Volume 10 Number 7 (Jul. 2015)
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JSW 2015 Vol.10(7): 869-880 ISSN: 1796-217X
doi: 10.17706/jsw.10.7.869-880

Energy-Aware Load Balanced Scheduler for Cloud Computing to Improve Quality of Service

N. R. Ram Mohan1*, E. Baburaj2
1Computer and Information Technology, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India.
2Dept of Computer Science and Engineering, Sun College of Engineering and Technology, Nagercoil, Tamilnadu, India.

Abstract—Cloud computing paradigm has progressed as extremely ascendable services with increasing power on computation, massive storage possibility and the resources being obtained as service using cloud environment by providing guarantee to the Service Level. However, the subscriber requirement has increased to an extent that necessitates a big active platform for balancing the load though the available resources are shared according to the availability. With the advent of powerful network processors, the cloud computing paradigm also give rise to load balancing problem which has to be solved in an optimal manner in order to avoid deadlock and enhance resource effectiveness. To address the issue of energy conservation in cloud computing paradigm, the use of progressive traffic data from data centers applied a service invocation forecast model. The collaborative data possession scheme applied responsive pattern using the Homomorphic verifiable format and hierarchy was performed using hash index model but the disadvantage of the model was that the match index structure did not matched properly using cluster. However enforcing policies in cloud computing paradigm is challenging because of the different slabs of power tariffs and requirements made to the servers affect the decisions, whether the loads to be pushed in or out of a cluster affecting the overall energy utilization. To address the issue of balancing the load and optimizing the bandwidth and energy utilization, an Energy-aware Load Balanced Scheduler (ELBS) for cloud computing to improve Quality of Service is presented.. The effectiveness of the proposed ELBS model is illustrated by theoretical analysis with Virtual Machine (VM) energy-efficient cloud data centers. Performance metric for evaluation of ELBS model is measured in terms of computational complex for energy utilization, performance (in terms of throughput), bandwidth utilization rate, cloud computation cost, and response time to service invocation, load balance to improve QoS and clustering quality.

Index Terms—Service level agreement, energy-aware load balanced scheduler, virtual machine, cloud computing paradigm, bandwidth utilization, query messaging, data centers.


Cite: N. R. Ram Mohan, E. Baburaj, "Energy-Aware Load Balanced Scheduler for Cloud Computing to Improve Quality of Service," Journal of Software vol. 10, no. 7, pp. 869-880, 2015.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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