SWrenOA: SpiderWren Optimization Algorithm with Multi-objectives for Agent-based Aggregation of Cloud Web Service Selection.
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| Title: | SWrenOA: SpiderWren Optimization Algorithm with Multi-objectives for Agent-based Aggregation of Cloud Web Service Selection. |
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| Authors: | Nagarmunoli, Sreedevi R., Patil, Uttam, Gudnavar, Anand |
| Source: | International Journal of Intelligent Engineering & Systems; 2025, Vol. 18 Issue 11, p482-499, 18p |
| Subject Terms: | QUALITY of service, CLOUD computing, MULTI-objective optimization, OPTIMIZATION algorithms |
| Abstract: | Cloud web service selection involves identifying the most suitable cloud-based services, such as hosting, databases, computing resources, and storage for specific applications. Ensuring reliable, cost-efficient, and requirement-based selection remains a challenge due to the vast number of available services. To address this, a novel method, the Spider Wren Optimization Algorithm (SWrenOA), is proposed. Initially, cloud providers like MFunds Service, WSEmboss Service, captcha WebService, TRMDemoBPService, transportservice, Adminservice, and OddFactWebService are considered. A user query is then matched against provider services to generate a candidate list. SWrenOA is applied for final selection using multi-objective Quality of Service (QoS) parameters, including response time, cost, availability, latency, reputation, reliability, confidentiality, authentication, and non-repudiation. SWrenOA is designed by combining the Spider Wasp Optimizer (SWO) and Superb Fairy-wren Optimization Algorithm (SFOA). Finally, the chosen services undergo agent-based aggregation to produce the final selection. The proposed approach achieves precision, F-measure, and recall of 96.47%, 97.38%, and 96.92%, respectively. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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