Backpressure routing, in which packets are preferentially transmitted over links with high queue differentials, offers the promise of throughput-optimal operation for a wide range of communication networks. However, when traffic load is low, backpressure methods suffer from long delays. This is of particular concern in intermittent encounter-based mobile networks which are already delay-limited due to the sparse and highly dynamic network connectivity. While state of the art mechanisms for such networks have proposed the use of redundant transmissions to improve delay, they do not work well when traffic load is high. In this paper we propose backpressure with adaptive redundancy (BWAR), a novel hybrid approach that provides the best of both worlds. This approach is robust, distributed, and does not require any prior knowledge of network load conditions. We also present variants of BWAR that remove redundant packets via a timeout mechanism, and that improve energy use. These algorithms are evaluated by mathematical analysis and by simulations of real traces of taxis in Beijing, China. The simulations confirm that BWAR outperforms traditional backpressure at low load, while outperforming encounter-routing schemes (Spray and Wait and Spray and Focus) at high load.

Backpressure scheduling and routing, in which packets are preferentially transmitted over links with high queue differentials, offers the promise of throughput-optimal operation for a wide range of communication networks. However, when the traffic load is low, due to the corresponding low queue occupancy, backpressure scheduling/routing experiences long delays. This is particularly of concern in intermittent encounter-based mobile networks which are already delay-limited due to the sparse and highly dynamic network connectivity. While state of the art mechanisms for such networks have proposed the use of redundant transmissions to improve delay, they do not work well when the traffic load is high. We propose in this paper a novel hybrid approach that we refer to as backpressure with adaptive redundancy (BWAR), which provides the best of both worlds. This approach is highly robust and distributed and does not require any prior knowledge of network load conditions. We evaluate BWAR through both mathematical analysis and simulations based on a cell-partitioned model. We prove theoretically that BWAR does not perform worse than traditional backpressure in terms of the maximum throughput, while yielding a better delay bound. The simulations confirm that BWAR outperforms traditional backpressure at low load, while outperforming a state of the art encounter-routing scheme (Spray and Wait) at high load.