The rapid progress of wireless communication and embedded micro-sensing MEMS technologies
has made wireless sensor networks possible. In light of storage in sensors, a sensor
network can be considered as a distributed database, in which one can conduct in-network data
processing. An important issue of wireless sensor networks is object tracking, which typically
involves two basic operations: update and query. This issue has been intensively studied in
other areas, such as cellular networks. However, the in-network processing characteristic of
sensor networks has posed new challenges to this issue. In this paper, we develop several
tree structures for in-network object tracking which take the physical topology of the sensor
network into consideration. The optimization process has two stages. The first stage tries to
reduce the location update cost based on a deviation-avoidance principle and a highest-weightfirst
principle. The second stage further adjusts the tree obtained in the first stage to reduce the
query cost. The way we model this problem allows us to analytically formulate the cost of object
tracking given the update and query rates of objects. Extensive simulations are conducted,
which show a significant improvement over existing solutions.
Relation:
IEEE Transactions on Mobile Computing 5(8) : 1044-1056
