Energy Efficient Load Balancing in Cloud Data Center Using Clustering Technique

Authored by N Thilagavathi, D Divya Dharani, R Sasilekha, Vasundhara Suruliandi, V Rhymend Uthariaraj

Date Published: 2019

DOI: 10.4018/ijiit.2019010104

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Cloud computing has seen tremendous growth in recent days. As a result of this, there has been a great increase in the growth of data centers all over the world. These data centers consume a lot of energy, resulting in high operating costs. The imbalance in load distribution among the servers in the data center results in increased energy consumption. Server consolidation can be handled by migrating all virtual machines in those underutilized servers. Migration causes performance degradation of the job, based on the migration time and number of migrations. Considering these aspects, the proposed clustering agent-based model improves energy saving by efficient allocation of the VMs to the hosting servers, which reduces the response time for initial allocation. Middle VM migration (MVM) strategy for server consolidation minimizes the number of VM migrations. Further, randomization of extra resource requirement done to cater to real-time scenarios needs more resource requirements than the initial requirement. Simulation results show that the proposed approach reduces the number of migrations and response time for user request and improves energy saving in the cloud environment.

Tags

Agent-based model Migration Clustering Optimization Energy efficiency Energy consumption Framework Resource-allocation Cloud computing Load balancing Server consolidation