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Genetic Algorithm Framework for Bi-objective Task Scheduling in Cloud Computing Systems

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Distributed Computing and Internet Technology (ICDCIT 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8956))

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Abstract

Cloud computing gives an excellent opportunity for business enterprises as well as researchers to use the computing power, over Internet, without actually owning the infrastructure, there by reducing establishment and management cost. Task scheduling in cloud systems is challenging due to the conflicting objectives of end users and the cloud service providers. Running time and cost are two key factors that determine the optimal service from the cloud. In this paper, we focus on two objectives, makespan and cost, to be optimized simultaneously using genetic algorithm framework. Finding an optimal schedule, considering both of these conflicting objectives, is a search problem under NP-hard category. We have considered the scheduling of independent tasks and the proposed frame work can be used in public or hybrid cloud.

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Beegom, A.S.A., Rajasree, M.S. (2015). Genetic Algorithm Framework for Bi-objective Task Scheduling in Cloud Computing Systems. In: Natarajan, R., Barua, G., Patra, M.R. (eds) Distributed Computing and Internet Technology. ICDCIT 2015. Lecture Notes in Computer Science, vol 8956. Springer, Cham. https://doi.org/10.1007/978-3-319-14977-6_38

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  • DOI: https://doi.org/10.1007/978-3-319-14977-6_38

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14976-9

  • Online ISBN: 978-3-319-14977-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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