Performance evaluation of a solution for composite service selection problem with multiple consumers

Abstract

In recent years, building business applications from independently developed services has become one of the current trends in service computing. To satisfy clients’ requirements, service composition is performed to compose the various capabilities of available services. With the proliferation of services having similar functionalities, assessing the quality of a given composition is a paramount factor to decide which services must be selected, or to choose whether a given composition can provide the requested QoS (Quality of Service). However, due to the fluctuating conditions in the dynamic cloud computing environment, the QoS and the performances of the services become unreliable, and therefore call into the question the accuracy of the composition QoS. To tackle this issue, different methods that analyse the QoS have been developed, making it possible to help the designers to first, understand the system behaviour when providers and consumers, are interacting, thus allowing to optimize the system by identifying performance bottlenecks within a specified deployment environment.In this study, the particular problem of many consumers that are competing to acquire services with same functionalities but with different QoS, is considered. For this purpose, assuming a dynamic environment, different models based on Discrete Time Markov Chain are developed to implement several policies of the system. A theoretical modelling of the problem is proposed including analytical results obtained using the Xborne tool. For each model, the average time to reach a given QoS for a community of consumers is reported. Such a performance metric allows the designer to predict the system behaviour in a dynamic environment.