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In this paper, we consider the problem of scheduling real-time traffic in wireless networks under a conflict-graph interference model and single-hop traffic. The objective is to guarantee that at least a certain fraction of packets of each link are delivered within their deadlines, which is referred to as delivery ratio. This problem has been studied before under restrictive frame-based traffic models, or greedy maximal scheduling schemes like LDF (Largest-Deficit First) that can lead to poor delivery ratio for general traffic patterns. In this paper, we pursue a different approach through randomization over the choice of maximal links that can transmit at each time. We design randomized policies in collocated networks, multi-partite networks, and general networks, that can achieve delivery ratios much higher than what is achievable by LDF. Further, our results apply to any traffic (arrival and deadline) process that evolves as an unknown positive recurrent Markov chain. Hence, this work is an improvement with respect to both efficiency and traffic assumptions compared to the past work. We further present extensive simulation results over various traffic patterns and interference graphs to illustrate the gains of our randomized policies over LDF variants. [ABSTRACT FROM AUTHOR]

For a wireless network with n nodes distributed in an area A, and with n source-destination pairs communicating with each other at some common rate, the hierarchical cooperation scheme proposed in (Ozgur, Leveque, and Tse, 2007) is analyzed and optimized by choosing the number of hierarchical stages and the corresponding cluster sizes that maximize the total throughput. It turns out that increasing the number of stages does not necessarily improve the throughput, and the closed-form solutions for the optimization problem can be explicitly obtained. Based on the expression of the maximum achievable throughput, it is found that the hierarchical scheme achieves a scaling with the exponent depending on n. In addition, to apply the hierarchical cooperation scheme to random networks, a clustering algorithm is developed, which divides the whole network into quadrilateral clusters, each with exactly the number of nodes required. [ABSTRACT FROM AUTHOR]