Analysis of Resource Management and placement policies using a new nature inspired meta heuristic SSCWA avoiding premature convergence in Cloud

Abstract

Cloud computing is the most evolving and promising part of today's world easing the computing needs of organizations cost effectively and has covered entire internet based activities. When the client gives request to the cloud, it is handled at the PaaS layer by the Resource Management Module where in tasks are managed and scheduled. At the IaaS layer, the Resource Placement Module allocates the resources to the tasks and manages them in order to provide desired level of services collectively. This resource Management and Placement should be handled effectively, so as to check the overall system performance, keeping in view of the QoS parameters. A framework for a collective action of IaaS and PaaS layer is proposed which is integrated with a new novel nature inspired meta-heuristic technique of social spiders that leads to the profit for both the client and the cloud service provider. In this paper, Resource Management Module of PaaS layer will be focused along with the Resource Placement Module to monitor the overall functioning of the Cloud.