A Hybrid Multiobjective Discrete Particle Swarm Optimization Algorithm for a SLA-Aware Service Composition Problem

For SLA-aware service composition problem (SSC), an optimization model for this algorithm is built, and a hybrid multiobjective discrete particle swarm optimization algorithm (HMDPSO) is also proposed in this paper. According to the characteristic of this problem, a particle updating strategy is designed by introducing crossover operator. In order to restrain particle swarm’s premature convergence and increase its global search capacity, the swarm diversity indicator is introduced and a particle mutation strategy is proposed to increase the swarm diversity. To accelerate the process of obtaining the feasible particle position, a local search strategy based on constraint domination is proposed and incorporated into the proposed algorithm. At last, some parameters in the algorithm HMDPSO are analyzed and set with relative proper values, and then the algorithm HMDPSO and the algorithm HMDPSO+ incorporated by local search strategy are compared with the recently proposed related algorithms on different scale cases. The results show that algorithm HMDPSO+ can solve the SSC problem more effectively. 1. Introduction Service-oriented architecture (SOA) is an emerging style of software architecture that reuses and combines loosely coupled services for building, maintaining, and integrating applications in order to improve productivity and cost effectiveness throughout the application life cycle [1]. In SOA, each application is often designed with a set of services and a workflow (or business process). Each service encapsulates the function of an application component. Each workflow defines how services interact with each other. When a service-oriented application operates, it is instantiated as a workflow instance that deploys each service in the application as one or more service instances. Each service instance follows a particular deployment plan; different service instances operate at different quality of service (QoS) levels. When an application is intended to serve different categories of users, it is instantiated with multiple workflow instances, each of which is responsible for offering a specific QoS level to a particular user category. In SOA, a service-level agreement (SLA) is defined upon a workflow instance as its end-to-end QoS requirements such as throughput, latency, and cost (e.g., resource utilization fees). In order to satisfy the given SLAs, application, developers are required to optimize a composition of service instances, service composition, for each user category by considering which service instances to use for each service and how many