Task scheduling in cloud environment: A multi-objective ABC framework. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Jena, R. K.
• Is Part Of: Journal of information & optimization sciences. Volume 38:Issue 1(2017)
• Page Start: 1
• Page End: 19
• Publication Date: 2017-01-02
• Subjects: Ant Bee Colony -- Cloud Computing -- Task Scheduling; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2016.1250460
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: Cloud computing is an emerging distributed, low cost computing paradigm with a large collection of heterogeneous autonomous systems. It provides, on demand, flexible and scalable services to customers through a pay per use basis. The overall performance of cloud infrastructure depends on task assignment and scheduling. Efficient task scheduling reduces power consumption of the cloud infrastructure and increase the profit of service providers by reducing processing time of the user job. This research focuses on efficient task scheduling using multi-objective Artificial Bee Colony Algorithm (TA-ABC). The proposed algorithm optimizes the energy, cost, resource utilization and processing time of the cloud environment. The results obtained by TA-ABC is also simulated by an open source cloud platform (CloudSim). Further, the proposed algorithm (TA-ABC) provide an optimal balance results for multiple objectives and the results are comparable to the state-of-the-art existing scheduling algorithms.