NITCO: an intelligent agent technique for optimising of resource utilisation in cloud

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.