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Ant Colony Optimization for Service Composition in Multi-cloud Environments

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dc.contributor.author Maurya, Mahesh
dc.contributor.author G, Vidhya
dc.contributor.author Akram, Faiz
dc.date.accessioned 2025-03-20T11:47:04Z
dc.date.available 2025-03-20T11:47:04Z
dc.date.issued 2024
dc.identifier.uri 10.1109/ICCCNT61001.2024.10725778
dc.identifier.uri https://repository.ju.edu.et//handle/123456789/9408
dc.description.abstract the Ant Colony Optimization (ACO) algorithm is a famous metaheuristic technique that has been successfully applied in various optimization issues. It mimics the foraging conduct of ants to locate the shortest path among meals assets and their colony. Recently, ACO has been increasingly more applied for provider composition in multi-cloud environments. This involves the composition of offerings from different cloud carriers to satisfy the service necessities of a person. By way of using ACO, services can be correctly selected and composed from a couple of carriers, considering elements including cost, excellent, and availability. ACO has proven promising outcomes in enhancing the overall performance and reliability of carrier composition in multi-cloud environments, making it a precious technique in todays tremendously distributed computing landscape. en_US
dc.language.iso en en_US
dc.publisher ICCCNT en_US
dc.subject Service Composition en_US
dc.subject Multi-cloud Environments en_US
dc.subject Distributed Computing en_US
dc.subject Resource Management en_US
dc.subject Quality of Service (QoS) en_US
dc.title Ant Colony Optimization for Service Composition in Multi-cloud Environments en_US
dc.type Article en_US


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