2020 16th International Conference on Mobility, Sensing and Networking (MSN)最新文献_第7页

Resilient Caching in Information-Centric Networking 信息中心网络中的弹性缓存

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00097

N. Kamiyama, Rin Hamada

{"title":"Resilient Caching in Information-Centric Networking","authors":"N. Kamiyama, Rin Hamada","doi":"10.1109/MSN50589.2020.00097","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00097","url":null,"abstract":"Information-centric networking (ICN), a new network architecture for efficiently delivering content, has been widely investigated recently. To be widely spread as a social infrastructure, ICN is required to sustain not only network availability, i.e., connectivity between operating routers, but also content availability, i.e., reachability to content, at network failures. In ICN, FIBs (forwarding information bases) at routers are configured so that content requests reach hosts of content providers having the originals of content. Therefore, requests for content whose connectivity to originals is lost cannot be transferred in networks, and the content availability of these content items is lost. However, copies of unavailable content are possibly cached at one or more operating routers in ICN, so content availability can be recovered by promoting one copy cached at operating routers to the original. Therefore, it is desirable to cache content at routers located far from its original to improve the recover probability of unavailable content items. In this paper, we propose a caching strategy of ICN to achieve this goal. Through numerical evaluation, we show that the proposed caching strategy can increase the maximum distance between the originals and cached copies by several percent to about 20% compared with the case simply caching content at all routers in ICN.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"435 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115227748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Game Theory based Joint Task Offloading and Resource Allocation Algorithm for Mobile Edge Computing 基于博弈论的移动边缘计算联合任务卸载与资源分配算法

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00135

Ning Li, Jianen Yan, Zhaoxin Zhang, José-Fernán Martínez, Xin Yuan

{"title":"Game Theory based Joint Task Offloading and Resource Allocation Algorithm for Mobile Edge Computing","authors":"Ning Li, Jianen Yan, Zhaoxin Zhang, José-Fernán Martínez, Xin Yuan","doi":"10.1109/MSN50589.2020.00135","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00135","url":null,"abstract":"Mobile edge computing (MEC) has emerged for reducing energy consumption and latency by allowing mobile users to offload computationally intensive tasks to the MEC server. Due to the spectrum reuse in the network of MEC, the inner-cell interference has a great effect on MEC’s performance. In this paper, for reducing the energy consumption and latency of MEC, we propose a game theory based approach to join task offloading decision and resource allocation together in the MEC system. In this algorithm, the offloading decision, the CPU capacity adjustment, the transmission power control, and the network interference management of mobile users are regarded as a game. In this game, based on the best response strategy, each mobile user makes their own utility maximum rather than the utility of the whole system. We prove that this game is an exact potential game and the Nash equilibrium (NE) of this game exists. We also investigate the properties of this algorithm, including the convergence, the computational complexity, and the Price of anarchy (PoA). We evaluate the performance of this algorithm by simulation. The simulation results illustrate that this algorithm is effective in improving the performance of the multi-user MEC system.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130978908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Reinforcement Learning based Joint Channel/Subframe Selection Scheme for Fair LTE-WiFi Coexistence 基于强化学习的LTE-WiFi公平共存联合信道/子帧选择方案

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00067

Yuki Kishimoto, Xiaoyan Wang, M. Umehira

引用次数: 2

Accurate IoT Device Identification from Merely Packet Length 仅从数据包长度就能准确识别物联网设备

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00132

Yizhen Sun, Shupo Fu, Shigeng Zhang, Hongyu Zhu, Yongfa Li

引用次数: 0

A Near-optimal Protocol for the Subset Selection Problem in RFID Systems RFID系统中子集选择问题的近最优协议

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00022

Xiujun Wang, Zhi Liu, S. Ishihara, Z. Dang, Jie Li

{"title":"A Near-optimal Protocol for the Subset Selection Problem in RFID Systems","authors":"Xiujun Wang, Zhi Liu, S. Ishihara, Z. Dang, Jie Li","doi":"10.1109/MSN50589.2020.00022","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00022","url":null,"abstract":"In many real-time RFID-enabled applications (e.g., logistic tracking and warehouse controlling), a subset of wanted tags is often selected from a tag population for monitoring and querying purposes. How this subset of tags is rapidly selected, which is referred to as the subset selection problem, becomes pivotal for boosting the efficiency in RFID systems. Current state-of-the-art schemes result in high communication latencies, which are far from the optimum, and this degrades the system performance. This problem is addressed in this paper by using a simple Bit-Counting Function BCF(), which has also been employed widely by other protocols in RFID systems. In particular, we first propose a near-OPTimal SeLection protocol, denoted by OPTSL, to rapidly solve this problem based on the simple function BCF(). Second, we prove that the communication time of OPTSL is near-optimal with rigorous theoretical analysis. Finally, we conduct extensive simulations to verify that the communication time of the proposed OPT-SL is not only near-optimal but also significantly less than that of benchmark protocols.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"16 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113976802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SDN Based Computation Offloading for Industrial Internet of Things 基于SDN的工业物联网计算分流

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00072

Gen Li, Shutian Hua, Liang Liu, Xiaolong Zheng, Huadong Ma

引用次数: 2

Data Collection Strategy Based on Drone Technology in Wireless Sensor Networks 基于无人机技术的无线传感器网络数据采集策略

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00035

Bofu Yang, Xiangyu Bai

{"title":"Data Collection Strategy Based on Drone Technology in Wireless Sensor Networks","authors":"Bofu Yang, Xiangyu Bai","doi":"10.1109/MSN50589.2020.00035","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00035","url":null,"abstract":"In recent years, drone technology has developed rapidly. Drone’s low cost, fast and flexible deployment, as well as strong mobility have made it possible to use drone-assisted sensor networks for data collection tasks. In this way, data collection nodes can break through the movement path restriction of traditional nodes, broaden the spatial movement range of nodes, and it is more suitable for data collection in complex environments. In this paper, we proposed a data collection strategy based on drone technology in Wireless Sensor Networks. Kmeans++ clustering method is used for auxiliary clustering and cluster head election in the initial state, which significantly improves the final error of the clustering result. Then, we used drone to assist cluster head election and data collection, which comprehensively considering the relative distance of every sensor node in the cluster and their relative remaining energy. In addition, for some nodes that have not been elected in the previous specified round, a reasonable priority is set to make the energy consumption of sensor nodes in the entire network more balanced. At the same time, we excluded the influence of dead nodes. Compared with many new methods proposed in recent years, the data collection strategy proposed delays the death time of the sensor nodes, reduces the overall energy consumption of the sensor nodes, and has a better performance. This work provides new ideas for the future work.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126627255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Impact of Mode Selection on the Performance of D2D-Unlicensed Communications 模式选择对无授权d2d通信性能的影响

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00102

Ganggui Wang, Celimuge Wu, T. Yoshinaga, Rui Yin

引用次数: 1

Mobility-Aware Offloading and Resource Allocation in MEC-Enabled IoT Networks 支持mec的物联网网络中的移动性感知卸载和资源分配

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00092

Han Hu, Weiwei Song, Qun Wang, Fuhui Zhou, R. Hu

{"title":"Mobility-Aware Offloading and Resource Allocation in MEC-Enabled IoT Networks","authors":"Han Hu, Weiwei Song, Qun Wang, Fuhui Zhou, R. Hu","doi":"10.1109/MSN50589.2020.00092","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00092","url":null,"abstract":"Mobile edge computing (MEC)-enabled Internet of Things (IoT) networks have been deemed a promising paradigm to support massive energy-constrained and computation-limited IoT devices. IoT with mobility has found tremendous new services in the 5G era and the forthcoming 6G eras such as autonomous driving and vehicular communications. However, mobility of IoT devices has not been studied in the sufficient level in the existing works. In this paper, the offloading decision and resource allocation problem is studied with mobility consideration. The long-term average sum service cost of all the mobile IoT devices (MIDs) is minimized by jointly optimizing the CPU-cycle frequencies, the transmit power, and the user association vector of MIDs. An online mobility-aware offloading and resource allocation (OMORA) algorithm is proposed based on Lyapunov optimization and Semi-Definite Programming (SDP). Simulation results demonstrate that our proposed scheme can balance the system service cost and the delay performance, and outperforms other offloading benchmark methods in terms of the system service cost.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125427936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Compressed Multivariate Kernel Density Estimation for WiFi Fingerprint-based Localization 基于WiFi指纹定位的压缩多元核密度估计

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00032

Zhendong Xu, Baoqi Huang, Bing Jia, Wuyungerile Li

引用次数: 0