Towards Green Service Composition Approach in the Cloud

被引:29
|
作者
Wang, Shangguang [1 ]
Zhou, Ao [1 ]
Bao, Ruo [1 ]
Chou, Wu [2 ]
Yau, Stephen S. [3 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
[2] Huawei Technol, Shenzhen 518129, Guangdong, Peoples R China
[3] Arizona State Univ ASU, Sch Comp Sci & Engn, Tempe, AZ 85287 USA
基金
美国国家科学基金会; 北京市自然科学基金;
关键词
Quality of service; Cloud computing; Switches; Energy consumption; Servers; Data centers; Virtual machining; Service composition; cloud computing; energy consumption; network resource consumption; WEB SERVICES; ENERGY; SELECTION; AWARE; QOS;
D O I
10.1109/TSC.2018.2868356
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the increasing popularity of cloud computing, many notable quality of service (QoS)-aware service composition approaches have been incorporated in service-oriented cloud computing systems. However, these approaches are implemented without considering the energy and network resource consumption of the composite services. The increases in energy and network resource consumption resulting from these compositions can incur a high cost in data centers. In this paper, the trade-off among QoS performance, energy consumption, and network resource consumption in a service composition process is first analyzed. Then, a green service composition approach is proposed. It gives priority to those composite services that are hosted on the same virtual machine, physical server, or edge switch with end-to-end QoS guarantee. It fulfills the green service composition optimization by minimizing the energy and network resource consumption on physical servers and switches in cloud data centers. Experimental results indicate that, with comparisons to other approaches, our approach saves 20-50 percent of energy consumption and 10-50 percent of network resource consumption.
引用
收藏
页码:1238 / 1250
页数:13
相关论文
共 50 条
  • [41] A novel approach for cloud service composition ensuring global QoS constraints optimization
    Khanam, Rashda
    Kumar, Rakesh Ranjan
    Kumari, Binita
    2018 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2018, : 1695 - 1701
  • [42] A New Integrated Approach for Cloud Service Composition and Sharing Using a Hybrid Algorithm
    Jayaudhaya J.
    Jayaraj R.
    Ramash Kumar K.
    Mathematical Problems in Engineering, 2024, 2024
  • [43] Global and local optimisation-based hybrid approach for cloud service composition
    Shetty, Jyothi
    D'Mello, Demian Antony
    INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING, 2018, 17 (01) : 1 - 14
  • [44] Service Composition Pattern Generation for Cloud Migration: a Graph Similarity Analysis Approach
    Wan, Zhitao
    Meng, Fan Jing
    Xu, Jing Min
    Wang, Ping
    2014 IEEE 21ST INTERNATIONAL CONFERENCE ON WEB SERVICES (ICWS 2014), 2014, : 321 - 328
  • [45] Towards Enterprise Software as a Service in the Cloud
    Schaffner, Jan
    Jacobs, Dean
    Eckart, Benjamin
    Brunnert, Jan
    Zeier, Alexander
    2010 IEEE 26TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING WORKSHOPS (ICDE 2010), 2010, : 52 - 59
  • [46] Towards Successful Cloud Ordering Service
    Chen, Yan-Kwang
    Chen, Yi-Ju
    Chiu, Fei-Rung
    Wang, Cheng-Yi
    BUSINESS SYSTEMS RESEARCH JOURNAL, 2015, 6 (01): : 1 - 21
  • [47] Towards automatic service composition
    Haarlaender, Nico
    Ahrens, Maximilian
    Boehm, Christoph
    MANAGING INFORMATION IN THE DIGITAL ECONOMY: ISSUES & SOLUTIONS, 2006, : 724 - +
  • [48] Cloud Architecture for Dynamic Service Composition
    Zhou, Jiehan
    Athukorala, Kumaripaba
    Gilman, Ekaterina
    Riekki, Jukka
    Ylianttila, Mika
    INTERNATIONAL JOURNAL OF GRID AND HIGH PERFORMANCE COMPUTING, 2012, 4 (02) : 17 - 31
  • [49] SDF-GA: a service domain feature-oriented approach for manufacturing cloud service composition
    Tianyang Li
    Ting He
    Zhongjie Wang
    Yufeng Zhang
    Journal of Intelligent Manufacturing, 2020, 31 : 681 - 702
  • [50] Multimedia analysis and composition cloud service
    Lin, Qian
    O'Brien-Strain, Eamonn
    Tretter, Daniel
    Liu, Jerry
    HP Laboratories Technical Report, 2011, (71):