QoS-driven metaheuristic service composition schemes: a comprehensive overview


Masdari M., Nouzad M., Ozdemir S.

ARTIFICIAL INTELLIGENCE REVIEW, cilt.54, sa.5, ss.3749-3816, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 54 Sayı: 5
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1007/s10462-020-09940-4
  • Dergi Adı: ARTIFICIAL INTELLIGENCE REVIEW
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, Educational research abstracts (ERA), Index Islamicus, INSPEC, Library and Information Science Abstracts, Library, Information Science & Technology Abstracts (LISTA), Metadex, Psycinfo, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.3749-3816
  • Anahtar Kelimeler: Metaheuristic, Service composition, Optimization, SOA, PSO, GA, Evolutionary algorithms, PARTICLE SWARM OPTIMIZATION, ANT COLONY OPTIMIZATION, GENETIC ALGORITHM, OPTIMAL-SELECTION, BEES ALGORITHM, SYSTEM, MODEL
  • Hacettepe Üniversitesi Adresli: Evet

Özet

Services Oriented Architecture provides Web Services (WSs) as reusable software components that can be applied to create more complicate composite services for users according to the specified QoS limitations. However, considering many WSs that may be appropriate for each task of a user-submitted workflow, finding the optimal WSs for a composite WS to maximize the overall QoS is an NP-hard problem. As a result, numerous composition schemes have been suggested in the literature to untangle this problem by using various metaheuristic algorithms. This paper presents a comprehensive survey and taxonomy of such QoS-oriented metaheuristic WS composition schemes provided in the literature. It investigates how metaheuristic algorithms are adapted for the WS composition problem and highlight their main features, advantages, and limitations. Also, in each category of the studied composition schemes, a comparison of their applied QoS factors, evaluated metrics, exploited simulators, and properties of the applied metaheuristic algorithms are explained. Finally, the concluding remarks and future research directions are summarized to help researchers in working in this area.