Robustness Estimation and Optimisation for Semantic Web Service Composition With Stochastic Service Failures

Abstract

Service-oriented architecture (SOA) is a widely adopted software engineering paradigm that encourages modular and reusable applications. One popular application of SOA is web service composition, which aims to loosely couple web services to accommodate complex goals not achievable through any individual web service. Many approaches have been proposed to construct composite services with optimized Quality of Service (QoS), assuming that QoS of web services never changes. However, the constructed composite services may not perform well and may not be executable later due to its component services' failure. Therefore, it is important to build composite services that are robust to stochastic service failures. Two challenges of building robust composite services are to efficiently generate service composition with near-optimal quality in a large search space of available services and to accurately measure the robustness of composite services considering all possible failure scenarios. This article proposes a novel two-stage GA-based approach to robust web service composition with an adaptive evolutionary control and an efficient robustness measurement. This approach can generate robust composite service at the design phase, which can cope with stochastic service failures and maintain high quality at the time of execution. We have conducted experiments with benchmark datasets to evaluate the performance of our proposed approach. Our experiments show that our method can produce highly robust composite services, achieving outstanding performance consistently in the event of stochastic service failures, on service repositories with varying sizes.