A service policy for real-time customers with (m,k) firm deadlines

The problem of scheduling multiple streams of realtime customers is addressed in this paper. The paper first introduces the notion of (m, k)-firm deadlines to better characterize the timing constraints of real-time streams. More specifically, a stream is said to have (m, k)-firm deadlines if at least m out of any k consecutive customers must meet their deadlines. Note that, the notion of (m, k)-firm deadlines is a generalization of firm and soft deadlines. In particular, m=k=1 characterizes a stream with firm deadlines. A large value for k with m/k equal to the maximum allowable loss percentage can be used to represent a stream with soft deadlines. A stream with (m, k)-firm deadlines will experience a dynamic failure if fewer than m out of any k consecutive customers meet their deadlines. The paper proposes a policy for scheduling N such streams on a single server to reduce the probability of dynamic failure. The basic idea of the proposed policy is to assign higher priorities to customers from streams which have had too many recent missed deadlines. The paper proposes a heuristic for assigning these priorities. The effectiveness of the approach is evaluated through simulation under various customer arrival and service patterns. The evaluation shows that by properly assigning the priorities one can substantially reduce the probability of dynamic failure.<>