We consider wireless networks in which multiple paths are available between each source and destination. We allow each source to split traffic among all of its available paths, and ask the question: how do we attain the lowest possible number of transmissions to support a given traffic matrix? Traffic bound in opposite directions over two wireless hops can utilize the reverse carpooling'' advantage of network coding in order to decrease the number of transmissions used. We call such coded hops as hyper-links''. With the reverse carpooling technique longer paths might be cheaper than shorter ones. However, there is a prisoners dilemma type situation among sources -- the network coding advantage is realized only if there is traffic in both directions of a shared path. We develop a two-level distributed control scheme that decouples user choices from each other by declaring a hyper-link capacity, allowing sources to split their traffic selfishly in a distributed fashion, and then changing the hyper-link capacity based on user actions. We show that such a controller is stable, and verify our analytical insights by simulation.
Network coding research was initiated by a seminal paper by Ahlswede @cite_7 and since then attracted a significant interest from the research community. Many initial works on the network coding technique focused on establishing connections between a fixed source and a set of terminal nodes. Li @cite_4 showed that the maximum rate of a multicast connection is equal to the minimum capacity of a cut that separates the source and any terminal. In a subsequent work, Koetter and M ' e dard @cite_2 developed an algebraic framework for network coding and investigated linear network codes for directed graphs with cycles. Network coding technique for wireless networks has been considered by Katabi @cite_1 . The proposed architecture, referred to as COPE, contains a special network coding layer between the IP and MAC layers. In @cite_13 Chachulski proposed an opportunistic routing protocol, referred to as MORE, that randomly mixes packets that belong to the same flow before forwarding them to the next hop. Sagduyu and Ephremides @cite_10 focused on the applications of network coding in simple path topologies (referred to in @cite_10 as networks) and formulate a related cross-layer optimization problems.
@cite_4 @cite_7 @cite_10 @cite_1 @cite_2 @cite_13
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Consider a communication network in which certain source nodes multicast information to other nodes on the network in the multihop fashion where every node can pass on any of its received data to others. We are interested in how fast each node can receive the complete information, or equivalently, what the information rate arriving at each node is. Allowing a node to encode its received data before passing it on, the question involves optimization of the multicast mechanisms at the nodes. Among the simplest coding schemes is linear coding, which regards a block of data as a vector over a certain base field and allows a node to apply a linear transformation to a vector before passing it on. We formulate this multicast problem and prove that linear coding suffices to achieve the optimum, which is the max-flow from the source to each receiving node. We introduce a new class of problems called network information flow which is inspired by computer network applications. Consider a point-to-point communication network on which a number of information sources are to be multicast to certain sets of destinations. We assume that the information sources are mutually independent. The problem is to characterize the admissible coding rate region. This model subsumes all previously studied models along the same line. We study the problem with one information source, and we have obtained a simple characterization of the admissible coding rate region. Our result can be regarded as the max-flow min-cut theorem for network information flow. Contrary to one's intuition, our work reveals that it is in general not optimal to regard the information to be multicast as a "fluid" which can simply be routed or replicated. Rather, by employing coding at the nodes, which we refer to as network coding, bandwidth can in general be saved. This finding may have significant impact on future design of switching systems. We take a new look at the issue of network capacity. It is shown that network coding is an essential ingredient in achieving the capacity of a network. Building on recent work by (see Proc. 2001 IEEE Int. Symp. Information Theory, p.102), who examined the network capacity of multicast networks, we extend the network coding framework to arbitrary networks and robust networking. For networks which are restricted to using linear network codes, we find necessary and sufficient conditions for the feasibility of any given set of connections over a given network. We also consider the problem of network recovery for nonergodic link failures. For the multicast setup we prove that there exist coding strategies that provide maximally robust networks and that do not require adaptation of the network interior to the failure pattern in question. The results are derived for both delay-free networks and networks with delays. Opportunistic routing is a recent technique that achieves high throughput in the face of lossy wireless links. The current opportunistic routing protocol, ExOR, ties the MAC with routing, imposing a strict schedule on routers' access to the medium. Although the scheduler delivers opportunistic gains, it misses some of the inherent features of the 802.11 MAC. For example, it prevents spatial reuse and thus may underutilize the wireless medium. It also eliminates the layering abstraction, making the protocol less amenable to extensions to alternate traffic types such as multicast. This paper presents MORE, a MAC-independent opportunistic routing protocol. MORE randomly mixes packets before forwarding them. This randomness ensures that routers that hear the same transmission do not forward the same packets. Thus, MORE needs no special scheduler to coordinate routers and can run directly on top of 802.11. Experimental results from a 20-node wireless testbed show that MORE's median unicast throughput is 22 higher than ExOR, and the gains rise to 45 over ExOR when there is a chance of spatial reuse. For multicast, MORE's gains increase with the number of destinations, and are 35-200 greater than ExOR.