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This paper studies the problem of optimal forwarding for reliable and energy-efficient real-time communication over lossy networks. The authors impose a strict per-packet latency bound and develop forwarding policies that maximize the probability that the packet is delivered within the specified deadline minus a transmission energy cost. A solution to this problem allows to characterize the set of achievable latency-reliability pairs and to trace out the Pareto frontier between achievable deadline-constrained reliability and transmission energy cost. They develop dynamic programming-based solutions under a finite-state Markov channel model. Particular instances with Bernoulli and Gilbert-Elliot loss models that admit numerically efficient solutions are discussed and their results are demonstrated on several examples.
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