Activity Scheduling on Identical Parallel Processors
Satyasundara Mahapatra1, Rati Ranjan Dash2, Niroj Kumar Pani3

1Satyasundara Mahapatra, Department of Computer Science and Engineering, Pranveer Singh Institute of Technology, Kanpur, India.
2Rati Ranjan Dash, Department of Mechanical Engineering, College of Engineering and Technology, Bhubaneswar, India.
3Niroj Kumar Pani, Department of Computer Science Engineering and Application, Indira Gandhi Institute of Technology, Sarang, India.

Manuscript received on 01 August 2019 | Revised Manuscript received on 07 August 2019 | Manuscript published on 30 August 2019 | PP: 3941-3948 | Volume-8 Issue-10, August 2019 | Retrieval Number: J99260881019/19©BEIESP | DOI: 10.35940/ijitee.J9926.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: The efficiency of parallel processors is achieved for the purpose of quick computing is mainly depending on the scheduling of activity. The most important factor for scheduling of activities are depend on the waiting time which is directly influence the computation time of overall activity. Minimizing the Variance of Waiting Time otherwise known as Waiting Time Variance (WTV) is one of the metrics of Quality of Services (QoS) which enhance the efficiency of activity scheduling. Allocate the activity from a set of activity pool and schedule them for each identical parallel processor for execution in a large scale by minimizing WTV is the main focusing area of this paper. In case of large scale computing activities are complex in nature. A prior knowledge of each activity must be known before the preparation of activity scheduling for efficient and rapid computing. A snake walks style of activity distribution among the parallel processor is presented in this paper for minimization problem. The minimization of WTV is measured with the help of three heuristic intend methods named as RSS, VS and BS. The results of the experiment are compared with current conspires and demonstrate the new snake style conspire is presenting the best practices for proven conspires and challenges in a wide range of activity. The algorithm’s predictable findings appear as illustrated with graph.
Index Terms: Activity, Combinatorial, Deterministic, Identical Parallel Processors, Scheduling, Waiting Time Variance.

Scope of the Article: Parallel Computing on GPU