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Interference-aware clustering approach improving QoS for linear WSNs using a token-based MAC protocol - 2020

Interference-aware clustering approach improving QoS for linear WSNs using a token-based MAC protocol

Research Area:  Wireless Sensor Networks


Wireless sensor networks (WSNs) have received a lot of attention from both academia and industry due to the increasing need for ubiquitous computing for monitoring applications, the continuous advances in miniaturization of electronic devices, and the ultra-low-power wireless technologies. These innovations in technology have driven the curiosity to use sensor networks in a new kind of applications such as road track or railway monitoring, border monitoring, oil and gas, or even water pipeline monitoring. Due to the underlying linear topology of these applications, a new type of network, called a linear sensor network (LSN), has emerged. Because of the specific characteristics of this application and the resource constraints of sensors, some of the major challenges faced in LSNs are to reduce end-to-end delays, to maximize the packet delivery ratio to a sink, and an even distribution of the load between nodes. To achieve these objectives, it is necessary to control node-to-node packet traffic conditions and to manage radio interference created by simultaneously active nodes. This paper addresses these challenges and proposes a new method of clustering LSNs that reduces or controls radio interference risks in order to satisfy these objectives, application needs, and the resource limitations of sensor nodes in the best possible way. This method is applied for LSNs using a token-passing mechanism to access the medium. The performance evaluation is conducted by using a realistic propagation model in the analytical evaluation and also a NS-2 simulation process.


Author(s) Name:  El Hadji Malick Ndoye, Ousmane Diallo, Nadir Hakem, Frédérique Jacquet, Michel Misson, Joel J. P. C. Rodrigues


Conferrence name:  

Publisher name:  Wiley

DOI:  10.1002/dac.4404

Volume Information:  Volume33, Issue11 25 July 2020