Cloud Service Selection and Workflow Scheduling Using P System

Abstract

Cloud Computing is a decade old technology that has changed the landscape of the internet based business model. This technology manifested itself unheralded, a decade ago and has been growing since. It now stands with several inherent complex problems, as a result of its expansion. Out of several issues being researched, service selection in cloud is one of the prime issues which is getting primary attention. Service selection is a process of selecting (ranking) services from a pool of available cloud services which is often based on multiple Quality of Service (QoS) attributes. Our work is divided into two major components. The first part of our work is solving the problem of cloud service selection. This study proposes inherently parallel, robust models for service selection in cloud based on a natural computing model called membrane computing. Membrane Computing, which is realised using P Systems, is an inherently parallel model that is based on the concept of animal cell interaction. There are several variants of P Systems and here Enzymatic Numerical P System (ENPS) is used, based on its suitability to the problem being solved. Multiple approaches have been proposed and the results are analysed. Additionally, two new software tools required for ENPS execution are proposed. The second part involves designing and implementing the algorithm for workflow scheduling in cloud. Workflow is a group of tasks that are collectively aimed at doing a single work. Cloud workflows consist of tasks to be mapped to Virtual Machines (VMs) that are part of the cloud. The process of assigning limited number of VMs to the tasks in a particular manner to optimize certain quality factor, is referred to as workflow scheduling in cloud. In this study the effort is to minimise makespan, which is the net time taken by the workflow to get executed. The ENPS model is used to obtain the sequence of the schedule, based on which the makespan is calculated and compared with other standard methods.