Clustering hypervisors to minimize failures in mobile cloud computing

被引:18
|
作者
Fekade, Berihun [1 ]
Maksymyuk, Taras [1 ]
Jo, Minho [1 ]
机构
[1] Korea Univ, Dept Comp Convergence Software, Sejong Metro City, South Korea
来源
关键词
mobile cloud computing; hypervisor clustering; hypervisor failure prediction; virtual server; physical server;
D O I
10.1002/wcm.2770
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Resource virtualization has become one of the key super-power mobile computing architecture technologies. As mobile devices and multimedia traffic have increased dramatically, the load on mobile cloud computing systems has become heavier. Under such conditions, mobile cloud system reliability becomes a challenging task. In this paper, we propose a new model using a naive Bayes classifier for hypervisor failure prediction and prevention in mobile cloud computing. We exploit real-time monitoring data in combination with historical maintenance data, which achieves higher accuracy in failure prediction and early failure-risk detection. After detecting hypervisors at risk, we perform live migration of virtual servers within a cluster, which decreases the load and prevents failures in the cloud. We performed a simulation for verification. According to the experimental results, our proposed model shows good accuracy in failure prediction and the possibility of decreasing downtime in a hypervisor service. Copyright (c) 2017 John Wiley & Sons, Ltd.
引用
收藏
页码:3455 / 3465
页数:11
相关论文
共 50 条
  • [31] The Future of Mobile Cloud Computing: Integrating Cloudlets and Mobile Edge Computing
    Jararweh, Yaser
    Doulat, Ahmad
    AlQudah, Omar
    Ahmed, Ejaz
    Al-Ayyoub, Mahmoud
    Benkhelifa, Elhadj
    [J]. 2016 23RD INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS (ICT), 2016,
  • [32] RETRACTED: Mobile Cloud Computing: The Taxonomy and Comparison of Mobile Cloud Computing Application Models (Retracted Article)
    Sosan, Raazia
    Azim, Choudhry Fahad
    [J]. WIRELESS PERSONAL COMMUNICATIONS, 2016, 89 (04) : 1435 - 1435
  • [33] Clustering-Based Emotion Recognition Micro-Service Cloud Framework for Mobile Computing
    Wang, Ping
    Dong, Luobing
    Xu, Yueshen
    Liu, Wei
    Jing, Ningning
    [J]. IEEE ACCESS, 2020, 8 : 49695 - 49704
  • [34] An Innovative Method for Load Balanced Clustering Problem for Wireless Sensor Network in Mobile Cloud Computing
    Sarddar, Debabrata
    Nandi, Enakshmi
    Sharma, Anil Kumar
    Biswas, Biswajit
    Sanyal, Manas Kumar
    [J]. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON FRONTIERS IN INTELLIGENT COMPUTING: THEORY AND APPLICATIONS, (FICTA 2016), VOL 2, 2017, 516 : 325 - 330
  • [35] Research on Mobile Cloud Robotics based on Cloud Computing
    Ma, Xinqiang
    Huang, Yi
    [J]. PROCEEDINGS OF THE 2016 INTERNATIONAL FORUM ON MANAGEMENT, EDUCATION AND INFORMATION TECHNOLOGY APPLICATION, 2016, 47 : 807 - 810
  • [36] Energy Compensated Cloud Assistance in Mobile Cloud Computing
    Champati, Jaya Prakash
    Liang, Ben
    [J]. 2014 IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), 2014, : 392 - 397
  • [37] Special Issue on Visual Computing in the Cloud: Mobile Computing
    Wen, Yonggang
    Chakareski, Jakov
    Frossard, Pascal
    Wu, Di
    Zeng, Wenjun
    [J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2017, 27 (01) : 1 - 5
  • [38] Adaptive Computing Resource Allocation for Mobile Cloud Computing
    Liang, Hongbin
    Xing, Tianyi
    Cai, Lin X.
    Huang, Dijiang
    Peng, Daiyuan
    Liu, Yan
    [J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2013,
  • [39] Reality Mining at the Convergence of Cloud Computing and Mobile Computing
    Steinbauer, Matthias
    Khalil, Ismail
    Kotsis, Gabriele
    [J]. ERCIM NEWS, 2013, (93): : 10 - 11
  • [40] CUDSwap: Tolerating Memory Exhaustion Failures in Cloud Computing
    Navas-Molina, Jose Antonio
    Mishra, Shivakant
    [J]. 2014 INTERNATIONAL CONFERENCE ON CLOUD AND AUTONOMIC COMPUTING (ICCAC 2014), 2014, : 15 - 24