Secure and energy efficient dynamic hierarchical load balancing framework for cloud data centers

被引:5
作者
Chhabra, Sakshi [1 ]
Singh, Ashutosh Kumar [2 ]
机构
[1] Panipat Inst Engn & Technol, Panipat, Haryana, India
[2] Natl Inst Technol, Kurukshetra, Haryana, India
关键词
Cloud computing; Load balancing; Energy consumption; Secure resource allocation; TRAFFIC SCALABILITY; VM PLACEMENT; OPTIMIZATION; STRATEGY; MODEL;
D O I
10.1007/s11042-023-14809-z
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Preserving the secrecy in the cloud systems is one of the considerable discussion for the further adoption of clouds. The side-channel attacks could extract the private information of other users that shares the computing resources through virtualization. Also, cloud customers face security risks in the context of load balancing of Virtual Machines (VMs). This paper proposes a multi-objective hierarchical load balancing framework to address this issue by means of resource requirement analysis, security and allocating an optimized number of computing resources to every application. The framework is recognized as Secure and Energy Efficient Dynamic Hierarchical Load Balancing Framework for Cloud Data Centers (SEE-DHLB). The experimental results show that our secure VM placement algorithm provides excellent security guarantees and better performance, and achieves better optimality and scalability than previous solutions. It improves the security by using grouping reliability up to 62.21%. Moreover, the model minimizes the power consumption as well as resource utilization up to 38.32% and 73.41% respectively over random, sequential, best fit and DHLB VM placement heuristics.
引用
收藏
页码:29843 / 29856
页数:14
相关论文
共 26 条
  • [1] A hyper-heuristic cost optimisation approach for Scientific Workflow Scheduling in cloud computing
    Alkhanak, Ehab Nabiel
    Lee, Sai Peck
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 86 : 480 - 506
  • [2] Dynamic hierarchical load balancing model for cloud data centre networks
    Chhabra, S.
    Singh, A. K.
    [J]. ELECTRONICS LETTERS, 2019, 55 (02) : 94 - +
  • [3] A Probabilistic Model for Finding an Optimal Host Framework and Load Distribution in Cloud Environment
    Chhabra, Sakshi
    Singh, Ashutosh Kumar
    [J]. 6TH INTERNATIONAL CONFERENCE ON SMART COMPUTING AND COMMUNICATIONS, 2018, 125 : 683 - 690
  • [4] Feature selection approach using ensemble learning for network anomaly detection
    Doreswamy
    Hooshmand, Mohammad Kazim
    Gad, Ibrahim
    [J]. CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY, 2020, 5 (04) : 283 - 293
  • [5] A Resource Co-Allocation method for load-balance scheduling over big data platforms
    Dou, Wanchun
    Xu, Xiaolong
    Liu, Xiang
    Yang, Laurence T.
    Wen, Yiping
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 86 : 1064 - 1075
  • [6] Li HY, 2013, CHINA COMMUN, V10, P114, DOI 10.1109/CC.2013.6723884
  • [7] Li Q., 2017, J INF SCI ENG, V33, P2
  • [8] The placement method of resources and applications based on request prediction in cloud data center
    Liang Quan
    Zhang Jing
    Zhang Yong-hui
    Liang Jiu-mei
    [J]. INFORMATION SCIENCES, 2014, 279 : 735 - 745
  • [9] Liang X., 2017, 2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC), P1
  • [10] Optimal VM placement for traffic scalability using Markov chain in cloud data centre networks
    Ma, Teng
    Wu, Jiangxing
    Hu, Yuxiang
    Huang, Wanwei
    [J]. ELECTRONICS LETTERS, 2017, 53 (09) : 602 - 603