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Directional antenna based node localization and reliable data collection mechanism using local sink for wireless sensor networks

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Abstract In smart industrial applications, Wireless Sensor Networks (WSNs) contribute to the development of innovative systems that aim to improve the operational efficiency. However, node localization in the indoor environment… Click to show full abstract

Abstract In smart industrial applications, Wireless Sensor Networks (WSNs) contribute to the development of innovative systems that aim to improve the operational efficiency. However, node localization in the indoor environment still remains one of the main limitations of this technology. For WSNs, the use of a directional antenna is found to be a promising strategy that is primarily used to reduce interference and collision. This paper proposes a Reliable Data Collection Mechanism (RDCM) which uses six directional antennas to achieve an omnidirectional pattern of radiation. This transceiver module can be used as either omnidirectional or directional radiation pattern mode for node localization and accurate information gathering. Alternatively, the suggested localization technique uses Received Signal Strength (RSS), Angle of Arrival (AoA), and the x , y coordinate value derived from a single anchor node to locate the sensor node’s position. The information collection mechanism based on Local Sink (LS) is implemented which uses joint approaches including the node’s remaining energy, velocity, and connection time to select the LS. LS then transmits the collected data to Base Station (BS) using the modified geographic routing. In this routing, the LS considers a timer-contention mechanism to pick the next hop node in the direction of the BS. The simulation findings indicate that the RDCM has better packet delivery ratio, average energy consumption, and average end-to-end delay than VELCT, MBC, and ESWCA.

Keywords: mechanism; node localization; localization; sensor; collection mechanism

Journal Title: Journal of Industrial Information Integration
Year Published: 2021

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