Paper Contents
Abstract
In the evolving landscape of distributed computing, heterogeneous systems have emerged as a powerful paradigm for executing complex and large-scale applications. However, heterogeneity in computing resources poses significant challenges for efficient task allocation and load balancing. This paper explores the design and implementation of efficient task partitioning algorithms tailored for heterogeneous distributed systems. We propose an adaptive hybrid algorithm that integrates static and dynamic strategies for optimal task distribution, taking into account the computational capabilities and communication overheads of each node. The proposed approach enhances system throughput, reduces task completion time, and ensures balanced resource utilization. Simulation results and a comparative study against traditional partitioning techniques validate the efficacy of the model.Keywords: Task partitioning, heterogeneous systems, distributed computing, load balancing, scheduling algorithms, resource allocation.
Copyright
Copyright © 2025 DR ANIL KARADWAL. This is an open access article distributed under the Creative Commons Attribution License.
