MSLB:Multi-level scheduling for achieving load balancing in Cloud Environment

Cloud computing offers an efficient solution to the users for the storage, computation, and many such services. With the incoming user requests, cloud system is assigned with load. This makes the system overloaded, underloaded and balanced system. The situations of overloaded and underloaded cloud s...

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Veröffentlicht in:NeuroQuantology 2022-01, Vol.20 (8), p.8029
Hauptverfasser: Priyadarshini, Aliva, Pradhan, Sateesh Kumar, Samaleswari Prasad Nayak
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Sprache:eng
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Zusammenfassung:Cloud computing offers an efficient solution to the users for the storage, computation, and many such services. With the incoming user requests, cloud system is assigned with load. This makes the system overloaded, underloaded and balanced system. The situations of overloaded and underloaded cloud system may invite different problems like power consumption, device failure, etc. So, load balancing is an essential system needs for a healthy and robust system. It becomes a significant aspect of task scheduling in cloud computing. There are various factors for considering load of the system such as memory load, network load, computation load etc. Various researches proposed different solutions to balance the load in cloud infrastructure. Through this article an optimal load balancing mechanism MSLB is proposed with solutions. A brief explanation of different parameters is also provided by comparing existing solutions with proposed one. An innovative solution to balance the load of the virtual machines is described considering various user bases. Simulation results are obtained using Cloud Analytics and the results are presented to support that.
ISSN:1303-5150
DOI:10.14704/nq.2022.20.8.NQ44828