Paper Info
Title
Workload-Aware Vm Consolidation In Cloud Based On Max-Min Ant System
Abstract
With the increasing consumption of energy in cloud data center, the cloud providers pay more attention to the green cloud computing for saving energy. The most effective way in green cloud computing is using virtual machine (VM) consolidation to pack VMs into a smaller amount of physical machines (PMs), which can save energy by switching off the idle PMs. However, in traditional static workload approach, VMs are over-provisioned with a static capacity to guarantee peak performance, which increases the unnecessary energy consumption. In this paper, we propose an innovative approach WAVMC to achieve efficient VM consolidation by using multi-dimensional time-varying workloads based on the Max-Min Ant System (MMAS). In the MMAS, we employ the complementary of both workload patterns and multi-dimensional resources usage as heuristic factors. Extensive simulations on production workloads demonstrate that the proposed model outperforms state-of-the-art baselines in active server counts and resources wastage.
Year
DOI
Venue
2017
10.1007/978-3-319-68505-2_16
CLOUD COMPUTING AND SECURITY, PT I
Keywords
Field
DocType
Cloud computing, VM consolidation, Workload patterns, Multi-dimensional resources, Max-Min Ant System
Heuristic,Virtual machine,Workload,Idle,Computer science,Cloud data center,Consolidation (soil),Energy consumption,Cloud computing,Distributed computing
Conference
Volume
ISSN
Citations 
10602
0302-9743
0
PageRank 
References 
Authors
0.34
10
5
Name
Order
Citations
PageRank
Hongjie Zhang101.35
Guansheng Shu201.69
Shasha Liao31279.02
Xi Fu400.68
Jing Li5226.73