Abstract
The cloud acts as a model that contains an aggregation of resources and data that needs to be shared among users. The scheduling of the load acts as a major challenge to fulfill the requests of the several users. Till now several algorithms have been proposed for fulfilling the purpose of load scheduling in cloud. The latest works are based on swarm-intelligence techniques. However, one such swarm-intelligence technique Bee Swarm Optimization (BSO) has not been exploited for serving this purpose. In this paper, an improvised version of BSO, the Improved Bee Swarm Optimization in Cloud (IBSO-C) has been proposed with the objective of efficient and cost-effective scheduling in cloud. It uses the swarm of particles as bees for scheduling and updated total cost evaluation function. The proposed algorithm is validated and tested by analysis on large set of iterations. The comparison of results with existing techniques has proven, the proposed IBSO-C to be a more cost-effective algorithm.
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Chaudhary, D., Kumar, B., Sakshi, S., Khanna, R. (2018). Improved Bee Swarm Optimization Algorithm for Load Scheduling in Cloud Computing Environment. In: Panda, B., Sharma, S., Roy, N. (eds) Data Science and Analytics. REDSET 2017. Communications in Computer and Information Science, vol 799. Springer, Singapore. https://doi.org/10.1007/978-981-10-8527-7_33
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DOI: https://doi.org/10.1007/978-981-10-8527-7_33
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