A Meta-Heuristic-Based Approach for Qos-Aware Service Composition

Recently, with the rapid increase in the number of web services, QoS-aware Web Service Composition(QWSC) has become a popular topic in both industry and academia. Meta-heuristic algorithm, as an effective way to solve classical optimization problems, has been successfully applied to QWSC nowdays. However, such approach has intrinsic drawbacks and usually lack of good performance in large-scale scenarios. For example, some meta-heuristic algorithms are suitable for continuous search space, while the search space of QWSC is discrete. For solving those problems which were commonly faced when applying meta-heuristic algorithm on QWSC, in this research, we firstly introduce a preprocessing approach for constructing fuzzy continuous neighborhood relations of concrete services, which makes the local search strategy of meta-heuristic algorithms be as effective in discrete space as in continuous space, thus improving the optimization performance. Second, we combine Harris Hawks Optimization (HHO) algorithm and logical chaotic sequence to propose an improved meta-heuristic algorithm named CHHO for solving QWSC. The ergodic and chaotic characteristics of chaotic sequences are used to enhance the ability of the CHHO to jump out of the local optimum for further optimization. Experimental results show that the CHHO has better optimization performance by comparing with the existing mainstream algorithms when solving QWSC problems. Additionally, the preprocessing approach not only greatly improves the optimization performance of the CHHO but also can be freely utilized in other meta-heuristics based approaches.