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A Pair-Task Heuristic for Scheduling Tasks in Heterogeneous Multi-cloud Environment

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Abstract

Heterogeneous multi-cloud environments make use of a collection of diverse performance rich cloud resources, linked with huge-speed, performs varied applications which are of computational nature. Applications in the multi-cloud environment require distinct computational features for processing. Heterogeneous multi-cloud domain well suits to satisfy the computational need of very big diverse nature of collection of tasks. Scheduling tasks to distributed heterogeneous clouds is termed NP-complete which leads to the ultimate establishment of heuristic problem solving technique. Identifying the heuristic which is appropriate and best still exists as a complicated problem. In this paper, to address scheduling collection of ‘n’ tasks in two groups among a set of 'm' clouds, three heuristicsPair-Task Threshold Limit (PTL), PTMax-Min, and PTMin-Max are proposed. Firstly, proposedheuristics calculate tasks threshold valuebased on the tasks attributes to determine the tasks scheduling order and then tasks are sorted in descending order of threshold value. Group 1 comprises ([n/2]) tasks ordered in descending value of threshold. Group 2 comprises remaining tasks ([n/2] − 1) ordered in ascending value of threshold. Secondly, tasks form group 1 are scheduled first based on minimum completion time, and then tasks in group 2 are scheduled. The proposed heuristicsare compared with existing heuristics, namely MCT, MET, Min-Min using benchmark dataset. The proposed approaches PTL, PTMax-Min, and PTMin-Max explicitly shows the better results in terms of reduced makespan, completion time, response time and more resource utilization compared to MCT, MET, and Min-min.

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Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

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Funding

There was no financial support received from any organization for carrying out this work.

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Authors and Affiliations

  1. Department of Information Technology, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India

    Kamalam Gobichettipalayam Krishnasamy

  2. School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    Suresh Periasamy & Keerthika Periasamy

  3. Department of Electrical and Electronics Engineering, Government College of Technology, Coimbatore, Tamil Nadu, India

    V. Prasanna Moorthy

  4. Department of Engineering, University of Technology and Applied Sciences, Muscat, Sultanate of Oman

    Gunasekaran Thangavel

  5. Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, Jaipur, Rajasthan, India

    Ravita Lamba

  6. Department of Electronics and Communication Engineering, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India

    Suresh Muthusamy

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  1. Kamalam Gobichettipalayam Krishnasamy
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Contributions

KGK, SP-Drafting the manuscript. KP, PMV-Assisting in drafting the manuscript. GT, RL, SM-project administration.

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Correspondence to Suresh Muthusamy.

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This paper organization proceeds as follows: Sect. 1 brings out detailed introduction. Section 2 lists related works on task scheduling in cloud. Section 3 brings out problem formulation and cloud model of the proposed work. Section 4 discusses the proposed methods such as PTL, PTMax-Min, and PTMin-Max. Section 5 illustrates the performance comparison of proposed heuristicswith the existing heuristic approaches. Sect. 6 provides conclusion and future scope of theresearch work.

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Krishnasamy, K.G., Periasamy, S., Periasamy, K. et al. A Pair-Task Heuristic for Scheduling Tasks in Heterogeneous Multi-cloud Environment. Wireless Pers Commun 131, 773–804 (2023). https://doi.org/10.1007/s11277-023-10454-9

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