Research Area: Cloud Computing
The emergence of cloud computing based on virtualization technologies brings huge opportunities to host virtual resource at low cost without the need of owning any infrastructure. Virtualization technologies enable users to acquire, configure, and be charged on pay-per-use basis. However, cloud data centers mostly comprise heterogeneous commodity servers hosting multiple virtual machines (VMs) with potential various specifications and fluctuating resource usages, which may cause imbalanced resource utilization within servers that may lead to performance degradation and service level agreements violations. So as to achieve efficient scheduling, these challenges should be addressed and solved by using load balancing strategies, which have been proved to be nondeterministic polynomial time (NP)-hard problem. From multiple perspectives, this work identifies the challenges and analyzes existing algorithms for allocating VMs to hosts in infrastructure clouds, especially focuses on load balancing. A detailed classification targeting load balancing algorithms for VM placement in cloud data centers is investigated, and the surveyed algorithms are classified according to the classification. The goal of this paper is to provide a comprehensive and comparative understanding of existing literature and aid researchers by providing an insight for potential future enhancements.
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Author(s) Name: Minxian Xu, Wenhong Tian, Rajkumar Buyya
Journal name: Concurrency and Computation: Practice and Experience
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Publisher name: Wiley
DOI: 10.1002/cpe.4123
Volume Information: Volume29, Issue12 25 June 2017
