This study considers a wireless sensor network (WSN) designed to track specified objects of interest such as bird-calls, insect-images, and so forth. An assumption is made that the sensors in the WSN are capable of analyzing and identifying detected objects and are pre-loaded with the features of the tracked objects before they are deployed. The features associated with the tracked objects are referred to as "model tuples". When a sensor subsequently detects an object, it extract features from the detected object and then compares it with the tuples stored in its memory in order to determine whether or not the detected object is the tracked object. Since the sensors have only limited memory and storage space, it is impossible to store all the tuples on a single sensor. Furthermore, the sensors are battery operated, and thus the stored tuples are irretrievably lost once the sensor's energy resources have been consumed. As a result, the network no longer has a complete knowledge of all the tracked information. Accordingly, the present study proposes four tuple dispatching schemes for distributing the tracked information amongst the sensors in such a way as to mitigate the effects of sensor energy depletion, namely sequential dispatching, sequential dispatching with overlap, fixed distance dispatching, and balanced incomplete block dispatching. In addition, an efficient diversity-driven selective forwarding scheme is proposed to resolve the problem where the detected object fails to match the tuples held at the local sensor. In the approach, the local sensor applies the correlation between the sensor identifier and the indexes of the tuples stored at the various sensors to deliver the feature of the object along the paths with the highest diversity. The simulation presents a series of experimental results to benchmark the performance of the proposed forwarding approach for each of the dispatching schemes against that of a blind flooding approach.
All Science Journal Classification (ASJC) codes
- Hardware and Architecture