Scalable object-tracking through unattended techniques (SCOUT)

A scalable object location service can enable users to search for various objects in an environment where many small, networked devices are attached to objects. We investigate two hierarchical, self-configuring or unattended approaches for an efficient object location service. Each approach has its advantages and disadvantages based on the anticipated load. The first approach, SCOUT-AGG, is based on aggregation of object names. The second approach, SCOUT-MAP, is based on indirection, where information about an object is stored at the locator sensor for the object. The relative efficiency of SCOUT-AGG and SCOUT-MAP can be characterized by the query to mobility, update rate of the system. SCOUT-AGG performs better for low query to update rate but its performance deteriorates in general relative to SCOUT-MAP as the queries to update rate increases. The rate of performance deterioration depends on query specificity (i.e., queries for a specific object or for any object of a particular type). SCOUT-MAP generally exhibits better load balancing than SCOUT-AGG for various scenarios. We support the above results through simple analytical modeling and simulation