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104
Network Coding for Large Scale Content Distribution
"... We propose a new scheme for content distribution of large files that is based on network coding. With network coding, each node of the distribution network is able to generate and transmit encoded blocks of information. The randomization introduced by the coding process eases the scheduling of bloc ..."
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Cited by 497 (6 self)
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We propose a new scheme for content distribution of large files that is based on network coding. With network coding, each node of the distribution network is able to generate and transmit encoded blocks of information. The randomization introduced by the coding process eases the scheduling of block propagation, and, thus, makes the distribution more efficient. This is particularly important in large unstructured overlay networks, where the nodes need to make decisions based on local information only. We compare network coding to other schemes that transmit unencoded information (i.e. blocks of the original file) and, also, to schemes in which only the source is allowed to generate and transmit encoded packets. We study the performance of network coding in heterogeneous networks with dynamic node arrival and departure patterns, clustered topologies, and when incentive mechanisms to discourage freeriding are in place. We demonstrate through simulations of scenarios of practical interest that the expected file download time improves by more than 2030 % with network coding compared to coding at the server only and, by more than 23 times compared to sending unencoded information. Moreover, we show that network coding improves the robustness of the system and is able to smoothly handle extreme situations where the server and nodes departure the system.
Polynomial time algorithms for multicast network code construction
 IEEE TRANS. ON INFO. THY
, 2005
"... The famous maxflow mincut theorem states that a source node can send information through a network ( ) to a sink node at a rate determined by the mincut separating and. Recently, it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediat ..."
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Cited by 317 (31 self)
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The famous maxflow mincut theorem states that a source node can send information through a network ( ) to a sink node at a rate determined by the mincut separating and. Recently, it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to reencode the information they receive. We demonstrate examples of networks where the achievable rates obtained by coding at intermediate nodes are arbitrarily larger than if coding is not allowed. We give deterministic polynomial time algorithms and even faster randomized algorithms for designing linear codes for directed acyclic graphs with edges of unit capacity. We extend these algorithms to integer capacities and to codes that are tolerant to edge failures.
Polynomial Time Algorithms for Network Information Flow
 in 15th ACM Symposium on Parallel Algorithms and Architectures
, 2003
"... The famous maxflow mincut theorem states that a source node s can send information through a network (V; E) to a sink node t at a data rate determined by the mincut separating s and t. Recently it has been shown that this rate can also be achieved for multicasting to several sinks provided that t ..."
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Cited by 118 (1 self)
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The famous maxflow mincut theorem states that a source node s can send information through a network (V; E) to a sink node t at a data rate determined by the mincut separating s and t. Recently it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to reencode the information they receive. In contrast, we present graphs where without coding the rate must be a factor jV j) smaller. However, so far no fast algorithms for constructing appropriate coding schemes were known. Our main result are polynomial time algorithms for constructing coding schemes for multicasting at the maximal data rate.
Network Coding in Undirected Networks
, 2004
"... Recent work in network coding shows that, it is necessary to consider both the routing and coding strategies to achieve optimal throughput of information transmission in data networks. So far, most research on network coding has focused on the model of directed networks, where each communication li ..."
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Cited by 82 (18 self)
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Recent work in network coding shows that, it is necessary to consider both the routing and coding strategies to achieve optimal throughput of information transmission in data networks. So far, most research on network coding has focused on the model of directed networks, where each communication link has a fixed direction. In this paper, we study the benefits of network coding in undirected networks, where each communication link is bidirectional. Our theoretical results show that, for a single unicast or broadcast session, there are no improvements with respect to throughput due to network coding. In the case of a single multicast session, such an improvement is bounded by a factor of two, as long as half integer routing is permitted. This is dramatically different from previous results obtained in directed networks. We also show that multicast throughput in an undirected network is independent of the selection of the sender within the multicast group. We finally show that, rather than improving the optimal achievable throughput, the benefit of network coding is to significantly facilitate the design of efficient algorithms to compute and achieve such optimal throughput. I.
On achieving optimal throughput with network coding
 in Proc. IEEE Infocom 2005
, 2005
"... Abstrkt With the constraints of network topologies and link capacities, achieving the optimal endtoend throughput in data networks has been known as a fundamental but camputationally hard problem, In this paper, we seek efficient solutions to the problem of achieving optimal throughput in data ne ..."
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Cited by 72 (30 self)
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Abstrkt With the constraints of network topologies and link capacities, achieving the optimal endtoend throughput in data networks has been known as a fundamental but camputationally hard problem, In this paper, we seek efficient solutions to the problem of achieving optimal throughput in data networks, with single or multiple unicast, multicast and broadcast sessions. Although previous approaches lead to solving NPcomplete prohlems, we show the surprising result that, facilitated by the recent advances of network coding, computing the strategies to achieve the optimal endtoend throughput can be performed in polynomial time. This result holds for one or more communication sessions, as well as in the overlay network model, Supported by empirical studies, we present the surprising observation that in most topologies, applying network coding may not improve the achievable optimal throughput; rather, it facilitates the design of significantly more efficient algorithms to achieve such optimality.
A CrossLayer Optimization Framework for Multihop Multicast in Wireless Mesh Networks
 JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (JSAC
, 2006
"... The optimal and distributed provisioning of high throughput in mesh networks is known as a fundamental but hard problem. The situation is exacerbated in a wireless setting due to the interference among local wireless transmissions. In this paper, we propose a crosslayer optimization framework for ..."
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Cited by 61 (6 self)
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The optimal and distributed provisioning of high throughput in mesh networks is known as a fundamental but hard problem. The situation is exacerbated in a wireless setting due to the interference among local wireless transmissions. In this paper, we propose a crosslayer optimization framework for throughput maximization in wireless mesh networks, in which the data routing problem and the wireless medium contention problem are jointly optimized for multihop multicast. We show that the throughput maximization problem can be decomposed into two subproblems: a data routing subproblem at the network layer, and a power control subproblem at the physical layer with a set of Lagrangian dual variables coordinating interlayer coupling. Various effective solutions are discussed for each subproblem. We emphasize the network coding technique for multicast routing and a game theoretic method for interference management, for which efficient and distributed solutions are derived and illustrated. Finally, we show that the proposed framework can be extended to take into account physicallayer wireless multicast in mesh networks.
Mutualcast: An Efficient Mechanism for Content Distribution in a PeertoPeer (P2P) Network
, 2004
"... In this paper, we propose Mutualcast, a new delivery mechanism for content distribution in peertopeer (P2P) networks. Compared with prior onetomany content distribution approaches, Mutualcast splits the tobedistributed content into many small blocks, so that more resourceful nodes may redistri ..."
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Cited by 46 (12 self)
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In this paper, we propose Mutualcast, a new delivery mechanism for content distribution in peertopeer (P2P) networks. Compared with prior onetomany content distribution approaches, Mutualcast splits the tobedistributed content into many small blocks, so that more resourceful nodes may redistribute more blocks, and less resourceful nodes may redistribute less blocks. Each content block is assigned to a single node for distribution, and the node in charge can be a contentrequesting peer node, a noncontentrequesting peer node, or even the source node. The throughput of the distribution is controlled by redistribution queues between the source and the peer nodes. We show that such a strategy fully utilizes the upload bandwidths of all the peer nodes, thereby maximizing the delivery throughput. Furthermore, Mutualcast is simple and flexible. It can be applied to file/software downloading, media streaming, and erasure coded file distribution in a P2P network.
Utility Maximization in PeertoPeer Systems
"... In this paper, we study the problem of utility maximization in P2P systems, in which aggregate applicationspecific utilities are maximized by running distributed algorithms on P2P nodes, which are constrained by their uplink capacities. This may be understood as extending Kelly’s seminal framework f ..."
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Cited by 43 (12 self)
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In this paper, we study the problem of utility maximization in P2P systems, in which aggregate applicationspecific utilities are maximized by running distributed algorithms on P2P nodes, which are constrained by their uplink capacities. This may be understood as extending Kelly’s seminal framework from singlepath unicast over general topology to multipath multicast over P2P topology, with network coding allowed. For certain classes of popular P2P topologies, we show that routing along a linear number of trees per source can achieve the largest rate region that can be possibly obtained by (multisource) network coding. This simplification result allows us to develop a new multitree routing formulation for the problem. Despite of the negative results in literature on applying Primaldual algorithms to maximize utility under multipath settings, we have been able to develop a Primaldual distributed algorithm to maximize the aggregate utility under the multipath routing environments. Utilizing our proposed sufficient condition, we show global exponential convergence of the Primaldual algorithm to the optimal solution under different P2P communication scenarios we study. The algorithm can be implemented by utilizing only endtoend delay measurements between P2P nodes; hence, it can be readily deployed on today’s Internet. To support this claim, we have implemented the Primaldual algorithm for use in a peerassisted multiparty conferencing system and evaluated its performance through actual experiments on a LAN testbed and the Internet.
A Comparison of Network Coding and Tree Packing
 IN PROC. 2004 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT 2004
, 2004
"... In this paper, we consider the problem of information multicast, namely transmitting common information from a sender s to a set of receivers T , in a communication network. Conventionally, in a communication network such as the Internet, this is done by distributing information over a multicast dis ..."
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Cited by 38 (3 self)
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In this paper, we consider the problem of information multicast, namely transmitting common information from a sender s to a set of receivers T , in a communication network. Conventionally, in a communication network such as the Internet, this is done by distributing information over a multicast distribution tree. The nodes of such a tree are required only to replicate and forward, i.e., route, information received. Recently, Ahlswede et al. [1] demonstrated that it is in general suboptimal to restrict the network nodes to perform only routing. They show that the multicast capacity, which is defined as the maximum rate that a sender can communicate common information to a set of receivers, is given by the minimum C = min t#T C t of maxflows C t = maxflow(s, t) between the sender and each receiver. Moreover, they showed that while the multicast capacity cannot be achieved in general by routing, it can be achieved by network coding. Network coding refers to a scheme where coding is done at the interior nodes in the network, not only at the sender and receivers. Li, Yeung, and Cai [2] showed that it is su#cient for the encoding functions at the interior nodes to be linear. Koetter and Medard[3] gave an algebraic characterization of linear encoding schemes and proved existence of linear timeinvariant codes achieving the multicast capacity. Jaggi, Sanders, et al. [4][5][6] showed for acyclic networks how to find the encoding and decoding coe#cients in polynomial time. Chou, Wu, and Jain [7][8] proposed a distributed scheme for practical network coding in real packet networks achieving throughput close to capacity with low delay that is robust to random packet loss and delay as well as robust to any changes to network topology or capacity