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A Security-Driven Scheduling Model for Delay-Sensitive Tasks in Fog Networks

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Advances in Computing, Informatics, Networking and Cybersecurity

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 289))

Abstract

Nowadays, the uses of delay-sensitive applications are rapidly increasing due to their performance, QoS, and enrich the user experience. Therefore, security and scheduling aspects for delay-sensitive tasks have become more critical issues that are not incorporated in the current existing algorithms. To solve these intricate issues, “A security-driven scheduling model for delay-sensitive tasks in Fog networks” has been introduced and abbreviated as “SDSM”. The proposed method is the integration of binary integer programming, Min_Heap algorithm, and modified Earliest Deadline First policy (m-EDF). The binary integer programming is used to evaluate optimal average security value for delay-sensitive tasks from basic security service categories, i.e., confidentiality, integrity, and authentication whereas, only one security service can be selected from a category, however, each category has some distinct security services along with their normalized performance value. The Min_Heap algorithm is used to find an optimal node in Fog networks, in which system load and load threshold values are used as the key parameters which are based on the weighted sum of the square method. And the m-EDF scheduling policy is used for the delay-sensitive tasks. The contribution of the proposed method is two-fold: first, is to provide the robust security service to the delay-sensitive tasks, and second, is to enhance the performance of the system (in terms of success ratio) without violating the scheduling constraints of delay-sensitive tasks. The novelty of the proposed method is proven in terms of success ratio, average security value, and overall performance through extensive experimental result analysis and compared to some existing baseline algorithms. The Network Simulator (NS-3) with python scriptwriting and a synthetic data set is used to obtain the experimental results.

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Notes

  1. 1.

    The global buffer is assumed as a finite size buffer.

  2. 2.

    The accepted and rejected queue are used to calculate the success ratio only.

  3. 3.

    Here node has multi-core processor.

  4. 4.

    Starting index of an array is zero (0).

  5. 5.

    sum of all assigned weight of each category equals to 1 [22].

  6. 6.

    The scheduling mode (SM), m-EDF scheduler, FN, task model, and scheduling constraints have developed using Python scriptwriting.

  7. 7.

    Author have selected these baseline algorithms due to having sufficient available synthetic data set.

  8. 8.

    This study has considered three Fog networks for simulation.

  9. 9.

    Overall performance is measured in terms of Fog networks.

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Author information

Authors and Affiliations

  1. National Institute of Technology, Uttarakhand, India

    Surendra Singh

  2. Indina Institute of Technology (IMS) Dhanbad, Dhanbad, India

    Sachin Tripathi

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  1. Surendra Singh
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  2. Sachin Tripathi
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Correspondence to Surendra Singh .

Editor information

Editors and Affiliations

  1. Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Petros Nicopolitidis

  2. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India

    Sudip Misra

  3. Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada

    Laurence T. Yang

  4. Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA

    Bernard Zeigler

  5. Dalian University of Technology, Dalian, China

    Zhaolng Ning

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Singh, S., Tripathi, S. (2022). A Security-Driven Scheduling Model for Delay-Sensitive Tasks in Fog Networks. In: Nicopolitidis, P., Misra, S., Yang, L.T., Zeigler, B., Ning, Z. (eds) Advances in Computing, Informatics, Networking and Cybersecurity. Lecture Notes in Networks and Systems, vol 289. Springer, Cham. https://doi.org/10.1007/978-3-030-87049-2_29

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