IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)最新文献_第7页

Efficient VM Migration for Multiple Destination Sites Across a Japan-US OpenFlow Testbed 跨日美OpenFlow测试平台多目标站点的高效虚拟机迁移

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/INFOCOMWKSHPS57453.2023.10226149

Kazumi Igarashi, Akira Nagata, Yohei Okamoto, M. Shibata, Kenichi Kourai, M. Tsuru

{"title":"Efficient VM Migration for Multiple Destination Sites Across a Japan-US OpenFlow Testbed","authors":"Kazumi Igarashi, Akira Nagata, Yohei Okamoto, M. Shibata, Kenichi Kourai, M. Tsuru","doi":"10.1109/INFOCOMWKSHPS57453.2023.10226149","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10226149","url":null,"abstract":"A globally integrated testbed for various experiments of distributed applications based on the edge cloud computing was constructed and operated as part of an international joint research program, Japan-US Network Opportunity 2 (JUNO2). The testbed consists of many virtual machines (VMs) at Kyushu Institute of Technology (Kyutech), The City College of The City University of New York (CCNY), StarBED (a large-scale PC cluster testbed), and RISE (a wide-area OpenFlow testbed) over multiple Layer-2 virtual networks (VLANs) through collaboration with international research and educational networks. Those VLANs are used as the data and the control planes with a single OpenFlow controller and twelve OpenFlow switches. As an example, this paper introduces an experiment of VM migration among CCNY, Kyutech, and StarBED for a global virtual collaborative working environment. An OpenFlow-based multicasting scheme is adopted for efficient use of the bottleneck network bandwidth in replicating a large VM environment from CCNY to two sites in Japan. The implementation details on the global testbed and the experimental results are reported, verifying that the multicast-based transfer halves the elapsed time of VM migration compared with the unicast-based transfer.","PeriodicalId":354290,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132615270","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

RIS-Empowered MEC for URLLC Systems with Digital-Twin-Driven Architecture 基于数字双驱动架构的URLLC系统的ris授权MEC

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/INFOCOMWKSHPS57453.2023.10226132

Sravani Kurma, Keshav Singh, Mayur Katwe, S. Mumtaz, Chih-Peng Li

引用次数: 0

CNERT 2023 TPC Technical Program Committee CNERT 2023 TPC技术计划委员会

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/infocomwkshps57453.2023.10225902

引用次数: 0

Artificial Neural Network and Game Theory for Secure Optimal Charging Station Selection for EVs 电动汽车安全最优充电站选择的人工神经网络与博弈论

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/INFOCOMWKSHPS57453.2023.10225788

Riya Kakkar, Aparna Kumari, Rajesh Gupta, Smita Agrawal, S. Tanwar

{"title":"Artificial Neural Network and Game Theory for Secure Optimal Charging Station Selection for EVs","authors":"Riya Kakkar, Aparna Kumari, Rajesh Gupta, Smita Agrawal, S. Tanwar","doi":"10.1109/INFOCOMWKSHPS57453.2023.10225788","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225788","url":null,"abstract":"The penetration of electric vehicles (EV s) entails the deployment of more charging station (CS) infrastructure to realize the charging requirement issues of the EV s. But, limited installation of charging infrastructure and data security issues require a secure and efficient CS selection mechanism for EV s. Towards this goal, we proposed an Artificial Intelligence (AI) and game theory-based secure CS selection scheme for EVs using blockchain. Blockchain and AI-based proposed scheme provides security and privacy during the communication between participants, i.e., EV s and CSs, for optimal CS selection. Moreover, an incorporated blockchain network with Interplanetary File System (IPFS) strengthens the reliability and cost-efficiency of CS selection by using beyond 5G network and its ultra-intelligent features. Furthermore, the blockchain and AI-based proposed scheme utilizes coalition game theory approach to recommend the optimal CS for EV and balance the fair payoff between the participants in the network. Finally, experimental results show that the proposed scheme yields better results than the conventional approaches considering the performance evaluation metrics such as State of Charge (SoC), profit analysis, and latency comparison.","PeriodicalId":354290,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132385322","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

8th IEEE Wireless-Sec Committee 第八届IEEE无线安全委员会

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/infocomwkshps57453.2023.10226024

引用次数: 0

Sum Computation Rate Maximization in Self-Sustainable RIS-Assisted MEC 自我可持续ris辅助MEC求和率最大化

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/INFOCOMWKSHPS57453.2023.10225948

Han Li, Ming Liu, Bo Gao, Ke Xiong, Pingyi Fan, K. Letaief

引用次数: 0

Ensemble Learning for Predicting Task Connectivity Over Time in Cloud Data Centers 集成学习用于预测云数据中心中任务随时间的连通性

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/INFOCOMWKSHPS57453.2023.10225964

Mustafa Daraghmeh, A. Agarwal, Y. Jararweh

{"title":"Ensemble Learning for Predicting Task Connectivity Over Time in Cloud Data Centers","authors":"Mustafa Daraghmeh, A. Agarwal, Y. Jararweh","doi":"10.1109/INFOCOMWKSHPS57453.2023.10225964","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225964","url":null,"abstract":"The rapid growth and interdependencies of cloud-hosted services and applications have made it imperative to optimize data center resource management while maintaining low operating costs. Inefficient resource use, rising energy consumption, and operating costs impact cloud provider's ability to provide high-quality services on an elastic basis. However, changing the selection and decision-making processes based on how the tasks are set up can improve scheduling and resource management in cloud data centers. In this paper, we develop a multivariate time series prediction model for task connectivity based on windowing characterization and ensemble learning methods. The high cardinality features are handled using a counter encoder, and the task trace data is transformed using a sliding window, from which features are extracted and used in conjunction with the task profile data to train and tune the candidate estimators. The best model outcomes are then used to construct an ensembled estimator. As part of the evaluation, a baseline comparison is performed in order to determine how well ensemble learning predicts task connectivity over time. The model outcomes are assisted using standard classification metrics such as accuracy, precision, and recall, including the F1 score, Kappa, and Matthews correlation coefficient. The results show that the proposed model outperformed the traditional models in most performance metrics, indicating the successful implementation of an ensemble learning approach for task connectivity predictions in large-scale cloud data centers.","PeriodicalId":354290,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131695120","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

A Lightweight Preprocessing Scheme for Secret Key Generation from MmWave Massive MIMO Channel Measurements 毫米波海量MIMO信道测量密钥生成的轻量级预处理方案

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/INFOCOMWKSHPS57453.2023.10226124

Lijun Yang, Xin-xing Ge, Qianyi Zhu, Lin Guo

{"title":"A Lightweight Preprocessing Scheme for Secret Key Generation from MmWave Massive MIMO Channel Measurements","authors":"Lijun Yang, Xin-xing Ge, Qianyi Zhu, Lin Guo","doi":"10.1109/INFOCOMWKSHPS57453.2023.10226124","DOIUrl":"https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10226124","url":null,"abstract":"Due to the new channel characteristics, previous preprocessing methods for physical layer key generation cannot be directly applied in mmWave massive MIMO systems. Actually, due to the intolerable high computation complexity and time consumption caused by large dimension of massive MIMO channel, even the previous optimal preprocessing method principal component analysis (PCA) is not suitable. To address the problem, in this paper, we propose a lightweight preprocessing approach called beamspace refinement, which is suitable for mmWave massive MIMO channel by exploiting its channel characteristics namely sparsity. The proposed scheme brings the following advantages. 1) It is lightweight. The computational complexity is quiet low. Unlike the PCA scheme, the proposed scheme does not involve the exponential calculation of the number of antennas, which makes it very suitable for mmWave massive MIMO channel. 2) It is robust against noise. Thus, it can be used to generate secret key with quiet high-entropy and high bit agreement ratio even in low SNR regimes. Numerical results show that the proposed approach outperforms the previous method DCT, WT and PCA in terms of bit agreement ratio, and is on par with PCA in terms of key capacity. Besides, the increase of the antennas number can improve key agreement ratio in our scheme, which is beneficial for massive MIMO system.","PeriodicalId":354290,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132176492","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

NG-OPERA 2023 TPC Technical Program Committee NG-OPERA 2023 TPC技术程序委员会

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/infocomwkshps57453.2023.10226071

引用次数: 0

Task Offloading Using Multi-Armed Bandit Optimization in Autonomous Mobile Robots 基于多臂强盗优化的自主移动机器人任务卸载

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2023-05-20 DOI: 10.1109/INFOCOMWKSHPS57453.2023.10226072

Anis ur Rahman, A. Malik, Hasan Ali Khattak, M. Aloqaily

引用次数: 0