  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 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.
