A Penalty-based Genetic Algorithm for the Composite SaaS Placement Problem in the Cloud

被引:0
|
作者
Yusoh, Zeratul Izzah Mohd [1 ]
Tang, Maolin [1 ]
机构
[1] Queensland Univ Technol, Fac Sci & Technol, Brisbane, Qld 4001, Australia
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Cloud computing is a latest new computing paradigm where applications, data and IT services are provided over the Internet. Cloud computing has become a main medium for Software as a Service (SaaS) providers to host their SaaS as it can provide the scalability a SaaS requires. The challenges in the composite SaaS placement process rely on several factors including the large size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. However, existing applications' placement methods in data centres are not concerned with the placement of the component's data. In addition, a Cloud network is much larger than data center networks that have been discussed in existing studies. This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. We believe this is the first attempt to the SaaS placement with its data in Cloud provider's servers. Experimental results demonstrate the feasibility and the scalability of the GA.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] A Penalty-based Grouping Genetic Algorithm for Multiple Composite SaaS Components Clustering in Cloud
    Yusoh, Zeratul Izzah Mohd
    Tang, Maolin
    [J]. PROCEEDINGS 2012 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2012, : 1396 - 1401
  • [2] A Penalty-Based Genetic Algorithm for the Migration Cost-Aware Virtual Machine Placement Problem in Cloud Data Centers
    Sarker, Tusher Kumer
    Tang, Maolin
    [J]. NEURAL INFORMATION PROCESSING, PT II, 2015, 9490 : 161 - 169
  • [3] A Cooperative Coevolutionary Algorithm for the Composite SaaS Placement Problem in the Cloud
    Yusoh, Zeratul Izzah Mohd
    Tang, Maolin
    [J]. NEURAL INFORMATION PROCESSING: THEORY AND ALGORITHMS, PT I, 2010, 6443 : 618 - 625
  • [4] An Ant Colony Optimization for the Composite SaaS Placement Problem in the Cloud
    Ni, Zhiwei
    Pan, Xuefeng
    Wu, Zhangjun
    [J]. MECHANICAL AND ELECTRONICS ENGINEERING III, PTS 1-5, 2012, 130-134 : 3062 - 3067
  • [5] An adaptive Simulated Annealing Genetic Algorithm for the data Placement Problem in SAAS
    Yuan Bowen
    Wu Shaochun
    [J]. 2012 INTERNATIONAL CONFERENCE ON INDUSTRIAL CONTROL AND ELECTRONICS ENGINEERING (ICICEE), 2012, : 1037 - 1043
  • [6] On a smoothed penalty-based algorithm for global optimization
    Rocha, Ana Maria A. C.
    Costa, M. Fernanda P.
    Fernandes, Edite M. G. P.
    [J]. JOURNAL OF GLOBAL OPTIMIZATION, 2017, 69 (03) : 561 - 585
  • [7] Composite SaaS Scaling in Cloud Computing using a Hybrid Genetic Algorithm
    Yusoh, Zeratul Izzah Mohd
    Tang, Maolin
    [J]. 2014 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2014, : 1609 - 1616
  • [8] A penalty-based evolutionary algorithm for constrained optimization
    Wang, Yuping
    Ma, Wei
    [J]. ADVANCES IN NATURAL COMPUTATION, PT 1, 2006, 4221 : 740 - 748
  • [9] On a smoothed penalty-based algorithm for global optimization
    Ana Maria A. C. Rocha
    M. Fernanda P. Costa
    Edite M. G. P. Fernandes
    [J]. Journal of Global Optimization, 2017, 69 : 561 - 585
  • [10] A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows
    Nagata, Yuichi
    Braysy, Olli
    Dullaert, Wout
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2010, 37 (04) : 724 - 737