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Erschienen in: The Journal of Supercomputing 10/2019

05.06.2019

SLA-RALBA: cost-efficient and resource-aware load balancing algorithm for cloud computing

verfasst von: Altaf Hussain, Muhammad Aleem, Muhammad Azhar Iqbal, Muhammad Arshad Islam

Erschienen in: The Journal of Supercomputing | Ausgabe 10/2019

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Abstract

Recently, Service-level agreement (SLA) is deemed to be an integral aspect for on-demand provisioning of scalable resources on Cloud. SLA defines important constraints for instance guaranteed quality of service (QoS), pricing, fault-tolerant availability, security, and period of service. Currently, there is a dire need of SLA-based scheduling that improves resources utilization on Cloud. Scheduling with reduced execution time and cost may adversely affect resource utilization. To overcome this issue, we present a cost-efficient SLA-based load balancing scheduler, namely SLA-RALBA, for heterogeneous Cloud infrastructures. The proposed technique supports three levels of SLA opted by the Cloud users. The proposed novel technique incorporates the execution cost for the successful execution of users’ services to elevate the resource utilization on Cloud. The SLA-RALBA is simulated for performance analysis using the benchmark GoCJ and HCSP datasets. The performance results of the SLA-RALBA are compared with the existing schedulers, namely Execution-MCT, Profit-MCT, SLA-MCT, Execution-Min-Min, Profit-Min-Min, and SLA-Min-Min in terms of average resource utilization, execution time, and cost of the Cloud services. The obtained results reveal that SLA-RALBA provides an even trade-off between execution time and cost of the services by guaranteeing a drastic improvement in resource utilization on Cloud than existing algorithms.

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Metadaten
Titel
SLA-RALBA: cost-efficient and resource-aware load balancing algorithm for cloud computing
verfasst von
Altaf Hussain
Muhammad Aleem
Muhammad Azhar Iqbal
Muhammad Arshad Islam
Publikationsdatum
05.06.2019
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 10/2019
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-019-02916-4

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