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A Probabilistic Deadline-aware Application Offloading in a Multi-Queueing Fog System: A Max Entropy Framework

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Abstract

Cloud computing and its derivatives, such as fog and edge computing, have propelled the IoT era, integrating AI and deep learning for process automation. Despite transformative growth in healthcare, education, and automation domains, challenges persist, particularly in addressing the impact of multi-hopping public networks on data upload time, affecting response time, failure rates, and security. Existing scheduling algorithms, designed for multiple parameters like deadline, priority, rate of arrival, and arrival pattern, can minimize execution time for high-priority applications. However, the difficulty lies in simultaneously minimizing overall application execution time while mitigating resource depletion issues for low-priority applications. This paper introduces a cloud-fog-based computing architecture to tackle fog node resource starvation, incorporating joint probability, loss probability, and maximum entropy concepts. The proposed model utilizes a probabilistic application scheduling algorithm, considering priority and deadline and employing expected loss probability for task offloading. Additionally, a second algorithm focuses on resource starvation, optimizing task sequence for minimal response time and improved quality of service in a multi-Queueing fog system. The paper demonstrates that the proposed model outperforms state-of-the-art models, achieving a 3.43-5.71% quality of service improvement and a 99.75-267.68 msec reduction in response time through efficient resource allocation.

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We declare that we have not received any funding for this research work.

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Authors and Affiliations

  1. KIET Group of Institutions, Delhi-NCR, Ghaziabad, India

    Naveen Chauhan

  2. Department of Electronics and Communications, Llyod Institute of Engineering and Technology, Greater Noida, 201306, India

    Rajeev Agrawal

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  1. Naveen Chauhan
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  2. Rajeev Agrawal
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Contributions

Naveen Chauhan: Investigation, Proposed Framework designing, Conceptualization, Writing-original draft, Result simulation, Result compilation, Validation. Rajeev Agrawal: Supervision, Conceptualization, Result compilation, Quality check.

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Correspondence to Naveen Chauhan.

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\(^{1}\)Computer Science and Engineering Department, Indian Institute of Technology (Indian School of Mines), Dhanbad, India. \(^2\) Department of Electronics and Communications, Llyod Institute of Engineering and Technology, Greater Noida, India.

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Chauhan, N., Agrawal, R. A Probabilistic Deadline-aware Application Offloading in a Multi-Queueing Fog System: A Max Entropy Framework. J Grid Computing 22, 31 (2024). https://doi.org/10.1007/s10723-024-09753-7

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