Wireless Inter-Session Network Coding - An Approach Using Virtual Multicasts

This paper addresses the problem of inter-session network coding to maximize throughput for multiple communication sessions in wireless networks. We introduce virtual multicast connections which can extract packets from original sessions and code them together. Random linear network codes can be used for these virtual multicasts. The problem can be stated as a flow-based convex optimization problem with side constraints. The proposed formulation provides a rate region which is at least as large as the region without inter-session network coding. We show the benefits of our technique for several scenarios by means of simulation.United States. Defense Advanced Research Projects Agency (Subcontract 18870740-37362-C

An Optimal Adaptive Network Coding Scheme for Minimizing Decoding Delay in Broadcast Erasure Channels

We are concerned with designing feedback-based adaptive network coding schemes with the aim of minimizing decoding delay in each transmission in packet-based erasure networks. We study systems where each packet brings new information to the destination regardless of its order and require the packets to be instantaneously decodable. We first formulate the decoding delay minimization problem as an integer linear program and then propose efficient algorithms for finding its optimal solution(s). We show that our problem formulation is applicable to memoryless erasures as well as Gilbert-Elliott erasures with memory. We then propose a number of heuristic algorithms with worst case linear execution complexity that can be used when an optimal solution cannot be found in a reasonable time. We verify the delay and speed performance of our techniques through numerical analysis. This analysis reveals that by taking channel memory into account in network coding decisions, one can considerably reduce decoding delays.</p

An Optimal Adaptive Network Coding Scheme for Minimizing Decoding Delay in Broadcast Erasure Channels

We are concerned with designing feedback-based adaptive network coding schemes with the aim of minimizing decoding delay in each transmission in packet-based erasure networks. We study systems where each packet brings new information to the destination regardless of its order and require the packets to be instantaneously decodable. We first formulate the decoding delay minimization problem as an integer linear program and then propose efficient algorithms for finding its optimal solution(s). We show that our problem formulation is applicable to memoryless erasures as well as Gilbert-Elliott erasures with memory. We then propose a number of heuristic algorithms with worst case linear execution complexity that can be used when an optimal solution cannot be found in a reasonable time. We verify the delay and speed performance of our techniques through numerical analysis. This analysis reveals that by taking channel memory into account in network coding decisions, one can considerably reduce decoding delays

Adaptive Network Coding for Broadcast Channels

We consider the throughput-delay tradeoff in network coded transmission over erasure broadcast channels. Interested in minimizing decoding delay, we formulate the problem of instantly decodable network coding as an integer linear program and propose algorithms to solve it heuristically. In particular, we investigate channels with memory and propose algorithms that can exploit channel erasure dependence to increase throughput and decrease delay

An Optimal Adaptive Network Coding Scheme for Minimizing Decoding Delay in Broadcast Erasure Channels

We are concerned with designing feedback-based adaptive network coding schemes with the aim of minimizing decoding delay in each transmission in packet-based erasure networks. We study systems where each packet brings new information to the destination regardless of its order and require the packets to be instantaneously decodable. We first formulate the decoding delay minimization problem as an integer linear program and then propose efficient algorithms for finding its optimal solution(s). We show that our problem formulation is applicable to memoryless erasures as well as Gilbert-Elliott erasures with memory. We then propose a number of heuristic algorithms with worst case linear execution complexity that can be used when an optimal solution cannot be found in a reasonable time. We verify the delay and speed performance of our techniques through numerical analysis. This analysis reveals that by taking channel memory into account in network coding decisions, one can considerably reduce decoding delays

Asynchronous Network Coded Multicast

We consider the problem of setting up a multicast connection of minimum cost using network coding. It is well-known that this can be posed in the form of a convex program. Our contribution is an asynchronous algorithm for solving the optimization problem, in analogy to the well-known distributed asynchronous Bellman-Ford algorithm for routing. Furthermore, we provide extensive simulation results showing fast convergence despite the lack of any central clock in the network and robustness with respect to link- or node failures

Joint scheduling and instantaneously decodable network coding

We consider a wireless multi-hop network and design an algorithm for jointly optimal scheduling of packet transmissions and network coding. We consider network coding across different users, however with the restriction that packets have to be decoded after one hop. We compute the stability region of this scheme and propose an online algorithm that stabilizes every arrival rate vector within the stability region. The online algorithm requires computation of stable sets in an appropriately defined conflict graph. We show by means of simulations that this inherently hard problem is tractable for some instances and that network coding extends the stability region over routing and leads, on average, to a smaller backlog.United States. Defense Advanced Research Projects Agency (Subcontract # 18870740-37362- C)United States. Space and Naval Warfare Systems Command (Contract No. N66001-06-C-2020)Seventh Framework Programme (European Commission). Network of Excellence in Wireless Communications (Contract no. 216715

Scheduling for network coded multicast: a distributed approach

We address the problem of maximizing the throughput for network coded multicast traffic in a wireless network in the bandwidth limited regime. For the joint scheduling and subgraph selection problem, we model valid network configurations as stable sets in an appropriately defined conflict graph. The problem formulation separates the combinatorial difficulty of scheduling from the arising optimization problem and facilitates the application of less complex scheduling policies. Lagrangian relaxation gives rise to two subproblems, a multiple shortest path, and a maximum weight stable set (MWSS) problem. For the latter we propose a greedy approach which can be computed in a distributed fashion, thus yielding a fully decentralized algorithm. Simulation results show that our technique is nearly optimal and outperforms heuristics such as orthogonal scheduling by a large margin.United States. Defense Advanced Research Projects Agency (DARPA) (subcontract No. 18870740-37362-C)European Union. NEWCOM+