Diverse Top-k Service Composition for Consumer Electronics With Digital Twin in MEC

Mobile Edge Computing (MEC) stands as an indispensable technology in the facilitation of 5G networks, enabling the deployment of widely-used services on edge servers situated in close proximity to consumer electronics. Within the MEC framework, a central role is attributed to edge service composition (ESC), pivotal in bolstering functionality and ameliorating user experiences. Presently, prevailing methods for ESC predominantly center on the prioritization of Quality of Service (QoS) optimization, presenting a solitary optimal composite service for consumer electronics invocation. Regrettably, this approach sidelines the significance of solution diversity within composite services, potentially resulting in service overload and the suboptimal utilization of edge resources. To surmount these challenges, this study integrates digital twin (DT) technology and diversified search mechanisms into the MEC domain, offering an innovative diversified top-k service composition methodology known as DSC-DT. By harnessing the capabilities of DT technology, DSC-DT enables the emulation and assessment of diverse composite service solutions within a virtual space. Specifically, the proposed methodology models the procedure of service composition within a DT environment as an issue of subgraph isomorphism. This is succeeded by the configuration of the diversification process as an independent set predicament within an undirected graph, efficiently resolved through a greedy algorithmic paradigm. It is noteworthy that DSC-DT accommodates a gamut of query types, including normal queries, constraint queries, and optimal queries. The efficacy and efficiency of the proposed approach are corroborated through comprehensive experiments conducted upon authentic datasets

Top-k Web Service Compositions using Fuzzy Dominance Relationship

International audienceData Web service composition is a powerful means to answer users' complex queries. User preferences are a key aspect that must be taken into account in the composition scheme. In this paper, we present an approach to automati- cally compose Data Web services while taking into account the user preferences. User preferences are modeled thanks to fuzzy sets. We use an RDF query rewriting algorithm to determine the relevant services. The fuzzy constraints of the relevant services are matched to those of the query using a set of matching methods. We rank-order services using a fuzzification of Pareto dominance, then compute the top-k service compositions. We propose also a method to improve the diversity of returned compositions while maintaining as possible the compositions with the highest scores. Finally, we present a thorough experimental study of our approach

Dynamic Formation and Strategic Management of Web Services Communities

In the last few years, communities of services have been studied in a certain numbers of proposals as virtual pockets of similar expertise. The motivation is to provide these services with high chance of discovery through better visibility, and to enhance their capabilities when it comes to provide requested functionalities. There are some proposed mechanisms and models on aggregating web services and making them cooperate within their communities. However, forming optimal and stable communities as coalitions to maximize individual and group efficiency and income for all the involved parties has not been addressed yet. Moreover, in the proposed frameworks of these communities, a common assumption is that residing services, which are supposed to be autonomous and intelligent, are competing over received requests. However, those services can also exhibit cooperative behaviors, for instance in terms of substituting each other. When competitive and cooperative behaviors and strategies are combined, autonomous services are said to be "coopetitive". Deciding to compete or cooperate inside communities is a problem yet to be investigated. In this thesis, we first identify the problem of defining efficient algorithms for coalition formation mechanisms. We study the community formation problem in two different settings: 1) communities with centralized manager having complete information using cooperative game-theoretic techniques; and 2) communities with distributed decision making mechanisms having incomplete information using training methods. We propose mechanisms for community membership requests and selections of web services in the scenarios where there is interaction between one community and many web services and scenarios where web services can join multiple established communities. Then in order to address the coopetitive relation within communities of web services, we propose a decision making mechanism for our web services to efficiently choose competition or cooperation strategies to maximize their payoffs. We prove that the proposed decision mechanism is efficient and can be implemented in time linear in the length of the time period considered for the analysis and the number of services in the community. Moreover, we conduct extensive simulations, analyze various scenarios, and confirm the obtained theoretical results using parameters from a real web services dataset