This paper presents an analysis and evaluation of the Hop Expansion Routing Algorithm, HERA, for delay-tolerant networks. HERA works by computing a reachability metric, akin to the metric used in PRoPHET routing, but with the major distinction that HERA expands the computation of the metric into the contributions of paths of different lengths, thus providing a more flexible metric that allows for the fine tuning of the effects of transitivity. In particular, HERA gives the flexibility to address the question of how many hops of transitivity a routing algorithm should take into account when making forwarding decisions. We present simulation results showing improvement of HERA over PRoPHET in terms of delivery ratio, number of replicas, and latency for several mobility scenarios, including real-life traces.

In most wireless networks, nodes have only limited local information about the state of the network, which includes connectivity and channel state information. With limited local information about the network, each node's knowledge is mismatched; therefore, they must make distributed decisions. In this paper, we pose the following question: If every node has network state information only about a small neighborhood, how and when should nodes choose to transmit? While link scheduling answers the above question for point-to-point physical layers that are designed for an interference-avoidance paradigm, we look for answers in cases when interference can be embraced by advanced PHY-layer design, as suggested by results in network information theory. To make progress on this challenging problem, we propose a constructive distributed algorithm that achieves rates higher than link scheduling based on interference avoidance, especially if each node knows more than one hop of network state information. We compare our new aggressive algorithm to a conservative algorithm we have presented in a 2013 conference paper. Both algorithms schedule subnetworks such that each subnetwork can employ advanced interference-embracing coding schemes to achieve higher rates. Our innovation is in the identification, selection, and scheduling of subnetworks, especially when subnetworks are larger than a single link.

In most wireless networks, nodes have only limited local information about the network state, which includes connectivity and channel state information. With limited local information about the network, each node's knowledge is mismatched, therefore they must make distributed decisions. In this paper, we pose the following question - if every node has network state information only about a small neighborhood, how and when should nodes choose to transmit? While scheduling answers the above question for point-to-point physical layers which are designed for an interference-avoidance paradigm, we look for answers in cases when interference can be embraced by advanced code design, as suggested by results in network information theory. To make progress on this challenging problem, we propose a distributed algorithm which achieves rates higher than interference-avoidance based link scheduling, especially if each node knows more than one hop of network state information.