Makespan Efficient Task Scheduling in Cloud Computing

被引:2
|
作者
Raju, Y. Home Prasanna [1 ]
Devarakonda, Nagaraju [2 ]
机构
[1] Acharya Nagarjuna Univ, Dept CSE, Guntur 522510, Andhra Pradesh, India
[2] Lakireddy Bali Reddy Coll Engn, Dept IT, Vijayawada 521230, Andhra Pradesh, India
关键词
Cloud service provider; Modified ant colony optimization; Modified fuzzy clustering means; Task scheduling; Virtual machine;
D O I
10.1007/978-981-13-1951-8_26
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cloud computing is an emerging technology in modern era of online processing of customizable resources gathered commonly for several remote server accesses through on-demand access. Cloud Service Provider (CSP) renders cloud computing infrastructure in pay per use scheme in various formats. Thus, CSP provides a major role in optimization of Task Scheduling (TS) in trade off with cost afford by the end user. In proposed scheme, to create efficient utilization of resources and balanced cost of rendering service to end user, Modified Fuzzy Clustering Means algorithm (MFCM) along with Modified Ant Colony Optimization (MACO) technique is used thereby minimizing the cost of using a cloud computing structure and with reduced makespan along with load balancing capability. Proposed strategy provides better results than existing strategies of various modifications on ACO alone that concentrates on optimizing lineup of Virtual Machine (VM).
引用
下载
收藏
页码:283 / 298
页数:16
相关论文
共 50 条
  • [41] Energy-efficient and Deadline-satisfied Task Scheduling in Mobile Cloud Computing
    Tang, Chaogang
    Xiao, Shuo
    Wei, Xianglin
    Hao, Mingyang
    Chen, Wei
    2018 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP), 2018, : 198 - 205
  • [42] A New Algorithm for Energy Efficient Task Scheduling Towards Optimal Green Cloud Computing
    Khullar, Rahul
    Hossain, Gahangir
    2022 IEEE/ACS 19TH INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS (AICCSA), 2022,
  • [43] Efficient task scheduling for budget constrained parallel applications on heterogeneous cloud computing systems
    Chen, Weihong
    Xie, Guoqi
    Li, Renfa
    Bai, Yang
    Fan, Chunnian
    Li, Keqin
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2017, 74 : 1 - 11
  • [44] Efficient Task Scheduling in Cloud Computing using an Improved Particle Swarm Optimization Algorithm
    Peng, Guang
    Wolter, Katinka
    CLOSER: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND SERVICES SCIENCE, 2019, : 58 - 67
  • [45] Efficient and scalable ACO-based task scheduling for green cloud computing environment
    Ari, Ado Adamou Abba
    Damakoa, Irepran
    Titouna, Chafiq
    Labraoui, Nabila
    Gueroui, Abdelhak
    2017 IEEE INTERNATIONAL CONFERENCE ON SMART CLOUD (SMARTCLOUD), 2017, : 66 - 71
  • [46] Efficient Delay-Aware Task Scheduling for IoT Devices in Mobile Cloud Computing
    Jin, Chenghou
    Xu, Jiajie
    Han, Yusen
    Hu, Jintao
    Chen, Ying
    Huang, Jiwei
    MOBILE INFORMATION SYSTEMS, 2022, 2022
  • [47] Adaptive DRL-Based Task Scheduling for Energy-Efficient Cloud Computing
    Kang, Kaixuan
    Ding, Ding
    Xie, Huamao
    Yin, Qian
    Zeng, Jing
    IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2022, 19 (04): : 4948 - 4961
  • [48] Adaptive Scheduling of Stochastic Task Sequence for Energy-Efficient Mobile Cloud Computing
    Jiang, Qi
    Leung, Victor C. M.
    Tang, Hao
    Xi, Hong-Sheng
    IEEE SYSTEMS JOURNAL, 2019, 13 (03): : 3022 - 3025
  • [49] Energy-makespan optimization of workflow scheduling in fog-cloud computing
    Ijaz, Samia
    Munir, Ehsan Ullah
    Ahmad, Saima Gulzar
    Rafique, M. Mustafa
    Rana, Omer F.
    COMPUTING, 2021, 103 (09) : 2033 - 2059
  • [50] Performance evaluation of task scheduling algorithms in virtual cloud environment to minimize makespan
    Kaur R.
    Laxmi V.
    Balkrishan
    International Journal of Information Technology, 2022, 14 (1) : 79 - 93