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Experimental Result Paper | Computer and Mathematical Sciences | India | Volume 12 Issue 9, September 2023

Enhancing Load Balancing in Heterogeneous High Performance Cloud Computing with MMWRR+: A Novel Task Allocation Approach

Suvarna N A

Abstract: Cloud computing has emerged as a leading paradigm for providing scalable, on - demand and pervasive computing resources. But load balancing through efficient task allocation remains a challenging problem in cloud environments due to the dynamic and unpredictable nature of workloads across diverse virtualized resources. Addressing this, we present an innovative task allocation approach by amalgamating two state - of - the - art scheduling algorithms, namely Max - Min and Weighted Round - Robin to achieve effective load balancing in heterogeneous high performance distributed computing (HPDC). The proposed method MMWRR+ emphasizes resource awareness, scalability and dynamic adaptability, alleviating resource contention and optimizing resource utilization. Comparative evaluations demonstrate that the proposed approach outperforms the referred individual algorithms and prior research - based improvement techniques to these algorithms. Moreover, it effectively mitigates resource imbalances, efficiently manages diverse workloads and empowers cloud systems to handle fault tolerance.

Keywords: Load Balancing; Resource Optimization; Max - Min; Heuristic Algorithm; Fault Tolerance

Edition: Volume 12 Issue 9, September 2023,

Pages: 757 - 766