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Multicriteria-based Resource-Aware Scheduling in Mobile Crowd Computing: A Heuristic Approach

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Abstract

Mobile crowd computing (MCC) has been fathomed as a high-performance computing system where public-owned smart mobile devices (SMDs) are utilized as computing resources to execute compute-intensive tasks. The overall performance and the integrity of the MCC can be assessed by factors such as execution time, resource utilization, load balancing, etc. An efficient task scheduler should conform to these requirements. Conversely, an inefficient scheduling method will have a negative impact on the QoS of MCC. However, in a dynamic and heterogeneous system like MCC, it is nontrivial to realize such an optimized scheduler, considering the fact that scheduling in a heterogeneous distributed system is an NP-complete problem. In this paper, a heuristic algorithm for resource-aware scheduling in MCC is proposed with the objectives of minimizing makespan and maximizing resource utilization and load balancing. Before scheduling, the resource strength of each SMD is calculated by considering several static and dynamic resource parameters such as CPU clock speed, number of cores, its present load, available RAM and battery, and device temperature. The work is analyzed and validated by extensive simulations with synthetic as well as collected datasets. Experimenting with diverse simulation scenarios confirms the consistency and reliability of the proposed algorithm. The proposed algorithm exhibits significant improvements compared to other popular meta-heuristic algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), and a heuristic algorithm minimum completion time (MCT) in terms of the considered objectives. The statistical hypothesis tests, viz. analysis of variance (ANOVA) and post hoc tests, are carried out to demonstrate the effectiveness of the proposed work.

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Data Availability

All data generated or analyzed during this study are included in the manuscript (Table 10). No separate data was used in the experiment.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, National Institute of Technology Durgapur, Durgapur, West Bengal, India

    Pijush Kanti Dutta Pramanik & Prasenjit Choudhury

  2. Department of Technology, Jodhpur Institute of Engineering and Technology, Jodhpur, Rajasthan, India

    Pijush Kanti Dutta Pramanik

  3. Department of Computer Science & Engineering, Indian Institute of Information Technology Ranchi, Ranchi, Jharkhand, India

    Tarun Biswas

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Piush Kanti Dutta Pramanik conceptualized and formulated the problem, wrote the paper, and interpreted and analyzed the results. Tarun Biswas formulated the problem, carried out the experiments and reviewed the paper. Prasenjit Choudhury supervised the work including reviewing, quality checking, and correction. All authors read and approved the final manuscript.

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Correspondence to Pijush Kanti Dutta Pramanik.

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Dutta Pramanik, P.K., Biswas, T. & Choudhury, P. Multicriteria-based Resource-Aware Scheduling in Mobile Crowd Computing: A Heuristic Approach. J Grid Computing 21, 1 (2023). https://doi.org/10.1007/s10723-022-09633-y

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