Research and Realization of Multi-channel Multi-interface Wireless Network Coding Based on Guesswork

This paper studies how to assign radio interfaces to work on multiple channels in multi-channel and multi-interface wireless networks. Different from previous studies that focused on the MAC layer, we study this problem from a global perspective. We use a layered graph to model multi-channel wireless networks, and develop effective interface assignment and routing path computation algorithms based on the layered graph. We have evaluated the performance of our algorithm and compared it to a sequential interface assignment algorithm. The numerical results show that our algorithm significantly outperforms the sequential interface assignment.

This paper considers the interplay between rate adaptation and inter-session network coding gains in wireless mesh or ad hoc networks. Inter-session network coding opportunities at relay nodes depend on packets being overheard by surrounding nodes ? The more packets nodes overhear, the more opportunities relays have to combine packets, resulting in a potential increase in network throughput. Thus, by adapting its transmission rate, a node can increase the range over which its packets are overheard, enabling additional opportunities for coding and increased overall throughput. This paper considers inter-session coding, restricted to a single relay (bottleneck) node, or star network topology. Even for such simple topologies the optimal joint rate adaptation and network coding policy is known to be NP-hard. Optimal rate vector selection is a combinatorial optimization problem, which is NP-hard, and finding optimal coding scheme turns out to be a clique partitioning problem which is also NP-hard. So, we provide heuristics to find a suboptimal rate vector and coding scheme. Additionally, we provide a linear programming formulation for network coding when only pairwise intersession coding is allowed. We evaluate the averaged throughput in two different scenarios, in which relays have different access opportunities, giving some intuition on the impact of rate adaptation in lightly and heavily loaded systems. The gains of joint rate adaptation and network coding are marginal when the relay has a higher access opportunity than other nodes, or when the MAC operates ideally it ranges from 9% to 19% as compared to a network without network coding and 4% over a network using regular network coding. While, when the relay has equal access opportunity as other source nodes, which is more typical of todays MAC protocols under heavy loads, the gain ranges from 40% to 62% as compared to the standard relaying case and is upto around 20% as compared to a network with regular pairwise network coding. This can further be increased to a gain of 40% to 120% by replacing pairwise coding with sub-optimal general network coding scheme.

We investigate the optimal design of a multihop wireless mesh network equipped with multiple orthogonal wireless channels and multiple radios. Specifically, we focus on solutions that can efficiently utilize the limited resource to support multiple unicast applications by routing and network coding. We propose a cross-layer optimization framework where the broadcasting feature of the wireless environment, which plays an important role in realizing the achievable gain of network coding, is taken into account. Moreover, we propose a network code construction scheme based on linear programming, with which the possible achievable Coding+MAC gain could be significantly increased. The proposed network design based on cross-layer optimization results in significant increase in network throughput.

A recent approach--COPE, presented by Katti et al. (Proc. ACM SIGCOMM 2006, pp. 243-254)--for improving the throughput of unicast traffic in wireless multihop networks exploits the broadcast nature of the wireless medium through opportunistic network coding. In this paper, we analyze throughput improvements obtained by COPE-type network coding in wireless networks from a theoretical perspective. We make two key contributions. First, we obtain a theoretical formulation for computing the throughput of network coding on any wireless network topology and any pattern of concurrent unicast traffic sessions. Second, we advocate that routing be made aware of network coding opportunities rather than, as in COPE, being oblivious to it. More importantly, our model considers the tradeoff between routing flows close to each other for utilizing coding opportunities and away from each other for avoiding wireless interference. Our theoretical formulation provides a method for computing source-destination routes and utilizing the best coding opportunities from available ones so as to maximize the throughput. We handle scheduling of broadcast transmissions subject to wireless transmit/receive diversity and link interference in our optimization framework. Using our formulations, we compare the performance of traditional unicast routing and network coding with coding-oblivious and coding-aware routing on a variety of mesh network topologies, including some derived from contemporary mesh network testbeds. Our evaluations show that a route selection strategy that is aware of network coding opportunities leads to higher end-to-end throughput when compared to coding-oblivious routing strategies.

Systems with multiple channels and multiple radios per node have been shown to enhance throughput of wireless mesh networks (WMNs). Recently, network coding has also been proved to be a promising technique for improving network throughput of WMNs. However, the performance of network coding in the context of multicast, a form of one-to-many communication, in multi-channel multi-radio (MCMR) WMNs is still unknown. In this paper, we present analytical models for estimating the average end-to-end delay, throughput and packet delivery ratio of a network-coded multicast session in 802.11-based MCMR WMNs. The proposed models are then validated using numerical analysis and simulations. To the best of our knowledge, our work is the first that studies the performance of network-coded multicast in MCMR WMNs.

Network coding is a technology with great potentiality in improving wireless multi-hop network throughput. And some routings combined with network coding have been proposed for wireless multi-hop network. In the routings combined with network coding, network coding condition is used to find network coding opportunities, which is very important to the performance improving of routings combined with network coding. However, the network coding conditions defined by existing routings combined with network coding unilaterally focus on the growth of network coding opportunities, which results in the increasing of cost and delay in routing discovery. Moreover, the more flows participating network coding, the higher probability of decoding failure, which degrade the network coding gain. In this paper, low complexity network coding condition (LCNC) is proposed. LCNC only detects two-flows network coding opportunity, and ensures the destination make successful decoding. In addition, the actual network coding gain is designed through analysis of link quality. Network coding opportunity will be ignored in case the actual network coding gain is negative. Based on LCNC, a low complexity network coding aware routing (LNCR) is designed aiming wireless multi-hop network. Simulation results demonstrate that LNCR obtain a balance between network coding gain and routing discovery cost, and can obtain higher network throughput when the network load is high compared with the classical network coding aware routings.

In this letter, an Opportunistic Interference Cancellation (OIC) is first introduced as a rate control strategy for secondary user in cognitive wireless networks. Based on the OIC rate control method, an optimal power control strategy for multichannel cognitive wireless networks is proposed. The algorithm aims to maximize the total transmit rate of cognitive user through appropriately controlling the transmit power of each subchannel under the constraint that the interference temperature at the primary receiver is below a certain threshold. Three suboptimal power control methods, namely Equal Power Transmission (EPT), Equal Rate Transmission (ERT) and Equal Interference Transmission (EIT), are also proposed. The performances of the proposed power control methods are compared through numerical simulations.

This paper studies the use of the proportional fairness (PF) utility function as the basis for capacity allocation and scheduling in multi-channel multi-rate wireless networks. Examples of applications include (i) access point (AP) association and transmission scheduling in large-scale IEEE 802.11 networks; and (ii) subcarrier assignment and transmission scheduling in orthogonal frequency division multiplexing (OFDM) cellular networks. The contributions of this paper are twofold. First, we study the fundamental properties and physical/economic interpretation of PF. We show by general mathematical arguments that PF leads to equal airtime allocation to individual users for the single-channel case; and equal equivalent airtime allocation to individual users for the multi-channel case, where the equivalent airtime enjoyed by a user is a weighted sum of the airtimes enjoyed by the user on all channels, with the weight of a channel being the price or value of that channel. In addition, we establish the Pareto efficiency of PF solutions and derive characteristics of PF solutions that are useful for the construction of PF algorithms. Second, we generate numerical results for application (i) above. We find that the PF solution simultaneously achieves higher system throughput, better fairness, and lower outage probability with respect to the default AP-association and medium access control (MAC) protocol adopted in today's 802.11 commercial products.

In recent years, network coding has emerged as an innovative method that helps wireless network approaches its maximum capacity, by combining multiple unicasts in one broadcast. However, the majority of research conducted in this area is yet to fully utilize the broadcasting nature of wireless networks, and still assumes fixed route between the source and destination that every packet should travel through. This assumption not only limits coding opportunities, but can also cause buffer overflow in some specific intermediate nodes. Although some studies considered scattering of the flows dynamically in the network, they still face some limitations. This paper explains pros and cons of some prominent research in network coding and proposes FlexONC (Flexible and Opportunistic Network Coding) as a solution to such issues. The performance results show that FlexONC outperforms previous methods especially in worse quality networks, by better utilizing redundant packets spread in the network.

Nowadays, wireless networks are employed for many applications, but they face some problems such as power source limitation and collision due to common media. These problems decrease the network throughput and increase the power consumption. Fading is another important characteristic of wireless channels, which degrades the network performance. On the contrary, network coding is a useful method that can be applied to increase throughput. We extend the network coding model from two nodes with one relay to four nodes with the same relay over Rayleigh fading channels. Each side of the relay consists of two neighbouring nodes, which relaying nodes are not needed between them. In this paper, we propose a new method that uses priority property for decoding so that high or low priority for a node means that the node will XOR received data from relay node and its own data or data received from its neighbour, respectively. Also, decoding procedure includes two stages in which one of the neighbour nodes in each side has high priority and the other one has low priority. Then, network performance and the effects of Rayleigh fading on network coding over double‐link channels are studied under power‐constant and channel‐inversion schemes. By solving optimisation problems called Double‐Link Network Coding Constant Power and Double‐Link Network Coding Channel Inversion, we obtain optimum network throughput. The results show that the proposed method increases network throughput and decreases power consumption by reducing number of time slots in comparison with the simple method. Copyright © 2013 John Wiley & Sons, Ltd.

Recently, it has been proven that retransmission based on Network Coding (NC) can greatly improve the performance of wireless networks with broadcast erasure channels. However, network coding also introduces additional delay at the both sending and receiving sides, resulting in the decline of the Quality of user Experience (QoE). In this paper, we consider the users' waiting time and the decoding delay as the performance metrics and then propose MixCode, a NC-based loss recovery method, to improve the delay performance in heterogeneous wireless networks. MixCode incorporates Opportunistic Network Coding (ONC) with Random Linear Network Coding (RLNC), where a NC packet can be decoded by simply XORing operation at some destinations, but by Gaussian elimination at other destinations. Simulation results show that our proposed algorithm can efficiently reduce both the waiting time and the decoding delay in comparison with the existing NC-based schemes.

This work studies the power optimal dynamic scheduling problem in multi-channel multi-user wireless access networks. Users have quality-of-service (QoS) requirements on the minimum rates with statistical delay guarantees. Only one user is allowed to transmit over a channel in a given time slot. This work considers two scenarios: homogeneous and heterogeneous users. For the former scenario, the optimal scheduling policy can be derived, and an online scheduling algorithm for the optimal policy is proposed using online time-averaging without requiring a-priori known fading statistics. For the latter scenario, the optimal scheduling problem is combinatorially hard; hence, even when the fading statistics are available, computing the optimal policy is intractable. Consequently, this work develops a sub-optimal online scheduling algorithm with linear complexity which does not require a-priori known fading statistics. Moreover, the scheduling algorithm satisfies the QoS constraints for the users. Illustrative results demonstrate the performance of the proposed scheduling algorithms in various settings.

Systems with multiple channels and multiple radios per node have been shown to enhance throughput of wireless mesh networks (WMNs). Recently, network coding has also been proved to be a promising technique for improving network throughput of WMNs. However, the performance of network coding in the context of multicast in multi-channel multi-radio (MCMR) WMNs is still unknown. In this paper, we present a comprehensive performance evaluation of network-coded multicast in MCMR WMNs using extensive simulations, realistic network settings and meaningful performance metrics such as throughput, file completion time, packet end-to-end delay, and packet delivery ratio under a wide range of scenarios.

As wireless networks are gaining increasing popularity, the network energy efficiency has become a critical issue. In this paper, we focus on energy-efficient networking in a generic multi-radio multi-channel (MR-MC) wireless network where transmission scheduling, transmit power control, radio and channel assignment are coupled together in a multi-dimensional resource space, thus requiring joint optimization and low complexity algorithms. We propose a novel Decomposed Approach For energy-efficient (DAFEE) networking in MR-MC networks, with the objective to minimize network energy consumption while guaranteeing a certain level of performance. In particular, we leverage a multi-dimensional tuple-link based model and a concept of resource allocation pattern to transform the complex optimization problem into a linear programming (LP) problem. The LP problem however has a very large solution space due to the exponentially many possible resource allocation patterns. We then exploit delay column generation and distributed learning techniques to decompose the problem and solve it with an iterative process. Furthermore, we propose a sub-optimal algorithm to speed up the iteration with constant-bounded performance. Simulation results are presented to demonstrate the effectiveness of the proposed algorithm.

Network coding is a promising enhancement of routing to improve network throughput and provide high reliability. It allows a node to generate output messages by encoding its received messages. Peer-to-peer networks are a perfect place to apply network coding due to two reasons: the topology of a peer-to-peer network is constructed arbitrarily, thus it is easy to tailor the topology to facilitate network coding; the nodes in a peer-to-peer network are end hosts which can perform more complex operations such as decoding and encoding than simply storing and forwarding messages. In this paper, we propose a scheme to apply network coding to peer-to-peer file sharing which employs a peer-to-peer network to distribute files resided in a web server or a file server. The scheme exploits a special type of network topology called combination network. It was proved that combination networks can achieve unbounded network coding gain measured by the ratio of network throughput with network coding to that without network coding. Our scheme encodes a file into multiple messages and divides peers into multiple groups with each group responsible for relaying one of the messages. The encoding scheme is designed to satisfy the property that any subset of the messages can be used to decode the original file as long as the size of the subset is sufficiently large. To meet this requirement, we first define a deterministic linear network coding scheme which satisfies the desired property, then we connect peers in the same group to flood the corresponding message, and connect peers in different groups to distribute messages for decoding. Moreover, the scheme can be readily extended to support link heterogeneity and topology awareness to further improve system performance in terms of throughput, reliability and link stress. Our simulation results show that the new scheme can achieve 15%–20% higher throughput than another peer-to-peer multicast system, Narada, which does not employ network coding. In addition, it achieves good reliability and robustness to link failure or churn.