Reliable and Energy Efficient Resource Provisioning and Allocation in Cloud Computing

被引:9
|
作者
Sharma, Yogesh [1 ]
Javadi, Bahman [1 ]
Si, Weisheng [1 ]
Sun, Daniel [2 ]
机构
[1] Western Sydney Univ, Penrith, NSW, Australia
[2] CSIRO, DATA61, Canberra, ACT, Australia
关键词
Cloud Computing; Failures; Reliability; Energy Consumption; Virtual Machines; Resource Provisioning; Bag of Tasks; Checkpointing; LARGE-SCALE; RELIABILITY; PERFORMANCE; TASKS; MODEL;
D O I
10.1145/3147213.3147218
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Reliability and Energy-efficiency is one of the biggest trade-off challenges confronting cloud service providers. This paper provides a mathematical model of both reliability and energy consumption in cloud computing systems and analyses their interplay. This paper also proposes a formal method to calculate the finishing time of tasks running in a failure prone cloud computing environment using checkpointing and without checkpointing. To achieve the objective of maximizing the reliability and minimizing the energy-consumption of cloud computing systems, three resource provisioning and virtual machine (VM) allocation policies using the aforementioned mathematical models are proposed. These three policies are named Reliability Aware Best Fit Decreasing (RABFD), Energy Aware Best Fit Decreasing (EABFD), Reliability-Energy Aware Best Fit Decreasing (REABFD). A simulation based evaluation of the proposed policies has been done by using real failure traces and workload models. The results of our experiments demonstrated that by considering both reliability and energy factors during resource provisioning and VM allocation, the reliability and energy consumption of the system can be improved by 23% and 61%, respectively.
引用
收藏
页码:57 / 66
页数:10
相关论文
共 50 条
  • [1] Energy Efficient Resource Allocation in Cloud Computing Environments
    Vakilinia, Shahin
    Heidarpour, Behdad
    Cherieti, Mohamed
    IEEE ACCESS, 2016, 4 : 8544 - 8557
  • [2] Energy Efficient Resource Allocation for Heterogeneous Workload in Cloud Computing
    Malik, Surbhi
    Saini, Poonam
    Rani, Sudesh
    PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON FRONTIERS IN INTELLIGENT COMPUTING: THEORY AND APPLICATIONS, FICTA 2016, VOL 1, 2017, 515 : 89 - 97
  • [3] Energy-Efficient Resource Allocation and Provisioning Framework for Cloud Data Centers
    Dabbagh, Mehiar
    Hamdaoui, Bechir
    Guizani, Mohsen
    Rayes, Ammar
    IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2015, 12 (03): : 377 - 391
  • [4] An Efficient Framework for Resource Allocation in Cloud Computing
    Kumar, Aman
    Pilli, Emmanuel S.
    Joshi, R. C.
    2013 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATIONS AND NETWORKING TECHNOLOGIES (ICCCNT), 2013,
  • [5] Analysis of QoS aware energy-efficient resource provisioning techniques in cloud computing
    Malla, Parvaz Ahmad
    Sheikh, Sophiya
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2023, 36 (01)
  • [6] Efficient dynamic resource provisioning based on credibility in cloud computing
    Vinothiyalakshmi, P.
    Anitha, R.
    WIRELESS NETWORKS, 2021, 27 (03) : 2217 - 2229
  • [7] Efficient dynamic resource provisioning based on credibility in cloud computing
    P. Vinothiyalakshmi
    R. Anitha
    Wireless Networks, 2021, 27 : 2217 - 2229
  • [8] Energy-Efficient Resource Allocation for Virtual Service in Cloud Computing Environment
    Nguyen Minh Nhut Pham
    Van Son Le
    Ha Huy Cuong Nguyen
    INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, INDIA 2017, 2018, 672 : 126 - 136
  • [9] Energy efficient temporal load aware resource allocation in cloud computing datacenters
    Vakilinia, Shahin
    JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, 2018, 7
  • [10] A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems
    Hameed, Abdul
    Khoshkbarforoushha, Alireza
    Ranjan, Rajiv
    Jayaraman, Prem Prakash
    Kolodziej, Joanna
    Balaji, Pavan
    Zeadally, Sherali
    Malluhi, Qutaibah Marwan
    Tziritas, Nikos
    Vishnu, Abhinav
    Khan, Samee U.
    Zomaya, Albert
    COMPUTING, 2016, 98 (07) : 751 - 774