HANDLING HEAVY-TAILED TRAFFIC IN QUEUEING NETWORKS USING MAX WEIGHT ALGORITHM

All scheduling systems consider the delay properties of one-hop and multi-hop networks with general interference constraints and multiple traffic streams with time-correlated arrivals. We first treat the case when arrivals are modulated by independent finite state Markov chains. To show that the well known maximal scheduling algorithm achieves average delay that grows at most logarithmically in the largest number of interferers at any link. Further, in the important special case when each Markov process has at most two states (such as ON/OFF sources), we prove that average delay is independent of the number of nodes and links in the network, and hence is order-optimal. The system has to analyze the delay performance of a multi-hop wireless network with a fixed route between each source-destination pair. To develop a new queue grouping technique to handle the complex correlations of the service process resulting from the multi-hop nature of the flows. For the tandem queue network, where the delayoptimal policy is known, the expected delay of the optimal policy numerically coincides with the lower bound. To achieve the time based as well as efficient packet based data transmission in multi-hop networks that the average delay of the back-pressure scheduling policy can be made close to the lower bound by using appropriate functions of queue length.