This paper proposes COPE, a new architecture for wireless mesh networks. In addition to forwarding packets, routers mix (i.e., code) packets from different sources to increase the information content of each transmission. We show that intelligently mixing packets increases network throughput. Our design is rooted in the theory of network coding. Prior work on network coding is mainly theoretical and focuses on multicast traffic. This paper aims to bridge theory with practice; it addresses the common case of unicast traffic, dynamic and potentially bursty flows, and practical issues facing the integration of network coding in the current network stack. We evaluate our design on a 20-node wireless network, and discuss the results of the first testbed deployment of wireless network coding. The results show that COPE largely increases network throughput. The gains vary from a few percent to several folds depending on the traffic pattern, congestion level, and transport protocol.

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We present a capacity-approaching coding scheme for unicast or multicast over lossy packet networks. In the scheme, all nodes perform coding, but do not wait for a full block of packets to be received before sending out coded packets. Rather, whenever they have a transmission opportunity, they form coded packets with random linear combinations of previously received packets. All coding and decoding operations in the scheme have polynomial complexity. Our analysis of the scheme shows that it is not only capacity-approaching, but that the propagation of packets carrying “innovative ” information follows that of a queueing network where every node acts as a stable M/M/1 queue. We consider networks with both lossy point-to-point and broadcast links, allowing us to model both wireline and wireless packet networks. 1

We consider applying network coding in settings where there is a cost associated with network use.

Abstract — A recent approach, COPE [10], for improving the throughput of unicast traffic in wireless multi-hop networks exploits the broadcast nature of the wireless medium through opportunistic network coding. In this paper, we analyze throughput improvements obtained by COPE-type network coding in wireless networks from a theoretical perspective. We make two key contributions. First, we obtain a theoretical formulation for computing the throughput of network coding on any wireless network topology and any pattern of concurrent unicast traffic sessions. Second, we advocate that routing be made aware of network coding opportunities rather than, as in COPE, being oblivious to it. More importantly, our work studies the tradeoff between routing flows “close to each other ” for utilizing coding opportunities and “away from each other ” for avoiding wireless interference. Our theoretical formulation provides a method for computing source-destination routes and utilizing the best coding opportunities from available ones so as to maximize the throughput. We handle scheduling of broadcast transmissions subject to wireless transmit/receive diversity and link interference in our optimization framework. Using our formulations, we compare the performance of traditional unicast routing and network coding with coding-oblivious and coding-aware routing on a variety of mesh network topologies, including some derived from contemporary mesh network testbeds. Our evaluations show that a route selection strategy that is aware of network coding opportunities leads to higher end-to-end throughput when compared to coding-oblivious routing strategies. I.

We show that network coding allows to realize energy savings in a wireless ad-hoc network, when each node of the network is a source that wants to transmit information to all other nodes. Energy efficiency directly affects battery life and thus is a critical design parameter for wireless networks. We propose an implementable method for performing network coding in such a setting. We analyze theoretical cases in detail, and use the insights gained to propose a practical, fully distributed method for realistic wireless ad-hoc scenarios. We address practical issues such as setting the forwarding factor, managing generations, and impact of transmission range. We use theoretical analysis and packet level simulation.

Abstract — We consider the problem of establishing efficient unicast connections over wireless packet networks. We show how network coding, combined with distributed flow optimization, gives a practicable approach that promises to significantly outperform the present approach of end-to-end or link-bylink retransmission combined with route optimization, where performance may be measured in terms of energy consumption, congestion, or any other cost that increases with the number of transmissions made by each node. We present a specific coding scheme and specific distributed flow optimization techniques that may be used to form the basis of a protocol. I.

Abstract — This paper analyzes the gains in delay performance resulting from network coding. We consider a model of file transmission to multiple receivers from a single base station. Using this model, we show that gains in delay performance from network coding with or without channel side information can be substantial compared to conventional scheduling methods for downlink transmission. I.

Abstract — Energy efficiency, i.e., the amount of battery energy consumed to transmit bits across a wireless link, is a critical design parameter for wireless ad-hoc networks. We examine the problem of broadcasting information to all nodes in an ad-hoc network, when a large percentage of the nodes act as sources. We theoretically quantify the energy savings that network coding can offer for the cases of two regular topologies. We then propose low-complexity distributed algorithms, and demonstrate through simulation that for random networks, network coding can in fact offer significant benefits in terms of energy consumption. I.

The transmission of information within a data network is constrained by network topology and link capacities. In this paper, we study the fundamental upper bound of information multicast rates with these constraints, given the unique replicable and encodable property of information flows. Based on recent information theory advances in coded multicast rates, we are able to formulate the maximum multicast rate problem as a linear network optimization problem, assuming the general undirected network model. We then proceed to apply Lagrangian relaxation techniques to obtain (1) a necessary and sufficient condition for multicast rate feasibility, and (2) a subgradient solution for computing the maximum rate and the optimal routing strategy to achieve it. The condition we give is a generalization of the well-known conditions for the unicast and broadcast cases. Our subgradient solution takes advantage of the underlying network flow structure of the problem, and therefore outperforms general linear programming solving techniques. It also admits a natural intuitive interpretation, and is amenable to fully distributed implementations.