Server Consolidation Algorithms for Virtualized Cloud Environment with Variable Workloads: A Performance Evaluation
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Abstract
Server Consolidation is an efficient approach towards the utilization of physical machines, in order to reduce the total number of servers that an organization requires. To prevent the server sprawl, this practice was developed. Server Consolidation allow large-scale data centers to improve their resource utilization and energy efficiency using virtualization technologies. To prevent server sprawl, server consolidation aims at reducing the number of server machines used in the data centers by consolidating load and enhancing resource utilization of physical systems. Virtualization enables the migration of virtual machines (VMs) between the physical machines using the technique of live migration mainly for improving the efficiency. Virtual machine migration is promising approach to realize the objectives of efficient, adaptive and dynamic resource management in virtualized cloud environment. In this paper, a comprehensive study of the server consolidation algorithms and their usage towards dynamic resource management in the virtualized cloud environment is presented. We try to simulate and investigate the impacts of different server consolidation algorithms on the performance of the live machine migration in both source and target machine in terms of response time. Here in this paper, a performance evaluation of the chosen heuristics and fundamental insights obtained when variable load is generated over the physical machines, aimed at reducing server sprawl, optimizing power consumption and load balancing across the physical machines in virtualized cloud environment is presented.
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Keywords: Cloud computing; live migration; Load balancing; Server Sprawl; Virtual Machine Monitor (VMM), Hotspot mitigation.
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