Integrated QoS-aware resource management and scheduling with multi-resource constraints

Authors:
Sourav Ghosh;Ragunathan Rajkumar;Jeffery Hansen;John Lehoczky
Affiliations:
Department of Electrical and Computer Engineering, Carnegie Mellon University, USA;Department of Electrical and Computer Engineering, Carnegie Mellon University, USA;Institute for Complex Engineered Systems, Carnegie Mellon University, USA;Department of Statistics, Carnegie Mellon University, USA
Venue:
Real-Time Systems
Year:
2006

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Abstract

In dynamic real-time systems such as sensor networks, mobile ad hoc networking and autonomous systems, the mapping between level of service and resource requirements is often not fixed. Instead, the mapping depends on a combination of level of service and outside environmental factors over which the application has no direct control. An example of an application where environmental factors play a significant role is radar tracking. In radar systems, resources must be shared by a set of radar tasks including tracking, searching and target confirmation tasks. 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. The QoS manager in a radar system must be adaptive, responding to dynamic changes in the environment by efficiently reallocating resource to maintain an acceptable level of service. In this paper, we present an integrated QoS optimization and dwell scheduling scheme for a radar tracking application. QoS optimization is performed using the Q-RAM (Baugh, 1973, ghosh-et al.,2004a approach. Heuristics are used to achieve a two order magnitude of reduction in optimization time over the basic Q-RAM approach allowing QoS optimization and scheduling of a 100 task radar problem to be performed in as little as 700 ms with only a 0.1% QoS penality over Q-RAM alone.