Authors: Harvinder Singh; Anshu Bhasin; Parag Ravikant Kaveri
Addresses: IKGPTU, Kapurthala, 144601 Punjab, India ' IKGPTU, Kapurthala, 144601 Punjab, India ' Symbiosis Institute of Computer Studies and Research, Pune, India
Abstract: Efficient task scheduling is significant to meet the quality of service (QoS) requirements in cloud computing. Cloud is a large pool of virtual access resources to perform thousands of computational and storage operations. Task scheduling is an NP-hard problem, unsuitable matching leads to performance degradation and violation of service level agreement (SLA). The growing complexity of cloud services needs an extension of existing scheduling algorithms. In this paper, the scheduling problem has been explored based on growing application trends. Cloud dynamic resource provisioning can satisfy users' requirements if execution of tasks performed: identifying of task requirements; workflow of application scheduling using a sufficient amount of resources. In this research work, we present an intelligent agent technique for optimising resource utilisation named NITCO. NITCO considers the above mentioned challenge, identification of task requirements and configuration of resource. The performance of proposed NITCO has been evaluated on simulated cloud environment and comparison of results show that NITCO performed better in terms of execution cost, execution time, VM utilisation and SLA violation while it delivers quality of service.
Keywords: cloud computing; scheduling; utilisation; energy-consumption; service level agreement; SLA.
International Journal of Reasoning-based Intelligent Systems, 2021 Vol.13 No.2, pp.69 - 75
Received: 16 May 2019
Accepted: 08 Dec 2019
Published online: 30 Mar 2021 *