%0 Journal Article
%T LIFO-Backpressure Achieves Near Optimal Utility-Delay Tradeoff
%A Longbo Huang
%A Scott Moeller
%A Michael J. Neely
%A Bhaskar Krishnamachari
%J Mathematics
%D 2010
%I arXiv
%X There has been considerable recent work developing a new stochastic network utility maximization framework using Backpressure algorithms, also known as MaxWeight. A key open problem has been the development of utility-optimal algorithms that are also delay efficient. In this paper, we show that the Backpressure algorithm, when combined with the LIFO queueing discipline (called LIFO-Backpressure), is able to achieve a utility that is within $O(1/V)$ of the optimal value, while maintaining an average delay of $O([\log(V)]^2)$ for all but a tiny fraction of the network traffic. This result holds for general stochastic network optimization problems and general Markovian dynamics. Remarkably, the performance of LIFO-Backpressure can be achieved by simply changing the queueing discipline; it requires no other modifications of the original Backpressure algorithm. We validate the results through empirical measurements from a sensor network testbed, which show good match between theory and practice.
%U http://arxiv.org/abs/1008.4895v2