A hybrid ABC-SA based optimized scheduling and resource allocation for cloud environment

被引:0
|
作者
B. Muthulakshmi
K. Somasundaram
机构
[1] St. Peter’s University,Department of Computer Science and Engineering
[2] Avadi,Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology
[3] Vinayaka Mission’s University,undefined
来源
Cluster Computing | 2019年 / 22卷
关键词
Cloud computing; Scheduling; Load balancing; Virtualization; Client–server communication;
D O I
暂无
中图分类号
学科分类号
摘要
Cloud computing is one of the rapidly growing environment in recent days where it interconnects the entire world in human’s day to day life activities. Resource allocation, scheduling and load balancing are the three important things which improve the quality of service in cloud computing. To do this and choose an optimum resource, optimum schedule and through this balancing the load can be obtained using ABC-SA method. The main contribution of this paper is to implement a hybrid optimization algorithm by integrating the functionality of simulated annealing (SA) into artificial bee colony (ABC) algorithm to do the efficient scheduling according to the task size, priority of the request and closest distance between client nodes to a server in the cloud environment. This ABC-SA based optimized scheduling approach has the capability of improving the efficiency in terms of searching optimum resource time where the dynamic and random searching behavior is obtained from SA. ABC-SA is implemented and experimented in the CloudSim tool and the results are verified. The performance of the proposed approach is evaluated by comparing the results with the existing system results.
引用
收藏
页码:10769 / 10777
页数:8
相关论文
共 50 条
  • [1] A hybrid ABC-SA based optimized scheduling and resource allocation for cloud environment
    Muthulakshmi, B.
    Somasundaram, K.
    [J]. CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (Suppl 5): : 10769 - 10777
  • [2] Optimized resource allocation in edge-cloud environment
    Randriamasinoro, Njakarison Menja
    Nguyen, Kim Khoa
    Cheriet, Mohamed
    [J]. 12TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE (SYSCON2018), 2018, : 816 - 823
  • [3] Optimized task scheduling and resource allocation on cloud computing environment using improved differential evolution algorithm
    Tsai, Jinn-Tsong
    Fang, Jia-Cen
    Chou, Jyh-Horng
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2013, 40 (12) : 3045 - 3055
  • [4] A Novel Resource Scheduler for Resource Allocation and Scheduling in Big Data Using Hybrid Optimization Algorithm at Cloud Environment
    Selvaraj, Aarthee
    Rajendran, Prabakaran
    Rajangam, Kanimozhi
    [J]. INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2023, 20 (06) : 863 - 873
  • [5] Optimized task scheduling and resource allocation in cloud computing using PSO based fitness function
    [J]. Yang, Z., 1600, Asian Network for Scientific Information (12):
  • [6] Energy-efficient task scheduling and resource management in a cloud environment using optimized hybrid technology
    Arasan, K. Kalai
    Anandhakumar, P.
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2023, 53 (07): : 1572 - 1593
  • [7] An Optimal Workflow Based Scheduling and Resource Allocation in Cloud
    Varalakshmi, P.
    Ramaswamy, Aravindh
    Balasubramanian, Aswath
    Vijaykumar, Palaniappan
    [J]. ADVANCES IN COMPUTING AND COMMUNICATIONS, PT I, 2011, 190 : 411 - 420
  • [8] A dynamic prediction for elastic resource allocation in hybrid cloud environment
    Chudasama V.
    Bhavsar M.
    [J]. Scalable Computing, 2020, 21 (04): : 661 - 672
  • [9] A DYNAMIC PREDICTION FOR ELASTIC RESOURCE ALLOCATION IN HYBRID CLOUD ENVIRONMENT
    Chudasama, Vipul
    Bhavsar, Madhuri
    [J]. SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2020, 21 (04): : 661 - 672
  • [10] An Optimized Framework for Energy-Resource Allocation in a Cloud Environment based on the Whale Optimization Algorithm
    Goyal, Shanky
    Bhushan, Shashi
    Kumar, Yogesh
    Rana, Abu ul Hassan S.
    Bhutta, Muhammad Raheel
    Ijaz, Muhammad Fazal
    Son, Youngdoo
    [J]. SENSORS, 2021, 21 (05) : 1 - 24