Name
Abstract | ||
|---|---|---|
Cloud service providers usually utilize the resource in the data center to offer cloud computing service which needs to satisfy the demand of different customers. The load among the physical servers in the data center needs to be balanced to avoid hotspot and improve resource utility. In this paper we present a load balancing system and design an algorithm base on MOGA to get a new mapping relationship between physical machines and VMs. By a set of migrating operations of VMs the problem of load imbalance are solved. Through comprehensive simulations, the experimental results demonstrate that our proposed approaches can significantly improve the resource utilization when system load is stable variant. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CCIS.2012.6664433 | Proceedings - 2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems, IEEE CCIS 2012 |
Keywords | DocType | Volume |
resource utility improvement,virtual machine,scheduling,load balancing system,computer centres,cloud computing service,load balance,multiobjective genetic algorithm,virtual machines,mapping policy,data center,resource allocation,resource utilization improvement,physical machines,genetic algorithms,multi-objective genetic algorithm,hotspot avoidance,cloud computing,multiobjective scheduling strategy,mapping relationship,moga | Conference | 1 |
Issue | ISSN | ISBN |
null | null | 978-1-4673-1855-6 |
Citations | PageRank | References |
1 | 0.40 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Zhou | 1 | 155 | 26.38 |
| Jinfeng Xiang | 2 | 1 | 0.40 |
| Zhebo Zhou | 3 | 1 | 0.74 |
| Feng Duan | 4 | 34 | 4.43 |
| Yu Lei | 5 | 116 | 11.85 |