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Despite the rich literature on scheduling algorithms for wireless networks,algorithms that can provide deadline guarantees on packet delivery for generaltraffic and interference models are very limited. In this paper, we study theproblem of scheduling real-time traffic under a conflict-graph interferencemodel with unreliable links due to channel fading. Packets that are notsuccessfully delivered within their deadlines are of no value. We considertraffic (packet arrival and deadline) and fading (link reliability) processesthat evolve as an unknown finite-state Markov chain. The performance metric isefficiency ratio which is the fraction of packets of each link which aredelivered within their deadlines compared to that under the optimal (unknown)policy. We first show a conversion result that shows classical non-real-timescheduling algorithms can be ported to the real-time setting and yield aconstant efficiency ratio, in particular, Max-Weight Scheduling (MWS) yields anefficiency ratio of 1/2. We then propose randomized algorithms that achieveefficiency ratios strictly higher than 1/2, by carefully randomizing over themaximal schedules. We further propose low-complexity and myopic distributedrandomized algorithms, and characterize their efficiency ratio. Simulationresults are presented that verify that randomized algorithms outperformclassical algorithms such as MWS and GMS.

Randomized Scheduling of Real-Time Traffic in Wireless Networks Over Fading Channels