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QoS based soft computing techniques for evaluating efficient web service recommendation

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Abstract

The main important aspects of SOA are web service recommendation, which aids in the integration of services in the development of a specific or unique application. Since selecting a web service communication code is the critical design concern for enhancing an application, influential effects on the process of development, that recommends the appropriate web service interaction procedure is based on two entities, where (1) (SOAP) Simple Object Access Protocol is a protocol that ensures data interchange in an integrated language environment and (2) (REST) Representational State Transfer Protocol enables unprocessed information (raw data) transfer and communication. The performance of web services for business Applications according to SOAP and the other is REST which is evaluated in this article. Because web services are delivered over the internet, metrics such as throughput and response time are used to assess them. According to the literature review, the emphasis for recommending web services is placed on interaction style. Nowadays, the number of services available rises in complexity, making it taking a long time and hard to interpret by promote certain services with same functions. Features and the set of operations are two terms described frequently in Webservices. If a low-quality application or content chosen by a consumer has an impact on the application's overall performance. As a result, online services are suggested on the basis of various (QoS) quality of service characteristics. Different prototypes in web service recommendation are constructed utilizing soft computing approaches in this suggested paper, and the performances of various parameters are compared.

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Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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Correspondence to S. Senthil Kumar.

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Kumar, S.S., Kumar, P.K.M., Panimalar, S.A. et al. QoS based soft computing techniques for evaluating efficient web service recommendation. Int J Syst Assur Eng Manag 15, 205–215 (2024). https://doi.org/10.1007/s13198-022-01698-y

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