How far have we come with Wireless sensor networks part2(Machine Learning)

<p>Abstract : Wireless sensor networks (WSNs) are self-organizing monitoring networks with a large number of randomly deployed microsensor nodes to collect various physical information to realize tasks such as intelligent perception, efficient control, and decision-making. However, WSN nodes are powered by batteries, so they will run out of energy after a certain time. This energy limitation will greatly constrain the network performance like network lifetime and energy efficiency. In this study, to prolong the network lifetime, we proposed a multi-hop routing protocol based on game theory and coverage optimization (MRP-GTCO). Briefly, in the stage of setup, two innovational strategies including a clustering game with penalty function and cluster head coverage set were designed to realize the uniformity of cluster head distribution and improve the rationality of cluster head election. In the data transmission stage, we first derived the applicable conditions theorem of inter-cluster multi-hop routing. Based on this, a novel multi-hop path selection algorithm related to residual energy and node degree was proposed to provide an energy-efficient data transmission path. The simulation results showed that the MRP-GTCO protocol can effectively reduce the network energy consumption and extend the network lifetime by 159.22%, 50.76%, and 16.46% compared with LGCA, RLEACH, and ECAGT protocol</p> <p>2. Energy-Efficient Routing Protocol Based on Multi-Threshold Segmentation in Wireless Sensors Networks for Precision Agriculture</p> <p><a href="https://medium.com/@monocosmo77/how-far-have-we-come-with-wireless-sensor-networks-part2-machine-learning-bb2f4c919432"><strong>Visit Now</strong></a></p>