Energy aware clustered load balancing in cloud computing environment. (2018)

• Record Type: Journal Article
• Authors: Babu, K.R. Remesh; Samuel, Philip
• Is Part Of: International journal of networking and virtual organisations. Volume 19:Number 2/3/4(2018)
• Page Start: 305
• Page End: 320
• Publication Date: 2018
• Subjects: cloud computing -- VM scheduling -- best-fit algorithm -- energy consumption -- load balancing -- resource allocation; Computer networks -- Periodicals; Information networks -- Periodicals; Virtual corporations -- Periodicals; Electronic commerce -- Periodicals; Management information systems -- Periodicals; Management -- Data processing -- Periodicals; 004.65
• Languages: English
• ISSNs: 1470-9503

Abstract

Cloud is a collection of datacentres with heterogeneous resources, which gives services to the users based on pay-as-you-use model. Even though it has several advantages such as availability, scalability, and reliability, some performance parameters like energy consumption, load balancing, response time, resource allocation time, etc., are not properly fine tuned. This paper proposes an energy aware clustered load balancing system in which, heterogeneous resources are clustered into different groups by using a partitioning-based clustering algorithm. The clustering reduces number of resources needs to be searched and hence minimizes the time required for resource discovery. An energy aware best-fit virtual machine (VM) allocation is used for reducing the power consumption. The process allocations to VMs are done based on best-fit allocation strategy for optimal space utilisation. The results show that proposed method reduces time for resource discovery, resource allocation and response time with power consumption.