528 research outputs found

    On wireless network scheduling with intersession network coding

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    Abstract—Cross-layer optimization including congestion con-trol, routing, and scheduling has shown dramatic throughput improvement over layered designs for wireless networks. In parallel, the paradigm-shifting network coding has empirically demonstrated substantial throughput improvement when coding operations are permitted at intermediate nodes and packets from different sessions are mixed. Designing network codes and the associated flow in network coding presents new challenges for cross-layer optimization for wireless multi-hop networks. This work shows that with a new flow-based characterization of pairwise intersession network coding, a joint optimal scheduling and rate-control algorithm can be implemented distributively. Optimal scheduling is computationally expensive to achieve even in a purely routing-based (without network coding) paradigm, let alone with network coding. Thus, in this paper, the impact of imperfect scheduling is studied, which shows that pairwise intersession network coding can improve the throughput of routing-based solutions regardless of whether perfect/imperfect scheduling is used. Both the deterministic and stochastic packet arrivals and departures are considered. This work shows for the first time a striking resemblance between pairwise intersession network coding and routing, and thus advocates extensions of routing-based wisdoms to their network coding counterpart. Index Terms—Network coding, pairwise intersession network coding, imperfect scheduling, cross-layer optimization, congestion control. I

    Network coding for wireless communication networks

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    This special issue includes a collection of 19 outstanding research papers which cover a diversity of topics on the application of network coding in wireless communication networks.published_or_final_versio

    Joint Congestion Control and Scheduling in Wireless Networks with Network Coding

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    Decoding Delay Minimization in Inter-Session Network Coding

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    Intra-session network coding has been shown to offer significant gains in terms of achievable throughput and delay in settings where one source multicasts data to several clients. In this paper, we consider a more general scenario where multiple sources transmit data to sets of clients over a wireline overlay network. We propose a novel framework for efficient rate allocation in networks where intermediate network nodes have the opportunity to combine packets from different sources using randomized network coding. We formulate the problem as the minimization of the average decoding delay in the client population and solve it with a gradient-based stochastic algorithm. Our optimized inter-session network coding solution is evaluated in different network topologies and is compared with basic intra-session network coding solutions. Our results show the benefits of proper coding decisions and effective rate allocation for lowering the decoding delay when the network is used by concurrent multicast sessions

    Content Distribution by Multiple Multicast Trees and Intersession Cooperation: Optimal Algorithms and Approximations

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    In traditional massive content distribution with multiple sessions, the sessions form separate overlay networks and operate independently, where some sessions may suffer from insufficient resources even though other sessions have excessive resources. To cope with this problem, we consider the universal swarming approach, which allows multiple sessions to cooperate with each other. We formulate the problem of finding the optimal resource allocation to maximize the sum of the session utilities and present a subgradient algorithm which converges to the optimal solution in the time-average sense. The solution involves an NP-hard subproblem of finding a minimum-cost Steiner tree. We cope with this difficulty by using a column generation method, which reduces the number of Steiner-tree computations. Furthermore, we allow the use of approximate solutions to the Steiner-tree subproblem. We show that the approximation ratio to the overall problem turns out to be no less than the reciprocal of the approximation ratio to the Steiner-tree subproblem. Simulation results demonstrate that universal swarming improves the performance of resource-poor sessions with negligible impact to resource-rich sessions. The proposed approach and algorithm are expected to be useful for infrastructure-based content distribution networks with long-lasting sessions and relatively stable network environment
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