Abstract
As there are more and more available Web services with the same or similar functionalities but different Quality of Service (QoS), the challenge of QoS-aware service composition is to efficiently select appropriate component services to achieve maximum utility and meet the global QoS constraints with low time cost. In this paper, we propose a dynamic service selection approach based on adaptive global QoS constraints decomposition. Fuzzy logic technology and Cultural Genetic Algorithm are used to adaptively decompose global QoS constraints into near-optimal local constraints. According to the near-optimal local constraints, the optimal service is selected for each service class during the running time efficiently. Experimental results show that the proposed approach not only achieves the near-optimal solution, but also significantly reduces the computation time, and has good adaptability and scalability.
Highlights
Service-oriented architecture (SOA) is a modern paradigm to develop software systems that are often described as composite Web services [1]
To overcome the problems above, this paper proposes a dynamic service selection approach based on adaptive Quality of Service (QoS) constraints decomposition (AQCD)
To overcome the above problem, this paper proposes a novel dynamic service selection approach based on adaptive global QoS constraints decomposition, in which the number of quality level is automatically adjusted
Summary
Service-oriented architecture (SOA) is a modern paradigm to develop software systems that are often described as composite Web services [1]. It is a challenge to develop an efficient QoS-aware dynamic service selection approach that can maximize the utility and satisfy the global QoS constraints and user’s preferences as well. Heuristic-based approaches search for near-optimal solutions with a polynomial time complexity [10,11] As these heuristic-based methods usually require a large number of global data and high cost of communication, they are not appropriate in distributed environments [12]. To overcome the problems above, this paper proposes a dynamic service selection approach based on adaptive QoS constraints decomposition (AQCD). Experimental results show that AQCD can efficiently solve the QoS-aware service composition problem with near-optimal solutions and low time cost.
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