A distributed scheme for achieving energy-delay tradeoffs with multiple service classes over a dynamically varying network

We consider a dynamical probabilistic traffic model for the number of users transmitting at any time. This model captures both user mobility and traffic burstiness. Moreover, we assume no centralized controller, such as a scheduler, is available. When multiple users transmit simultaneously, multiple-access interference (MAI) affects throughput considerably. Most queue control schemes assume individual users know the states of their own queues (local queue information) along with the states of other users queues (shared queue information) and address issues of scheduling; but this sharing of information may be onerous in a practical system. While shared queue information has recently been shown (Me/spl acute/dard et al., 2004) not to affect the capacity of such systems, it has a considerable impact on delay. We introduce a scheme, where for each user, a bit of shared queue information specifies whether its queue length is above or below a threshold. Our scheme relies on two different service classes implemented through a superposition coding scheme (first proposed with Me/spl acute/dard and Goldsmith, 1999, further studied and expanded with Me/spl acute/dard et al., 2004). The first class experiences no delay due to multiple-access interference, while the second class requires retransmissions when such an event occurs. We show how our scheme affords an energy-delay tradeoff. Moreover, when configured properly, our scheme can attain boundary points of the region corresponding to minimum energy with no shared queue information for zero delay along with minimum energy subject to system stability. We derive bounds on the performance of the multiple-access system using our proposed scheme by introducing Lyapunov function bounds in a manner similar to Bertsimas et al., 2001.