A Gossip-Based Dynamic Virtual Machine Consolidation Strategy for Large-Scale Cloud Data Centers

Abstract

Dynamic virtual machine consolidation strategies refer to a number of resource management algorithms aiming at finding the right balance between energy consumption and SLA violations by using live migration techniques in virtualized cloud data centers. Most strategies found in the literature typically focus on centralized approaches, with a single management node responsible for VM placement. These approaches suffer from poor scalability, as the management node may become a performance bottleneck if the number of physical and virtual machines grows. In this paper we propose a fully decentralized dynamic virtual machine consolidation strategy on top of an unstructured P2P network of physical host nodes and investigate the performance of the strategy in terms of energy consumption, average CPU utilization, performance degradation due to overloading, performance degradation due to migration and total number of sleep nodes inside data center. The experimental results show that the proposed P2P strategy can achieve a global efficiency in terms of energy and performance very close to a centralized approach while assuring scalability due to increasing the number of hosts in data center.