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Efficient Location Tracking Using Sensor Networks
H. T. Kung and D. Vlah
WCNC 2003
Speaker : Chi-Chih Wu
Outline Introduction STUN: Scalable Tracking Using
Networked Sensors DAB: Drain-and-Balance Method
for Constructing Message-Pruning Hierarchies
Evaluation Conclusions
Introduction The method will need to handle a large nu
mber of moving objects at once Tracking consists of detecting and monitori
ng locations of real-world objects Air traffic control Fleet tracking
We focus on improving the energy efficiency of such schemes
Introduction Example :
A downtown area of a city may consists of a street grid and buildings that prevent pedestrians from moving around arbitrarily. Further, it is uncommon for a city-dweller to roam around uniformly at random; a more likely trajectory consists of spending time within some local region, and occasionally making long-range transitions
Introduction Example :
We consider a large-scale disaster recovery or battlefield scenario. It may be unusual for every participant to move uniformly across the entire field; rather, due to organizational structure, the movement may be constrained so that there is little traffic between different units, while movement within units is quite high
Introduction Example :
let us examine a large natural habitat, such as a national park, that scientists may wish to monitor. Once more, it is unlikely to observe animals moving around uniformly. The animals may be living in herds; different types of animals may avoid trespassing upon each others’ territory; or there may be various natural obstacles like hills or undergrowth that restrict movement in certain regions, etc.
STUN: Scalable Tracking Using Networked Sensors The STUN Design
the objects we wish to track A natural limit on their speed
Our method uses a hierarchy to connect the sensors
The leaves are sensors the querying point as the root the other nodes are communication nodes
Conclusions This paper made two main contributi
ons STUN (Scalable Tracking using Networke
d Sensors) the DAB (drain-and-balance) method for
building STUN hierarchiesthat take advantage of information about the mobility patterns of the objects being tracked