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We consider unreliable multi-hop networks serving multiple flows in whichpackets not delivered to their destination nodes by their deadlines aredropped. We address the design of policies for routing and scheduling packetsthat optimize any specified weighted average of the throughputs of the flows.We provide a new approach which directly yields an optimal distributedscheduling policy that attains any desired maximal timely-throughput vectorunder average-power constraints on the nodes. It pursues a novel intrinsicallystochastic decomposition of the Lagrangian of the constrained network-wide MDPrather than of the fluid model. All decisions regarding a packet's transmissionscheduling, transmit power level, and routing, are completely distributed,based solely on the age of the packet, not requiring any knowledge of networkstate or queue lengths at any of the nodes. Global coordination is achievedthrough a tractably computable "price" for transmission energy. This price isdifferent from that used to derive the backpressure policy where pricecorresponds to queue lengths. A quantifiably near-optimal policy is provided ifnodes have peak-power constraints.

Throughput Optimal Decentralized Scheduling of Multi-Hop Networks with End-to-End Deadline Constraints: Unreliable Links