Distributed Task Scheduling in Cloud Platform: A Survey

被引:9
|
作者
Hazra, Debojyoti [1 ]
Roy, Asmita [1 ]
Midya, Sadip [1 ]
Majumder, Koushik [1 ]
机构
[1] West Bengal Univ Technol, Dept Comp Sci & Engn, Kolkata, India
来源
关键词
Cloud computing; Task scheduling; Task scheduler; Makespan;
D O I
10.1007/978-981-10-5544-7_19
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 a booming area in distributed computing and parallel processing. Cloud provides services to its customer on pay-per-use basis. It has gained a lot of attention due to its unique features-elasticity, scalability, and on-demand services. Cloud facilitates both computational and storage service to its customers. This reduces the cost of deployment and maintenance for any organization. As a result, demand for cloud computing has increased considerably. To provide the services, cloud service provider needs to utilize all resources in an optimal way. To utilize all resources efficiently, task schedule plays a significant role. It is responsible for scheduling users' tasks in the cloud environment. The task scheduler arranges tasks in a queue for the available connected resources. This arrangement benefits the cloud service provider to achieve maximum performance in a cost efficient manner. In this paper, an extensive study of some well-known task-scheduling algorithms in cloud environment is done while identifying the advantages and weaknesses of these existing algorithms. Future research areas and further improvement on the existing methodologies are also suggested.
引用
收藏
页码:183 / 191
页数:9
相关论文
共 50 条
  • [1] Survey on Task Scheduling in Inter-Cloud Environment
    Tang, Xuhao
    Liu, Fagui
    Wang, Bin
    Li, Chao
    Jiang, Jun
    Tang, Quan
    Chen, Weiming
    He, Fengwen
    [J]. Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2023, 60 (06): : 1262 - 1275
  • [2] Task Scheduling in Heterogeneous Cloud Environment-A Survey
    Pradhan, Roshni
    Satapathy, Suresh Chandra
    [J]. INTELLIGENT COMPUTING AND COMMUNICATION, ICICC 2019, 2020, 1034 : 1 - 9
  • [3] Task scheduling techniques in cloud computing: A literature survey
    Arunarani, A. R.
    Manjula, D.
    Sugumaran, Vijayan
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 91 : 407 - 415
  • [4] Cluster Based Scheduling Method With Task Duplication In Cloud Platform
    Akilandeswari, P.
    Vennila, B.
    Srimathi, H.
    [J]. 11TH NATIONAL CONFERENCE ON MATHEMATICAL TECHNIQUES AND APPLICATIONS, 2019, 2112
  • [5] A Cooperative Method of Task Scheduling based on FPGA Cloud Platform
    Su, Dongdong
    Wang, Chengqi
    Du, Lin
    Li, Rengang
    Liu, Wei
    Zhang, Deshan
    [J]. PROCEEDINGS OF 2019 IEEE 7TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2019), 2019, : 447 - 450
  • [6] Towards a lightweight task scheduling framework for cloud and edge platform
    Dreibholz, Thomas
    Mazumdar, Somnath
    [J]. INTERNET OF THINGS, 2023, 21
  • [7] Energy Aware Task Scheduling Algorithms in Cloud Environment: A Survey
    Hazra, Debojyoti
    Roy, Asmita
    Midya, Sadip
    Majumder, Koushik
    [J]. SMART COMPUTING AND INFORMATICS, 2018, 77 : 631 - 639
  • [8] Scheduling of Task in Cloud Environment Using Optimization Algorithms : Survey
    Natesan, Gobalakrishnan
    Pradeep, K.
    Ali, L. Javid
    [J]. PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICCS), 2019, : 417 - 424
  • [9] RESEARCH ON CO-SIMULATION TASK SCHEDULING IN CLOUD SIMULATION PLATFORM
    Yang, Chen
    Li, Bo Hu
    Chai, Xudong
    [J]. 23RD EUROPEAN MODELING & SIMULATION SYMPOSIUM, EMSS 2011, 2011, : 715 - 721
  • [10] A New Task Scheduling Algorithm based on Value and Time for Cloud Platform
    Kuang, Ling
    Zhang, Lichen
    [J]. GREEN ENERGY AND SUSTAINABLE DEVELOPMENT I, 2017, 1864