Adaptive QoS Optimizations with applications to Radar Tracking ?

In many applications such as sensor networks, mobile ad hoc net- working and autonomous systems, the relationship between level of service and resource requirements is not fixed. Environmental factors outside the direct con- trol of the system affect this relationship and may also affect the perceived utility of a given level of service. Radar tracking provides a good example. In radar systems, a fixed amount of radar bandwidth and computing resources must be apportioned among multiple tasks, each of which corresponds to a target. In ad- dition, environmental factors such as noise, heating constraints of the radar and the speed, distance and maneuverability of tracked targets dynamically affect the mapping between the level of service and resource requirements as well as the mapping between the level of service and the user-perceived utility. To be able to handle these tasks, a QoS manager must be adaptive, reacting to dynamic changes in the environment, adjusting the level of service and reallocating resources effi- ciently. In this paper, we present a dynamic QoS optimization scheme for a radar tracking application based on Q-RAM (1, 2). Our scheme is able to deal with a large number of operating points in real-time with very acceptable losses in total utility accrued. This result is made possible by an efficient heuristic to compute the concave majorant of a multi-variate function, and an off-line storage-efficient discretization of the static aspects of the problem space. These two contributions will also be useful in many dynamic QoS-driven applications beyond radar track- ing.