Improvised Dynamic Round-Robin Scheduling for Optimum Resource Utilization in Cloud Systems

Author:

Aradhya Suvarna N1,Priya Rashmi2

Affiliation:

1. JSS Academy of Technical Education Noida

2. GD Goenka University

Abstract

Abstract Task Scheduling is the process of assigning the incoming tasks to the available systems for optimum utilization of resources (CPU, Memory, Bandwidth, etc.). Optimum, in the present context implies executing maximum number of tasks using minimum of resources. In large scale Cloud Computing, resource optimization plays a critical role as it determines the quality of service (QoS) offered to customers. Therefore, task scheduling algorithm for parallel processing directly relates to QoS and is fundamental to understanding Resource Utilization, Inter-Process Communication, Network Latency, Load Balancing, Job Migration and Fault Tolerance. In this paper, an effort is made to explore and understand some of the basic scheduling algorithms through an experimental study. Algorithms are implemented in a cloud scenario. The results are construed with respect to several performance indicators that affect the QoS.

Publisher

Research Square Platform LLC

Reference11 articles.

1. Pandaba Pradhan, Prafulla Ku. Behera, B N B Ray (2016), “Modified Round Robin Algorithm for Resource Allocation in Cloud Computing”, Procedia Computer Science 85, 878–890

2. Saqib Ul Sabha (2018), “ A Novel and Efficient Round Robin Algorithm with Intelligent Time Slice and Shortest Remaining Time First”, Materials Today Proceedings 5, 12009–12015.

3. Dynamic Task scheduling Based on Burst Time requirement for cloud environment”;Bindu VR;International Journal of Computer Networks & Communications (IJCNC),2021

4. “A new median-average round Robin scheduling algorithm: An optimal approach for reducing turnaround and waiting time”;Sakshi Chetan;Alexandria Engineering Journal,2022

5. Abdulaziz A. Alsulami, Qasem Abu Al-Haija, Mohammed I. Thanoon, Qian Mao (2019), “Performance Evaluation of Dynamic Round Robin Algorithms for CPU Scheduling”, DOI: https://doi.org/0.1109/SoutheastCon 42311.2019.9020439

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