With the ever increasing number of functionally similar web services being available on the Internet, the market competition is becoming intense. Web service providers (WSPs) realize that good Quality of Service (QoS) is a key of business success and low network latency is a critical measurement of good QoS. Because network latency is related to location, a straightforward way to reduce network latency is to allocate services to proper locations. However, Web Service Location Allocation Problem (WSLAP) is a challenging task since there are multiple objectives potentially conflicting with each other and the solution search space has a combinatorial nature. In this paper, we consider minimizing the network latency and total cost simultaneously and model the WSLAP as a multi-objective optimization problem. We develop a new PSO-based algorithm to provide a set of trade-off solutions. The results show that the new algorithm can provide a more diverse range of solutions than the compared three well known multi-objective optimization algorithms. Moreover, the new algorithm performs better especially on large problems.
Web services are independent programmable application components which scatter over the Internet. Due to the improvement on local computing power and development on high-speed Internet, network latency has a significant impact on determining the service response time. Thus, physical locations of web services and users should be taken into account for web service composition. In this paper, we propose a new solution based on the binary PSO-based approach to allocate the service locations. Although several heuristic approaches have been proposed for web service location-allocation, to our best knowledge, PSO-based approach is the first attempt to solve the problem. A simulated experiment is done using WS-DREAM data set with five different complexities. To compare with two GA-based approaches, the proposed BPSO approach has advantages in most situations.
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