GPE: A Grid-based Population Estimation Algorithm for Resource Inventory Applications over Sensor Networks

The growing advance in wireless communications and electronics makes the development of low-cost and low-power sensors possible. These sensors are usually small in size and are able to communicate with other sensors in short distance wirelessly. A sensor network consists of a number of sensors which cooperate with one another to accomplish some tasks. In this paper, we address the problem of resource inventory applications, which means a class of applications involving population calculation of a specific object type. To reduce energy consumption, each sensor only reports the number of the sensed objects to the server, and the server will estimate the number of the sensed objects according to the received reports of all sensors. To address this problem, we design in this paper a population estimation scheme, called algorithm GPE (standing for Grid-based Population Estimation), to estimate the numbers of the sensed objects. Several experiments are conducted to measure the performance of algorithm GPE. Experimental results show that algorithm GPE is able to obtain close approximations of the numbers of the sensed objects. In addition, experimental results also show that algorithm GPE is more scalable, and hence, is more suitable than prior schemes for practical use.