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A Traffic Reduction Method for Centralized RSSI-Based Location Estimation in Wireless Sensor Networks

In a centralized localization scenario, the limited throughput of the central node constrains the possible number of target node locations that can be estimated simultaneously. To overcome this limitation, we propose a method which effectively decreases the traffic load associated with target node localization, and therefore increases the possible number of target node locations that can estimated simultaneously in a localization system based on received signal strength indicator (RSSI) and maximum likelihood estimation. Our proposed method utilizes a threshold which limits the amount of forwarded RSSI data to the central node. As the threshold is crucial to the method, we further propose a method to theoretically determine its value. We experimentally verified the proposed method in various environments and the experimental results revealed that the method can reduce the load by 32-64% without significantly affecting the estimation accuracy.