A quality of service–aware preemptive tidal flow queuing model for wireless multimedia sensor networks in the smart grid environment

Li Peizhe, Wu Muqing, Zhao Min and Liao Wenxing

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 7, 1550147717718755

Abstract: The smart grid incorporates a two-way communication system between customers and the utility for advanced monitoring and intelligent control of supply and demand. Wireless multimedia sensor network can be treated as an organic supplement and a peripheral network in this two-way communication system. However, the challenging smart grid environment makes it difficult to achieve a high quality of service in wireless multimedia sensor network. This article proposes a prioritization mechanism that considers the heterogeneous characteristics of smart grid traffic. Specifically, an innovative channel allocation and traffic scheduling scheme, named the preemptive tidal flow queuing model, is presented. This scheme achieves differentiated services for diverse communication data when the wireless multimedia sensor network accesses the core network and ensures the performance for high-priority data at the expense of the performance for low-priority data. Simulation analyses show that the performance for high-priority messages can be reliably guaranteed and that the preemptive tidal flow queuing model satisfies the requirements for a wireless multimedia sensor network operating in the smart grid environment. This article offers three main contributions: the development of a prioritization mechanism specifically for a wireless multimedia sensor network in the smart grid environment, the proposal of the preemptive tidal flow queuing model, and the presentation of formulas and simulations to verify the performance of the preemptive tidal flow queuing model.

Keywords: Smart grid; wireless multimedia sensor network; matrix theory; prioritization mechanism; preemptive tidal flow queuing model (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:7:p:1550147717718755

DOI: 10.1177/1550147717718755

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