QoS-aware Optimization of Cloud Service Composition using Symbiotic Organisms Search Algorithm

Nowadays, service-oriented systems according to possibility of using in heterogeneous distributed environments and being independent of the specific technology, also with the existence of large-scale dynamic system with changeable requirements, are highly regarded. Cloud services are one of the implementation methods of service-oriented concepts. Increasing the tendency of users to use cloud computing, encourages service vendors to provide services with different non-functionality features. Mostly single services couldn’t satisfy users’ requirements, so it’s necessary to compose some services to achieve the demand service. With the increasing of service providers, also services in the internet service pools, selecting the optimal service from a set of functionality equivalent candidates which are differ in QoS, becomes an important NP-Hard research problem. Therefore increasing the quality of composite services is a vital challenge and since the quality of cloud composite services derived from previous approaches can still be increased, in this research, we have tried to increase the quality of cloud composite services using the Symbiotic Organism Search Algorithm. Simulations are conducted in Matlab environment and the results are compared to three famous algorithms including GA, ACO and PSO. The comparisons demonstrate the remarkable superiority of SOS in result's quality, stability and scalability, also 13% improvement.