Comprehensive quality-aware automated semantic web service composition is an NP-hard problem, where service composition workflows are unknown, and comprehensive quality, i.e., Quality of services (QoS) and Quality of semantic matchmaking (QoSM) are simultaneously optimized. The objective of this problem is to find a solution with optimized or near-optimized overall QoS and QoSM within polynomial time over a service request. In this paper, we proposed novel memetic EDA-based approaches to tackle this problem. The proposed method investigates the effectiveness of several neighborhood structures of composite services by proposing domain-dependent local search operators. Apart from that, a joint strategy of the local search procedure is proposed to integrate with a modified EDA to reduce the overall computation time of our memetic approach. To better demonstrate the effectiveness and scalability of our approach, we create a more challenging, augmented version of the service composition benchmark based on WSC-08 bansal2008wsc and WSC-09 kona2009wsc . Experimental results on this benchmark show that one of our proposed memetic EDA-based approach (i.e., MEEDA-LOP) significantly outperforms existing state-of-the-art algorithms.
In the second category, service composition solutions are represented as permutations, which are then decoded into solutions represented as DAGs @cite_20 @cite_37 @cite_24 . PSO is utilized to find an optimized queue of services (i.e., a permutation), which can be decoded into a corresponding DAG-based composite service @cite_24 . @cite_20 extends @cite_24 to jointly optimize QoSM and QoS, where a weighted DAG is decoded, where edge weights correspond to matchmaking quality between services. These two PSO-based approaches rely on PSO to determine the weights of particle's position (that corresponding with a service) to form an ordered service queue. Optimizing QoSM and QoS simultaneously is more challenging than optimizing QoS only because the searching space has significantly increased, and it demands more effective and efficient searching techniques. Apart from that, it has been suggested that utilizing the indirect representation often contributes to a higher performance, compared to direct representation @cite_37 . It is due to that the search space is not unwittingly restricted by unconstrained random initialization of solutions and operators.
@cite_24 @cite_37 @cite_20
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Web services have become increasingly popular in recent years, and they are especially suitable to the process of Web service composition, which is when several services are combined to create an application that accomplishes a more complex task. In recent years, significant research efforts have been made on developing approaches for performing Quality of Service -aware Web service composition. Evolutionary computing (EC) techniques have been widely used for solving this problem, since they allow for the quality of compositions to be optimised, meanwhile also ensuring that the solutions produced have the required functionality. Existing EC-based composition approaches perform constrained optimisation to produce solutions that meet those requirements, however these constraints may hinder the effectiveness of the search. To address this issue, a novel framework based on an indirect representation is proposed in this work. The core idea is to first generate candidate service compositions encoded as sequences of services. Then, a decoding scheme is developed to transform any sequence of services into a corresponding feasible service composition. Given a service sequence, the decoding scheme builds the workflow from scratch by iteratively adding the services to proper positions of the workflow in the order of the sequence. This is beneficial because it allows the optimisation to be carried out in an unconstrained way, later enforcing functionality constraints during the decoding process. A number of encoding methods and corresponding search operators, including the PSO, GA, and GP-based methods, are proposed and tested, with results showing that the quality of the solutions produced by the proposed indirect approach is higher than that of a baseline direct representation-based approach for twelve out of the thirteen datasets considered. In particular, the method using the variable-length sequence representation has the most efficient execution time, while the fixed-length sequence produces the highest quality solutions. In recent years, quite a few search algorithms have been used to solve Web service composition problem. However, it is still lack of systematic analysis about these methods. In the paper, we attempt to analyze the effect of three typical meta-heuristic search algorithms. The experimental analysis is performed according to the search-based Web service composition framework. In the experiments, we mainly carry out the analysis as follows: different abstract service number, different candidate service number and different QoS constraint strength. Based on the above analysis, some guidelines of realizing Web service composition via search algorithms are yielded. For example, EDA is suitable for the composition problem with large abstract service number. PSO is more effective for the case of large candidate service number. GA is a good choose for the little-scale Web service composition problem. In addition, EDA can effectively settle the composition problem with strong QoS constraint. GA is suitable for the problem with medium constraint strength, and PSO has the poor ability to tackle the QoS constraint with high strength. Web service composition has been a prevailing research direction in recent years. There are two major challenges faced by researchers, semantic matchmaking and Quality of Service (QoS) optimisation. Semantic matchmaking aims to discover interoperable web services that can interact with each other by their resources described semantically. QoS optimisation aims to optimise the non-functional requirements of service users, such as minimum cost and maximum reliability. To meet the requirements of service users, both semantic matchmaking quality and QoS should be considered simultaneously. Most existing works on web service composition, however, focus only on one of these two aspects. Therefore, we propose a comprehensive quality model that takes both semantic matchmaking quality and QoS into account with the aim of achieving a more desirable balance of both sides. Further, we develop a PSO-based service composition approach with explicit support for the proposed comprehensive quality model. We also conduct experiments to explore the effectiveness of our PSO-based approach and the desirable balance achieved by using our comprehensive quality model. Many enterprises have a growing interest in service composition to construct their business applications. With the increase of alternative services, Quality of Service (QoS) becomes an important indicator of obtaining optimal composite services. Due to the dynamic nature of the service environment, a composite service may not guarantee to deliver an overall optimal QoS. Re-optimization approaches have been developed to handle a dynamic environment. However, these approaches do not consider the diversity of alternative solutions, which may lead to better solutions. In this work, we introduce an adaptive approach, called estimation of distribution algorithm based on Restricted Boltzmann Machine (rEDA). rEDA effectively maintains the diversity of alternative solutions, by leveraging the inference ability of Restricted Boltzmann Machine to capture the potential solutions. It also provides a predictive guidance for the exploration of solution space, by considering the degree of how well a service contributes to the global QoS. The experimental evaluation shows that rEDA has a significant improvement on effectiveness and efficiency over existing approaches.