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A Mathematical Task Dispatching Model in Wireless Sensor Actor Networks

Morteza Okhovvat, Mohammad Reza Kangavari*

School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
E-mail: morteza.okhovvat@gmail.com

* Corresponding Author: E-mail: email

Computer Systems Science and Engineering 2019, 34(1), 5-12. https://doi.org/10.32604/csse.2019.34.005

Abstract

In this paper, we propose a mathematical task dispatching model to reduce the total tasks completion time, i.e. make-span, in Wireless Sensor Actor Networks (WSANs). The proposed approach minimizes the completion time of tasks that have been allocated to actors but have not yet been dispatched to actors for execution in the networks. We calculate the best rate of dispatching of tasks by the network sink to allocated actors through a steady state analysis of our proposed model to solve equations and inequalities. It is shown that this dispatching rate improves the network lifetime too. Experimental results with a prototyped simulation of the proposed approach show shorter make-span and longer network lifetime compared to when one of the three famous task allocation algorithms, namely, the min-min, opportunistic load balancing (OLB), and stochastic allocation algorithms, is used.

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APA Style
Okhovvat, M., Kangavari, M.R. (2019). A mathematical task dispatching model in wireless sensor actor networks. Computer Systems Science and Engineering, 34(1), 5-12. https://doi.org/10.32604/csse.2019.34.005
Vancouver Style
Okhovvat M, Kangavari MR. A mathematical task dispatching model in wireless sensor actor networks. Comput Syst Sci Eng. 2019;34(1):5-12 https://doi.org/10.32604/csse.2019.34.005
IEEE Style
M. Okhovvat and M.R. Kangavari, “A Mathematical Task Dispatching Model in Wireless Sensor Actor Networks,” Comput. Syst. Sci. Eng., vol. 34, no. 1, pp. 5-12, 2019. https://doi.org/10.32604/csse.2019.34.005

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cc Copyright © 2019 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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