Improved localisation algorithm based on Markov chain Monte Carlo-Metropolis Hastings for wireless sensor networks
by Yucai Zhou; Munyabugingo Charles; Tong Wang; Min Song
International Journal of Sensor Networks (IJSNET), Vol. 33, No. 3, 2020

Abstract: Accurate and low-cost sensor localisation is the key requirement for deploying wireless sensor networks (WSNs) and the internet of things (IoT) in various applications. Researchers are trying their best to find a way to localise mobile nodes in WSNs. To solve the problem of the moment outside the anchoring range or positioning errors, an improved distance vector hop (DV-Hop) location algorithm based on the Markov chain Monte Carlo Metropolitan Hastings algorithm (MMDV-Hop) is proposed. According to the receiving and transmitting power of received signal strength indication (RSSI), anchor information is taken into account when calculating the distance between unknown nodes and anchor nodes. From the different percentages of anchor nodes and unknown nodes, node density, and node connectivity, MMDVHop shows better position error than traditional algorithms.

Online publication date: Fri, 17-Jul-2020

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