Polar Coordinate-Based Energy-Efficient-Chain Routing in Wireless Sensor Networks Using Random Projection

Random projection based on compressed sensing can reduce the amount of data transmitted in a wireless sensor network (WSN), and efficient routing can reduce the network traffic. Thus, this paper presents a Random projection-Polar coordinate-Chain routing (RPC) method. The method uses polar coordinates to locate nodes, establishes a chain structure to form a route, and applies random projection to achieve the compressed data collection. In a WSN, the sink is the center of the data collection. With the sink as the pole, the polar coordinates can be used to determine the orientation of each node relative to the sink so that nodes can be searched under certain conditions. By adopting the chain topological structure, the establishment of the chain through the greedy algorithm reduces the energy consumption and complexity. Based on the comparative analysis, a four-quadrant chain routing method combining the polar radius and polar angle is proposed for smaller networks. For large-scale networks, a routing algorithm combining the sector and inner circle is proposed. Then, according to the random projection theory, the weighted sum of the random projections of each row of the corresponding measurement matrix in each partition is transmitted to the sink. The sink has collected all measurements of each partition to complete the signal reconstruction. In this method, the route is formed by searching in the zones according to the polar radius and the polar angle, which avoids the roundabout route between distant nodes and reduces the energy consumption of the network. By comparing the RPC method with other related methods and the simulation experiments for different types of routing, the proposed method is proved to be time and energy efficient.