A Reliability Improvement Method for SOA-Based Applications

As SOA gains more traction through various implementations, building reliable service compositions remains one of the principal research concerns. Widely researched reliability assurance methods, often rely on applying redundancy or complex optimization strategies that can make them less applicable when it comes to designing service compositions on a larger scale. To address this issue, we propose a design time reliability improvement method that enables selective service composition improvements by focusing on the most reliability-critical workflow components, named weak points. With the aim of detecting most significant weak points, we introduce a method based on a suite of recommendation algorithms that leverage a belief network reliability model. The method is made scalable by using heuristic algorithms that achieve better computational performance at the cost of recommendation accuracy. Although less accurate heuristic algorithms on average require more improvement steps, they can achieve better overall performance in cases when the additional step-wise overhead of applying improvements is low. We confirm the soundness of the proposed solution by performing experiments on data sets of randomly generated service compositions.