A bio-inspired hybrid algorithm for effective load balancing in cloud computing. (2016)

• Record Type: Journal Article
• Authors: Kumar, Rajeev; Prashar, Tanya
• Is Part Of: International journal of cloud computing. Volume 5:Number 3(2016)
• Page Start: 218
• Page End: 246
• Publication Date: 2016
• Subjects: cloud computing -- swarm intelligence -- load balancing -- ant colony optimisation -- ACO -- priority-based ABC -- artificial bee colony -- bio-inspired computation -- resource scheduling -- response time -- processing time -- processing cost; Cloud computing -- Periodicals; 004.678205
• Languages: English
• ISSNs: 2043-9989

Abstract

Effective scheduling and load balancing are the key challenges of cloud computing technology. A prominent task scheduler must be adaptable to the dynamic distributed environment and to the job scheduling policy based upon the workload. In this research, a novel hybrid algorithm is developed for balancing the load among cloud nodes by hybridising the existing ant colony optimisation (ACO) algorithm and priority-based artificial bee colony (ABC) algorithm where ACO is used for balancing the workload and ABC is used to optimise the resource scheduling from the prospect of cloud computing systems. The proposed technique is tested to show that proposed approach minimise the average response time, average data centre processing time and total processing cost to serve the user requests.