On the power of cooperation: Can a little help a lot?

In this paper, we propose a new cooperation model for discrete memoryless multiple access channels. Unlike in prior cooperation models (e.g., conferencing encoders), where the transmitters cooperate directly, in this model the transmitters cooperate through a larger network. We show that under this indirect cooperation model, there exist channels for which the increase in sum-capacity resulting from cooperation is significantly larger than the rate shared by the transmitters to establish the cooperation. This result contrasts both with results on the benefit of cooperation under prior models and results in the network coding literature, where attempts to find examples in which similar small network modifications yield large capacity benefits have to date been unsuccessful

Information exchange for routing protocols

Abstract—Distance vector routing is a classic distributed algo-rithm for obtaining routing tables in a communication network. The algorithm relies on message exchange between neighbor routers. This paper studies the amount of routing data that needs to be stored and exchanged. On a static network, a variation of the algorithm that exchanges routing trees or pseudotrees is slightly more information theoretically efficient than a tradi-tional implementation that exchanges tables. Knowledge of an underlying graph model and proper estimation of parameters allow more efficient coding schemes, including schemes related to Slepian-Wolf coding. Further improvements can be obtained on a dynamic network

A Local Perspective on the Edge Removal Problem

The edge removal problem studies the loss in network coding rates that results when a network communication edge is removed from a given network. It is known, for example, that in networks restricted to linear coding schemes and networks restricted to Abelian group codes, removing an edge e^∗ with capacity R_(e^∗) reduces the achievable rate on each source by no more than R_(e^∗). In this work, we seek to uncover larger families of encoding functions for which the edge removal statement holds. We take a local perspective: instead of requiring that all network encoding functions satisfy certain restrictions (e.g., linearity), we limit only the function carried on the removed edge e^∗. Our central results give sufficient conditions on the function carried by edge e^∗ in the code used to achieve a particular rate vector under which we can demonstrate the achievability of a related rate vector once e^∗ is removed