タグ: Overlay Networks @conference{Suto2014ICNC, title = {An Overlay Network Construction Technique for Minimizing the Impact of Physical Network Disruption in Cloud Storage Systems}, author = {Katsuya Suto and Hiroki Nishiyama and Nei Kato and Takayuki Nakachi and Tatsuya Fujii and Atsushi Takahara}, year = {2014}, date = {2014-02-01}, booktitle = {in proc. ICNC 2014}, pages = {68-72}, keywords = {Overlay Networks}, pubstate = {published}, tppubtype = {conference} } |
Shintaro Arai, Katsuya Suto, Hiroki Nishiyama An Energy Efficient Upload Transmission Method in Storage-Embedded Wireless Mesh Networks Conference in proc. IEEE ICC 2014, 2014. @conference{Arai2014ICC, title = {An Energy Efficient Upload Transmission Method in Storage-Embedded Wireless Mesh Networks}, author = {Shintaro Arai and Katsuya Suto and Hiroki Nishiyama}, year = {2014}, date = {2014-06-01}, booktitle = {in proc. IEEE ICC 2014}, pages = {pp. 2785-2790}, keywords = {WMN}, pubstate = {published}, tppubtype = {conference} } |
Katsuya Suto, Hiroki Nishiyama, Nei Kato Context-aware Task Allocation for Fast Parallel Big Data Processing in Optical-Wireless Networks Conference in proc. IWCMC 2014, 2014. @conference{Suto2014IWCMC, title = {Context-aware Task Allocation for Fast Parallel Big Data Processing in Optical-Wireless Networks }, author = {Katsuya Suto and Hiroki Nishiyama and Nei Kato}, year = {2014}, date = {2014-08-01}, booktitle = {in proc. IWCMC 2014}, pages = {423-428}, keywords = {FiWi}, pubstate = {published}, tppubtype = {conference} } |
2013 |
Katsuya Suto, Hiroki Nishiyama, Nei Kato, Takayuki Nakachi, Tatsuya Fujii, Atsushi Takahara THUP: A P2P Network Robust to Churn and DoS Attack based on Bimodal Degree Distribution Journal Article IEEE Journal on Selected Areas in Communications, 31 (9), pp. 247-256, 2013. Abstract | Links | BibTeX | タグ: Overlay Networks @article{Suto2013THUP, title = {THUP: A P2P Network Robust to Churn and DoS Attack based on Bimodal Degree Distribution}, author = {Katsuya Suto and Hiroki Nishiyama and Nei Kato and Takayuki Nakachi and Tatsuya Fujii and Atsushi Takahara}, doi = {10.1109/JSAC.2013.SUP.0513022}, year = {2013}, date = {2013-09-01}, journal = {IEEE Journal on Selected Areas in Communications}, volume = {31}, number = {9}, pages = {247-256}, abstract = {Hierarchical unstructured peer-to-peer (P2P) networks for file sharing systems such as Gnutella and Kazaa have made a tremendous achievement in the last decade. However, while these P2P networks can be tolerant to churn, i.e., the dynamics of peer participation and departure (or fault), there still remains the issue of vulnerability to Denial of Service (DoS) attacks, i.e., when the highest degree peers are removed. In order to overcome this shortcoming, we focus on a bimodal degree distribution, which is tolerant to both churn and DoS attacks. However, the network topology affects the network stability that was not taken into considered in the previous works. Therefore, we analyze the optimal network topology for DoS attack tolerance, and accordingly develop the peer joining procedure to construct and maintain the proposed network topology. Our proposed scheme is dubbed THUP (churn/DoS Tolerant, Hierarchical, Unstructured, P2P network). Performance evaluation conducted through computer simulations shows that THUP substantially improves the stability and communication efficiency compared with other existing P2P networking structures.}, keywords = {Overlay Networks}, pubstate = {published}, tppubtype = {article} } Hierarchical unstructured peer-to-peer (P2P) networks for file sharing systems such as Gnutella and Kazaa have made a tremendous achievement in the last decade. However, while these P2P networks can be tolerant to churn, i.e., the dynamics of peer participation and departure (or fault), there still remains the issue of vulnerability to Denial of Service (DoS) attacks, i.e., when the highest degree peers are removed. In order to overcome this shortcoming, we focus on a bimodal degree distribution, which is tolerant to both churn and DoS attacks. However, the network topology affects the network stability that was not taken into considered in the previous works. Therefore, we analyze the optimal network topology for DoS attack tolerance, and accordingly develop the peer joining procedure to construct and maintain the proposed network topology. Our proposed scheme is dubbed THUP (churn/DoS Tolerant, Hierarchical, Unstructured, P2P network). Performance evaluation conducted through computer simulations shows that THUP substantially improves the stability and communication efficiency compared with other existing P2P networking structures. |
Katsuya Suto, Panu Avakul, Hiroki Nishiyama, Nei Kato An Efficient Data Transfer Method for Distributed Storage System over Satellite Networks Conference in Proc. IEEE VTC 2013-Spring, 2013. BibTeX | タグ: Disaster Recovery Networks @conference{Suto2013An, title = {An Efficient Data Transfer Method for Distributed Storage System over Satellite Networks}, author = {Katsuya Suto and Panu Avakul and Hiroki Nishiyama and Nei Kato}, year = {2013}, date = {2013-06-01}, booktitle = {in Proc. IEEE VTC 2013-Spring}, keywords = {Disaster Recovery Networks}, pubstate = {published}, tppubtype = {conference} } |
2012 |
Katsuya Suto, Hiroki Nishiyama, Sherman Shen, Nei Kato Designing P2P Networks Tolerant to Attacks and Faults based on Bimodal Degree Distribution Journal Article Academy Publisher Journal of Communications, 7 (8), pp. 587-595, 2012. Links | BibTeX | タグ: Overlay Networks @article{Suto2012Designing, title = {Designing P2P Networks Tolerant to Attacks and Faults based on Bimodal Degree Distribution}, author = {Katsuya Suto and Hiroki Nishiyama and Sherman Shen and Nei Kato}, doi = {10.4304/jcm.7.8.587-595}, year = {2012}, date = {2012-08-01}, journal = {Academy Publisher Journal of Communications}, volume = {7}, number = {8}, pages = {587-595}, keywords = {Overlay Networks}, pubstate = {published}, tppubtype = {article} } |
Katsuya Suto, Hiroki Nishiyama, Hideaki Yoshino, Keisuke Ishibashi, Nei Kato A Method to Construct an Attack and Fault Tolerant Scalable Distributed Network Conference in Proc. CMC 2012, 2012. BibTeX | タグ: Overlay Networks @conference{Suto2012A, title = {A Method to Construct an Attack and Fault Tolerant Scalable Distributed Network}, author = {Katsuya Suto and Hiroki Nishiyama and Hideaki Yoshino and Keisuke Ishibashi and Nei Kato}, year = {2012}, date = {2012-05-01}, booktitle = {in Proc. CMC 2012}, keywords = {Overlay Networks}, pubstate = {published}, tppubtype = {conference} } |
Publicationsstlab2020-02-28T14:35:55+09:00
2021 |
Space-Frequency-Interpolated Radio Map Journal Article IEEE Transactions on Vehicular Technology, 70 (1), pp. 714-725, 2021. |
Image-Driven Spatial Interpolation with Deep Learning for Radio Map Construction Journal Article IEEE Wireless Communications Letters, 10 (6), pp. 1222-1226, 2021. |
Harvest-Then-Transmit-Based TDMA Protocol with Statistical Channel State Information for Wireless Powered Sensor Networks Conference in Proc. VTC2021-Spring, 2021. |
Deterministic Video Streaming with Deep Learning Enabled Base Station Intervention for Stable Remote Driving System Conference in Proc. ICC2021 workshop - TsDN, 2021. |
2020 |
Machine Learning meets Computation and Communication Control in Evolving Edge and Cloud Journal Article IEEE Communications Surveys and Tutorials, 22 (1), pp. 38-67, 2020. |
SICNN: Spatial Interpolation with Convolutional Neural Networks for Radio Environment Mapping Conference in Proc. ICAIIC 2020, 2020. |
Spatial Extrapolation with Generative Adversarial Networks for Radio Map Construction Conference in Proc. ICETC 2020, 2020. |
On Radio Propagation Estimation based on Deep Learning withConvolution and Self-attention Conference in Proc. ICETC 2020, 2020. |
電波伝搬推定システム、電波伝搬推定方法および生成部の製造方法 Patent 特願2020-204831, 2020. |
2019 |
A Control-Theoretic Approach for Cell Zooming of Energy Harvesting Small Cell Networks Journal Article IEEE Transactions on Green Communications and Networking, 3 (2), pp. 329 - 342, 2019. |
Edge Cloud Server Deployment with Transmission Power Control through Machine Learning for 6G Internet of Things Journal Article IEEE Transactions on Emerging Topics in Computing, 2019. |
Hyperparameter Study of Machine Learning Solutions for the Edge Server Deployment Problem Conference in Proc. IEEE 90th VTC2019-Fall, 2019. |
Privacy-preserved Cell Zooming with Distributed Optimization in Green Networks Conference in Proc. IEEE 90th VTC2019-Fall, 2019. |
Crowdsensing Based Spectrum Database with Total Variation Regularization Conference in Proc. IEEE DySPAN 2019 Workshop on Data-Driven Dynamic Spectrum Sharing, 2019. |
2018 |
Model Predictive Joint Transmit Power Control for Improving System Availability in Energy-Harvesting Wireless Mesh Networks Journal Article IEEE Communications Letters, 22 (10), pp. 2112-2115, 2018. |
Cloudlets Activation Scheme for Scalable Mobile Edge Computing with Transmission Power Control and Virtual Machine Migration Journal Article IEEE Transactions on Computers, 67 (9), pp. 1287-1300, 2018. |
Secure and Efficient Privacy-Preserving Ciphertext Retrieval in Connected Vehicular Cloud Computing Journal Article IEEE Network, 32 (3), pp. 52-57, 2018. |
Cooperative Edge Caching in User-Centric Clustered Mobile Networks Journal Article IEEE Transactions on Mobile Computing, 17 (8), pp. 1791-1805, 2018. |
Model Predictive Cell Zooming for Energy-harvesting Small Cell Networks Conference in Proc. IEEE ICC 2018, 2018. |
2017 |
Hybrid Method for Minimizing Service Delay in Edge Cloud Computing through VM Migration and Transmission Power Control Journal Article IEEE Transactions on Computers, 66 (5), pp. 810-819, 2017. |
Cyber Physical Systems for Intelligent Disaster Response Networks: Conceptual Proposal and Field Experiment Journal Article IEEE Network, 31 (4), pp. 120-128, 2017. |
Post-Disaster User Location Maneuvering Method for Improving the QoE Guaranteed Service Time in Energy Harvesting Small Cell Networks Journal Article IEEE Transactions on Vehicular Technology, 66 (10), pp. 9410-9420, 2017. |
Traffic Steering Assisted Mobile Edge Caching: Exploiting Spatial Content Diversity Gain Conference in Proc. IEEE GLOBECOM 2017, 2017. |
A PSO Model with VM Migration and Transmission Power Control for Low Service Delay in the Multiple Cloudlets ECC Scenario Conference in Proc. IEEE ICC2017, 2017. |
2016 |
A Mobility-Based Mode Selection Technique for Fair Spatial Dissemination of Data in Multi-Channel Device-to-Device Communication Conference in Proc. IEEE ICC 2016, 2016. |
Towards a Low-Delay Edge Cloud Computing Through a Combined Communication and Computation Approach Conference in Proc. IEEE 84th VTC2016-Fall, 2016. |
QoE-Guaranteed and Sustainable User Position Guidance for Post-Disaster Cloud Radio Access Network Conference in Proc. IEEE GLOBECOM 2016, 2016. |
2015 |
An Energy-Efficient and Delay-Aware Wireless Computing System for Industrial Wireless Sensor Networks Journal Article IEEE Access, 3 , pp. 1026-1035, 2015. |
A Cloud Radio Access Network with Power over Fiber toward 5G Network: QoE-Guaranteed Design and Operation Journal Article IEEE Wireless Communications, 22 (4), pp. 58-64, 2015. |
QoE-Guaranteed and Power-Efficient Network Operation for Cloud Radio Access Network with Power over Fiber Journal Article IEEE Transactions on Computational Social Systems, 2 (4), pp. 127-136, 2015. |
A Failure-Tolerant and Spectrum-Efficient Wireless Data Center Network Design for Improving Performance of Big Date Mining Conference in Proc. IEEE 81th VTC 2015-Spring, 2015. |
A Novel Network Design and Operation for Reducing Transmission Power in Cloud Radio Access Network with Power over Fiber Conference in Proc. IEEE/CIC ICCC 2015, 2015. |
2014 |
Toward Integrating Overlay and Physical Networks for Robust Parallel Processing Architecture Journal Article IEEE Network, 28 (4), pp. 40-45, 2014. |
An Overlay-based Data Mining Architecture Tolerant to Physical Network Disruptions Journal Article IEEE Transactions on Emerging Topics in Computing, 2 (3), pp. 292-301, 2014. |
An Overlay Network Construction Technique for Minimizing the Impact of Physical Network Disruption in Cloud Storage Systems Conference in proc. ICNC 2014, 2014. |
An Energy Efficient Upload Transmission Method in Storage-Embedded Wireless Mesh Networks Conference in proc. IEEE ICC 2014, 2014. |
Context-aware Task Allocation for Fast Parallel Big Data Processing in Optical-Wireless Networks Conference in proc. IWCMC 2014, 2014. |
2013 |
THUP: A P2P Network Robust to Churn and DoS Attack based on Bimodal Degree Distribution Journal Article IEEE Journal on Selected Areas in Communications, 31 (9), pp. 247-256, 2013. |
An Efficient Data Transfer Method for Distributed Storage System over Satellite Networks Conference in Proc. IEEE VTC 2013-Spring, 2013. |
2012 |
Designing P2P Networks Tolerant to Attacks and Faults based on Bimodal Degree Distribution Journal Article Academy Publisher Journal of Communications, 7 (8), pp. 587-595, 2012. |
A Method to Construct an Attack and Fault Tolerant Scalable Distributed Network Conference in Proc. CMC 2012, 2012. |