Metaheuristic Scheduling for Cloud: A Survey

被引:165
|
作者
Tsai, Chun-Wei [1 ]
Rodrigues, Joel J. P. C. [2 ]
机构
[1] Chia Nan Univ Pharm & Sci, Dept Appl Informat & Multimedia, Tainan 717, Taiwan
[2] Univ Beira Interior, Inst Telecomun, P-6201001 Covilha, Portugal
来源
IEEE SYSTEMS JOURNAL | 2014年 / 8卷 / 01期
关键词
Cloud computing; metaheuristics; scheduling; PARTICLE SWARM OPTIMIZATION; ANT COLONY OPTIMIZATION; GENETIC-ALGORITHM; COMPUTING ENVIRONMENTS; SIMULATION; SERVICES; SEARCH; ACO;
D O I
10.1109/JSYST.2013.2256731
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing has become an increasingly important research topic given the strong evolution and migration of many network services to such computational environment. The problem that arises is related with efficiency management and utilization of the large amounts of computing resources. This paper begins with a brief retrospect of traditional scheduling, followed by a detailed review of metaheuristic algorithms for solving the scheduling problems by placing them in a unified framework. Armed with these two technologies, this paper surveys the most recent literature about metaheuristic scheduling solutions for cloud. In addition to applications using metaheuristics, some important issues and open questions are presented for the reference of future researches on scheduling for cloud.
引用
收藏
页码:279 / 291
页数:13
相关论文
共 50 条
  • [41] Scheduling of Task in Cloud Environment Using Optimization Algorithms : Survey
    Natesan, Gobalakrishnan
    Pradeep, K.
    Ali, L. Javid
    PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICCS), 2019, : 417 - 424
  • [42] An Analysis of the Load Scheduling Algorithms in the Cloud Computing Environment: A Survey
    Chaudhary, Divya
    Kumar, Bijendra
    2014 9TH INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS (ICIIS), 2014, : 1037 - 1042
  • [43] A Survey on Scheduling Strategies for Workflows in Cloud Environment and Emerging Trends
    Adhikari, Mainak
    Amgoth, Tarachand
    Srirama, Satish Narayana
    ACM COMPUTING SURVEYS, 2019, 52 (04)
  • [44] A hybrid metaheuristic for the resource-constrained project scheduling problem
    Tseng, Lin-Yu
    Chen, Shih-Chieh
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2006, 175 (02) : 707 - 721
  • [45] A Hybrid Metaheuristic for Multi-Objective Scientific Workflow Scheduling in a Cloud Environment
    Anwar, Nazia
    Deng, Huifang
    APPLIED SCIENCES-BASEL, 2018, 8 (04):
  • [46] Multi objective task scheduling based on hybrid metaheuristic algorithm for cloud environment
    Neelakantan, P.
    Yadav, N. Sudhakar
    MULTIAGENT AND GRID SYSTEMS, 2022, 18 (02) : 149 - 169
  • [47] Clustering-assisted gradient-based optimizer for scheduling parallel cloud workflows with budget constraints
    Li, Huifang
    Chen, Boyuan
    Huang, Jingwei
    Song, Zhuoyue
    Xia, Yuanqing
    JOURNAL OF SUPERCOMPUTING, 2024, 80 (12) : 17097 - 17134
  • [48] A Survey on Metaheuristic Approaches and Its Evaluation for Load Balancing in Cloud Computing
    Garg, Deepak
    Kumar, Pardeep
    ADVANCED INFORMATICS FOR COMPUTING RESEARCH, ICAICR 2018, PT I, 2019, 955 : 585 - 599
  • [49] A Survey on Task Scheduling in Edge-Cloud
    Subham Kumar Sahoo
    Sambit Kumar Mishra
    SN Computer Science, 6 (3)
  • [50] A Survey of Various Scheduling Algorithms in Cloud Environment
    Santhosh, B.
    Manjaiah, D. H.
    Suresh, L. Padma
    IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGICAL TRENDS IN COMPUTING, COMMUNICATIONS AND ELECTRICAL ENGINEERING (ICETT), 2016,