A Deep Investigation Into Network Performance in Virtual Machine Based Cloud Environments

被引:0
|
作者
Shea, Ryan [1 ]
Wang, Feng [2 ]
Wang, Haiyang [1 ,3 ]
Liu, Jiangchuan [1 ]
机构
[1] Simon Fraser Univ, Burnaby, BC V5A 1S6, Canada
[2] Univ Mississippi, University, MS 38677 USA
[3] Univ Minnesota, Duluth, MN 55812 USA
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Existing research on cloud network (in) stability has primarily focused on communications between Virtual Machines (VMs) inside a cloud, leaving that of VM communications over higher-latency wide-area networks largely unexplored. Through measurement in real-world cloud platforms, we find that there are prevalent and significant degradation and variation for such VM communications with both TCP and UDP traffic, even over lightly utilized networks. Our in-depth measurement and detailed system analysis reveal that the performance variation and degradation are mainly due to the dual-role of the CPU in both computation and network communication in a VM, and they can be dramatically affected by the CPU's scheduling policy. We provide strong evidence that such issues can be addressed in the hypervisor level and present concrete solutions. Such remedies have been implemented and evaluated in our cloud testbed, showing noticeable improvement for long-haul network communications with VMs.
引用
收藏
页码:1285 / 1293
页数:9
相关论文
共 50 条
  • [31] Workload Generation for Virtual Machine Placement in Cloud Computing Environments
    Ortigoza, Jammily
    Lopez-Pires, Fabio
    Baran, Benjamin
    PROCEEDINGS OF THE 2016 XLII LATIN AMERICAN COMPUTING CONFERENCE (CLEI), 2016,
  • [32] Prediction Model for Virtual Machine Power Consumption in Cloud Environments
    Veni, T.
    Bhanu, S. Mary Saira
    FOURTH INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTER SCIENCE & ENGINEERING (ICRTCSE 2016), 2016, 87 : 122 - 127
  • [33] Virtual Machine Migration-Based Intrusion Detection System in Cloud Environment Using Deep Recurrent Neural Network
    Srinivas, B., V
    Mandal, Indrajit
    Keshavarao, Seetharam
    CYBERNETICS AND SYSTEMS, 2024, 55 (02) : 450 - 470
  • [34] Hybrid Deep Neural Network based Performance Estimation Method for Efficient Offloading on IoT-Cloud Environments
    Son, Yunsik
    Oh, Seman
    Lee, Yangsun
    INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING, 2018, 11 (07): : 23 - 30
  • [35] Artificial neural network-based virtual machine allocation in cloud computing
    Shalu
    Singh, Dinesh
    JOURNAL OF DISCRETE MATHEMATICAL SCIENCES & CRYPTOGRAPHY, 2021, 24 (06): : 1739 - 1750
  • [36] Network Aware Virtual Machine and Image Placement in a Cloud
    Breitgand, David
    Epstein, Amir
    Glikson, Alex
    Israel, Assaf
    Raz, Danny
    2013 9TH INTERNATIONAL CONFERENCE ON NETWORK AND SERVICE MANAGEMENT (CNSM), 2013, : 9 - 17
  • [37] Performance of Container Network Technologies in Cloud Environments
    Bankston, Ryan
    Guo, Jinhua
    2018 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY (EIT), 2018, : 277 - 283
  • [38] Machine Learning-Based Network Intrusion Detection Optimization for Cloud Computing Environments
    Samriya, Jitendra Kumar
    Kumar, Surendra
    Kumar, Mohit
    Wu, Huaming
    Gill, Sukhpal Singh
    IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2024, 70 (04) : 7449 - 7460
  • [39] Metaheuristics algorithms for virtual machine placement in cloud computing environments—a review
    Gabhane J.P.
    Pathak S.
    Thakare N.M.
    Lecture Notes on Data Engineering and Communications Technologies, 2021, 66 : 329 - 349
  • [40] Virtual machine provisioning through satellite communications in federated Cloud environments
    Celesti, Antonio
    Fazio, Maria
    Villari, Massimo
    Puliafito, Antonio
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2012, 28 (01): : 85 - 93