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Authors = Fethallah Hadjila

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23 pages, 468 KiB  
Article
An Intelligent Bat Algorithm for Web Service Selection with QoS Uncertainty
by Abdelhak Etchiali, Fethallah Hadjila and Amina Bekkouche
Big Data Cogn. Comput. 2023, 7(3), 140; https://doi.org/10.3390/bdcc7030140 - 10 Aug 2023
Cited by 1 | Viewed by 1824
Abstract
Currently, the selection of web services with an uncertain quality of service (QoS) is gaining much attention in the service-oriented computing paradigm (SOC). In fact, searching for a service composition that fulfills a complex user’s request is known to be NP-complete. The search [...] Read more.
Currently, the selection of web services with an uncertain quality of service (QoS) is gaining much attention in the service-oriented computing paradigm (SOC). In fact, searching for a service composition that fulfills a complex user’s request is known to be NP-complete. The search time is mainly dependent on the number of requested tasks, the size of the available services, and the size of the QoS realizations (i.e., sample size). To handle this problem, we propose a two-stage approach that reduces the search space using heuristics for ranking the task services and a bat algorithm metaheuristic for selecting the final near-optimal compositions. The fitness used by the metaheuristic aims to fulfil all the global constraints of the user. The experimental study showed that the ranking heuristics, termed “fuzzy Pareto dominance” and “Zero-order stochastic dominance”, are highly effective compared to the other heuristics and most of the existing state-of-the-art methods. Full article
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