We consider a relay node that stochastically receives packets from two opposing flows. Whenever opportunities exist, the relay performs network coding to efficiently transmit packets. However, on one hand, because of ...
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We consider a relay node that stochastically receives packets from two opposing flows. Whenever opportunities exist, the relay performs network coding to efficiently transmit packets. However, on one hand, because of the stochastic nature, as well as possible asymmetry between the opposing flows, it would not be possible to always code packets. On the other hand, waiting for a coding opportunity could result in excessive latency, and one may be better off transmitting packets without coding. Thus, one needs to decide at each transmission opportunity whether to transmit a packet uncoded or wait for a future transmission opportunity. To enable us to optimally make that decision, we consider costs for transmission and delay, and formulate our problem as a Markov decision process. We show that the optimal policy is threshold type under a sufficient condition, and we compute it by modeling the resulting system as a Markov chain. Through numerical analysis, we show the effectiveness of the threshold policy in the relay node network, as well as in a line network scenario. Further, we compare the threshold policy against a number of simple heuristic policies and identify situations where these policies can be effective.
In this paper, we investigate transmission techniques for a fundamental cooperative cognitive radio network, i.e., a cognitive radio system where a Secondary user may act as relay for messages sent by the Primary user...
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In this paper, we investigate transmission techniques for a fundamental cooperative cognitive radio network, i.e., a cognitive radio system where a Secondary user may act as relay for messages sent by the Primary user, hence offering performance improvement of Primary user transmissions, while at the same time obtaining more transmission opportunities for its own transmissions. Specifically, we examine the possibility of improving the overall system performance by employing network coding techniques. The objective is to achieve this while affecting Primary user transmissions only positively, namely: 1) avoid network coding operations at the Primary transmitter, hence avoiding increase of its storage requirements and keeping its complexity low, 2) keep the order of packets received by the Primary receiver the same as in the non cooperative case and 3) induce packet service times that are stochastically smaller than the packet service times induced in the non-cooperative case. A network coding algorithm is investigated in terms of achieved throughput region and it is shown to enlarge Secondary user throughput as compared to the case where the Secondary transmitter acts as a simple relay, while leaving the Primary user stability region unaffected. A notable feature of this algorithm is that it operates without knowledge of channel and packet arrival rate statistics. We further present a second network coding algorithm which increases the throughput region of the system under certain conditions on system parameters;however, the latter algorithm requires knowledge of channel and packet arrival rate statistics.
In this paper, we study a flow control problem considering network coding in wireless ad-hoc networks with multi-path routing. As a network coding scheme, we use XOR network coding, in which each node bitwise-XORs som...
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In this paper, we study a flow control problem considering network coding in wireless ad-hoc networks with multi-path routing. As a network coding scheme, we use XOR network coding, in which each node bitwise-XORs some packets received from different sessions, and then broadcasts this coded packet to multiple nodes in a single transmission. This process can reduce the number of required transmissions, and thus can improve network utilization, especially if it is used with appropriate network coding-aware protocols. Considering this XOR network coding, we formulate an optimization problem for flow control that aims at maximizing network utility. By solving the optimization problem in a distributed manner, we implement a distributed flow control algorithm that provides the optimal transmitting rate on each of multiple paths of each session. The simulation results show that our flow control algorithm performs well exploiting the advantages of network coding and provides significant performance improvement.
The following network computing problem is considered. Source nodes in a directed acyclic network generate independent messages and a single receiver node computes a target function of the messages. The objective is t...
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The following network computing problem is considered. Source nodes in a directed acyclic network generate independent messages and a single receiver node computes a target function of the messages. The objective is to maximize the average number of times can be computed per network usage, i.e., the "computing capacity". The network coding problem for a single-receiver network is a special case of the network computing problem in which all of the source messages must be reproduced at the receiver. For network coding with a single receiver, routing is known to achieve the capacity by achieving the network min-cut upper bound. We extend the definition of min-cut to the network computing problem and show that the min-cut is still an upper bound on the maximum achievable rate and is tight for computing (using coding) any target function in multi-edge tree networks. It is also tight for computing linear target functions in any network. We also study the bound's tightness for different classes of target functions. In particular, we give a lower bound on the computing capacity in terms of the Steiner tree packing number and a different bound for symmetric functions. We also show that for certain networks and target functions, the computing capacity can be less than an arbitrarily small fraction of the min-cut bound.
By caching the most popular content into mobile devices, users can retrieve content directly from nearby devices through Device to Device (D2D) communications, which can significantly reduce backhaul traffic and impro...
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By caching the most popular content into mobile devices, users can retrieve content directly from nearby devices through Device to Device (D2D) communications, which can significantly reduce backhaul traffic and improve network performance. Most existing D2D cache placement strategies are proactive approaches, which cannot deal with the problem of timely cache updating. In this paper, we propose a network coding-based socially-aware D2D caching strategy, which takes geographical proximity and the social relationships of users into consideration. First, a physical D2D network with high communication reliability is built according to the geographical proximity, composed of devices with high probability of communicating to each other through stable D2D communications. According to the social relationship between users within the physical D2D network, we partition the devices into communities and rank the devices within same community by their influence degree. Within a community, each caching decision is made independently according to the user-content contribution degree. To calculate the contribution degree, the impact between devices on requesting same content is modeled using an Indian Buffet Process. Devices cache coded blocks instead of the whole content to improve caching efficiency. Simulation results show that the proposed strategy achieves higher cache hit and sum rates compared to other schemes.
In this paper, we use entropy functions to characterize the set of rate-capacity tuples achievable with either zero decoding error, or vanishing decoding error, for general network coding problems for acyclic networks...
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In this paper, we use entropy functions to characterize the set of rate-capacity tuples achievable with either zero decoding error, or vanishing decoding error, for general network coding problems for acyclic networks. We show that when sources are colocated, the outer bound is tight and the sets of zero-error achievable and vanishing-error achievable rate-capacity tuples are the same. Then, we extend this paper to networks subject to linear encoding constraints, routing constraints (where some or all nodes can only perform routing), and secrecy constraints. Finally, we show that even for apparently simple networks, design of optimal codes may be difficult. In particular, we prove that for the incremental multicast problem and for the single-source secure network coding problem, characterization of the achievable set can be very hard and linear network codes may not be optimal.
network coding is a powerful coding technique that has been proved to be very effective in achieving the maximum multicast capacity. It is especially suited for new emerging networks such as ad-hoc and sensor networks...
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network coding is a powerful coding technique that has been proved to be very effective in achieving the maximum multicast capacity. It is especially suited for new emerging networks such as ad-hoc and sensor networks. In this work, we investigate the multicast routing problem based on network coding and put forward a practical algorithm to obtain the maximum flow multicast routes in ad-hoc networks. The "Conflict Phenomenon" that occurs in undirected graphs will also be discussed. Given the developed routing algorithm, we will present the condition for a node to be an encoding node along with a corresponding capacity allocation scheme. We will also analyze the statistical characteristics of encoding nodes and maximum flow in ad-hoc networks based on random graph theory.
Ten years ago, Ahlswede, Cai, Li, and Yeung refuted the folklore that information can be regarded as a commodity in network communication by means of an example now known as the butterfly network. The concept of netwo...
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Ten years ago, Ahlswede, Cai, Li, and Yeung refuted the folklore that information can be regarded as a commodity in network communication by means of an example now known as the butterfly network. The concept of network coding was formulated, and the fundamental max-flow-min-cut theorem for information flow was established. Since then, the work has generated much interest among many different research communities in engineering, mathematics, and natural science. This paper gives a historical account of the developments that led to this seminal work in network coding.
network coding enables novel network functionalities and thus offers a wider canvas of choices when optimizing an information flow problem. In this paper, we examine the simplest possible information flow problem, a u...
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network coding enables novel network functionalities and thus offers a wider canvas of choices when optimizing an information flow problem. In this paper, we examine the simplest possible information flow problem, a unicast connection, and explore what we believe is one of the most attractive features network coding offers: the ability to enable near-optimal performance in a completely decentralized and randomized setting. This is an especially attractive feature for wireless applications. However, it comes at the cost of an overhead in terms of rate that can be significant for applications that operate using relatively short frame lengths, as is the case in the wireless setting. We review the efforts in the literature to either alleviate this overhead, or alternatively, to exploit it for network management and control.
This paper addresses the problem of survivability of many-to-one flows in wireless networks, such as wireless mesh networks (WMNs) and wireless sensor networks (WSNs). Traditional protection schemes are either resourc...
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This paper addresses the problem of survivability of many-to-one flows in wireless networks, such as wireless mesh networks (WMNs) and wireless sensor networks (WSNs). Traditional protection schemes are either resource-hungry like the (1 + 1) protection scheme, or introduce a delay and interrupt the network operation like the (1 : N) protection scheme. In this paper, we present a network coding-based protection technique that overcomes the deficiencies of the traditional schemes. We derive and prove the necessary and sufficient conditions for our solution on a restricted network topology. Then we relax these connectivity requirements and show how to generalize the sufficient and necessary conditions to work with any other topology. We also show how to perform deterministic coding with {0,1} coefficients to achieve linear independence. Moreover, we discuss some of the practical considerations related to our approach. Specifically, we show how to adapt our solution when the network has a limited min-cut;we therefore define a more general problem that takes this constraint into account, which prove to be NP-complete. Furthermore, we discuss the decoding process at the sink, and show how to make use of our solution in the upstream communication (from sink to sources). We also study the effect of the proposed scheme on network performance. Finally, we consider the implementation of our approach when all network nodes have single transceivers, and we solve the problem through a greedy algorithm that constructs a feasible schedule for the transmissions from the sources.
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