Service Level Agreement Aware SaaS Placement in Cloud

Abstract

Cloud computing is an encouraging and favourable paradigm for both providers and consumers in diverse scopes of endeavors. Software as a Service (SaaS) is a method of conveying services or applications through the Internet – as a service, and it is known to be one of the very crucial computing services in cloud computing. Cloud computing has become a major medium for the SaaS providers to provide their applications because required scalability can be achieved through this. The challenges of SaaS placement process depends on various factors comprising cloud network size, resource requirements, and communication among its components. This thesis analyzes the SaaS Placement Problem (SPP) and proposes a mathematical model for SaaS placement in Cloud. This thesis gives an evolutionary approach, known as Particle Swarm Optimization (PSO) that has been applied to find the optimal placement of SaaS component and aiming to minimize the total cost incurred to the SaaS provider, and then evaluated against the traditional Greedy approach in experiments. The obtained results show our proposed algorithm SPPSO generates better solutions than Greedy approach SPGA.