On the Feasibility of Linear Discrete-Time Systems of the Green Scheduling Problem

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Real-Time and Embedded Systems Lab (mLAB)
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green scheduling; feasibility;
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Li, Zheng
Huang, Pei-Chi
Mok, Aloysius K.

Peak power consumption of buildings in large facilities like hospitals and universities becomes a big issue because peak prices are much higher than normal rates. During a power demand surge an automated power controller of a building may need to schedule ON and OFF different environment actuators such as heaters and air quality control while maintaining the state variables such as temperature or air quality of any room within comfortable ranges. The green scheduling problem asks whether a scheduling policy is possible for a system and what is the necessary and sufficient condition for systems to be feasible. In this paper we study the feasibility of the green scheduling problem for HVAC(Heating, Ventilating, and Air Conditioning) systems which are approximated by a discrete-time model with constant increasing and decreasing rates of the state variables. We first investigate the systems consisting of two tasks and find the analytical form of the necessary and sufficient conditions for such systems to be feasible under certain assumptions. Then we present our algorithmic solution for general systems of more than 2 tasks. Given the increasing and decreasing rates of the tasks, our algorithm returns a subset of the state space such that the system is feasible if and only if the initial state is in this subset. With the knowledge of that subset, a scheduling policy can be computed on the fly as the system runs, with the flexibility to add power-saving, priority-based or fair sub-policies.

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Real-Time and Embedded Systems Lab (mLAB)
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Suggested Citation: Z. Li, P.C. Huang, A. Mok, T. Nghiem, M. Behl, G.J. Pappas, and R. Magharam. On the Feasibility of Linear Discrete-Time Systems of the Green Scheduling Problem. In Proceedings of the 32nd IEEE Real-Time Systems Symposium, Vienna, Austria, December 2011. ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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