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The Journal of Supercomputing
Published in: The Journal of Supercomputing 1/2015

01-01-2015

QRSF: QoS-aware resource scheduling framework in cloud computing

Authors: Sukhpal Singh, Inderveer Chana

Published in: The Journal of Supercomputing | Issue 1/2015

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Abstract

Cloud computing harmonizes and delivers the ability of resource sharing over different geographical sites. Cloud resource scheduling is a tedious task due to the problem of finding the best match of resource-workload pair. The efficient management of dynamic nature of resource can be done with the help of cloud workloads. Till cloud workload is deliberated as a central capability, the resources cannot be utilized in an effective way. In literature, very few efficient resource scheduling policies for energy, cost and time constraint cloud workloads are reported. This paper presents an efficient cloud workload management framework in which cloud workloads have been identified, analyzed and clustered through K-means on the basis of weights assigned and their QoS requirements. Further scheduling has been done based on different scheduling policies and their corresponding algorithms. The performance of the proposed algorithms has been evaluated with existing scheduling policies through CloudSim toolkit. The experimental results show that the proposed framework gives better results in terms of energy consumption, execution cost and time of different cloud workloads as compared to existing algorithms.
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Metadata
Title
QRSF: QoS-aware resource scheduling framework in cloud computing
Authors
Sukhpal Singh
Inderveer Chana
Publication date
01-01-2015
Publisher
Springer US
Published in
The Journal of Supercomputing / Issue 1/2015
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-014-1295-6

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