Energy-Efficient Service Allocation Techniques in Cloud: A Survey. Issue 4 (3rd July 2020)

• Record Type: Journal Article
• Authors: Mishra, Sambit Kumar; Sahoo, Sampa; Sahoo, Bibhudatta; Jena, Sanjay Kumar
• Is Part Of: IETE technical review. Volume 37:Issue 4(2020)
• Page Start: 339
• Page End: 352
• Publication Date: 2020-07-03
• Subjects: Cloud computing -- energy-aware -- QoS -- service allocation -- virtualization -- VM; Telecommunication -- Periodicals; Electronics -- Periodicals; Electronics; Telecommunication; Periodicals; 621.38
• DOI: 10.1080/02564602.2019.1620648
• Languages: English
• ISSNs: 0256-4602

Abstract

Abstract : The demand for cloud computing infrastructure is increasing day by day to meet the requirement of small and medium enterprises. The data center-centric cloud technology has a high share of energy consumption from the IT-industry. The amount of energy consumption in a data center depends on the allocation of user service requests to virtual machines running on the different host. Minimization of energy consumption in the data center is a significant issue and addressed by optimal allocation of cloud resources. In this paper, we have discussed how service allocation strategies have been used to optimize the energy consumption in a cloud system. A generalized system architecture is presented based on which we define the service allocation problem and energy model. Further, we present the taxonomy of various energy-efficient resource allocation techniques found in the literature. In the end, various research challenges related to the energy-efficient service allocation in cloud are discussed.