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A Hybrid Algorithm for Optimized Resource Allocation under Constrained Task Schedule

Publication Type : Conference Proceedings

Publisher : 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), IEEE,

Source : 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), IEEE, Erode, India, p.136-141 (2020)

Url : https://ieeexplore.ieee.org/document/9076471

Keywords : chunk allocation, geometrical domain, random tie-breaking, Resource allocation, task compatibility

Campus : Amritapuri

School : Department of Computer Science and Engineering, School of Engineering

Center : AI (Artificial Intelligence) and Distributed Systems, Algorithms and Computing Systems

Department : Computer Science

Year : 2020

Abstract : We present a novel hybrid algorithm for optimal resource allocation for scheduling tasks that satisfy a variety of diverse constraints. The problem is pitched in geometrical domain and has direct application to several areas including, and not limited to physical resource allocation, crowd sourcing and distributed/cloud computing. The fundamental problem is to complete a set of N tasks at geographically separate locations in a two-dimensional plane where each task takes a fixed duration, requires certain number resources and must be completed within a specified time window. The goal is to maximize the profit by efficient utilization of resources and reducing the cost of movement between locations and waiting at each location. In this paper, we propose multiple strategies with each one progressively better than the previous. The main contribution of the paper is the novel hybrid algorithm that combines the traditional greedy approach with chunk allocation and random tie-breaking scheme to achieve maximal profit by efficient resource allocation.

Cite this Research Publication : M. Pugalia, A. Ashok, and Swaminathan J., “A Hybrid Algorithm for Optimized Resource Allocation under Constrained Task Schedule”, 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC). IEEE, Erode, India, pp. 136-141, 2020.

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