Efficient Strategies for Signal Aggregation in Low-Power Wireless Sensor Networks With Discrete Transmission Ranges

Sensors with different transmission ranges are preferred for future-ready low-power wireless sensor networks because of their functional advantages. However, different transmission ranges introduce connectivity constraints that affect the signal aggregation process. In this letter, we address the sensor signal aggregation problem in such networks and propose solutions. We introduce a mathematical framework that captures the connectivity restrictions and propose an integer linear program for small-scale networks and an approximation technique for large-scale networks. The performance of the proposed method is evaluated under compression techniques based on compressed sensing.