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2017 | OriginalPaper | Buchkapitel

12. Adaptive Resource Allocation for Load Balancing in Cloud

verfasst von : Somnath Mazumdar, Alberto Scionti, Anoop S. Kumar

Erschienen in: Cloud Computing

Verlag: Springer International Publishing

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Abstract

Cloud computing has become a robust computing paradigm aimed at providing ubiquitous access to almost “infinite” computational as well as storage resources. However, the ever-changing demand for computational capabilities pushes data centres (DCs) to adopt power-hungry solutions. The problem of reducing energy consumption in a DC is exacerbated by the difficulties in fairly distributing the workload among the available physical servers. Current methods rely on algorithmic solutions which are not able to capture and counterbalance all the changes in the user access pattern. It leads to an over-provisioning of the resources and to an underutilisation of the active servers. This chapter advocates for an effective way to tackle the resource allocation problem with the aim of improving energy efficiency and reliability. We show how a flexible framework, designed to foreseen expected load and to use an evolutionary optimisation algorithm (such as particle swarm optimization – PSO), can efficiently map the user requests with the available hardware resources.

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Titel: Adaptive Resource Allocation for Load Balancing in Cloud
verfasst von: Somnath Mazumdar
Alberto Scionti
Anoop S. Kumar
Verlag: Springer International Publishing
Buch: Cloud Computing
Print ISBN: 978-3-319-54644-5

Electronic ISBN: 978-3-319-54645-2

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-54645-2_12