Advantage Of Network Coding Research Articles

Improving bidirectional controlled remote preparation of arbitrary number of qudits in noisy environment

By elaborately selecting entangled channel, we put forward a universal scheme to achieve bidirectional remote preparation of qudit states with arbitrary numbers of particles under the control of the supervisor. Each sender needs to perform a positive-operator-value measurement and a projective measurement, while the supervisor requires to execute a projective measurement. Based on their measurement outcomes, the receivers can recover the desired states concurrently by carrying out single-qudit generalized Pauli operations which are given by general formulas. A point to highlight is that classical communication cost is greatly reduced at the supervisor’s broadcast channel by taking advantage of network coding. In addition, we analyze the influence of amplitude-damping and phase-damping noises, and utilize weak measurement and environment-assisted measurement to suppress noise.

Effective capacity of multi‐unicast flows using network coded‐ARQ

In this Letter, the authors consider a multi-unicast flow wireless communication system with a retransmission scheme. The effective capacity (EC) is used as a performance metric in order to make use of the recurrence relation approach. They also take advantage of network coding (NC) as combined with automatic repeat request (ARQ) protocol (NC-ARQ), for more robust communication. The authors' main contribution, in this work, is the derivation of the EC for M-user NC-ARQ using only the opportunity of XoR-ing M packets. They then, focus on a 3-user system and derive the EC using the opportunity of XoR-ing packets for 3 and 2 users. An interesting result is the fact that, contrary to expectation, as the number of users in a network that uses NC-ARQ increases, the performance in terms of EC increases as well, depending on how the sender schedules and manages the retransmissions.

Dynamic Resource Scheduling Optimization With Network Coding for Multi-User Services in the Internet of Vehicles

For Internet of Vehicles (IoV) systems with multiple users, network coding can be introduced to provide efficient error control and throughput improvement services. However, if the heterogeneity characteristics and requirements of the end users (vehicles) are neglected, it will be difficult for an IoV system to provide each end user with fair system services, without which the advantages of network coding cannot be fully achieved and the performance of the multi-user diversity system will be degraded. In this paper, we propose a Dynamic Resource Scheduling Optimization (DRSO) algorithm, a dynamic fair scheduling algorithm combined with network coding for system resource allocation in a multi-user IoV system. We construct a general solution framework for service scheduling: first, we estimate the fairness index for each end user (vehicle) with the key information on Quality of Service (QoS). Second, we construct a service scheduling control model based on the service capability of control entities (multi-access edge computing servers), and propose a new utility evaluation function. Third, based on the fairness index, we select end users into multiple network coding sets. Network coding sets are the basic units of service scheduling. The optimization objective of the scheduling service is to maximize the total utility of all the network coding sets (the utility of the control entity). Finally, we establish a coding cache queue in the control entity based on the scheduling decision. To obtain the global optimal solution for active queue control, we combine a Quantum Particle Swarm Optimization (QPSO) algorithm with a Proportional Integral (PI) model. Then, the optimal scheduling decision can be made. Extensive simulation results show that DRSO outperforms related scheduling algorithms in varying traffic loads, demonstrating that DRSO can effectively guide service resource allocation.

Network Coding for Wireless Sensor Network Cluster over Rayleigh Fading Channel: Finite State Markov Chain

Network Coding (NC) is confirmed to be power and bandwidth efficient technique, because of the less number of transmitted packets over the network. Wireless Sensor Network (WSN) is usually power limited network application, and in many scenarios it is power and bandwidth limited application. The proposed scenario in this paper applies the advantages of NC over WSN to obtain such power and bandwidth efficient WSN. To take the advantages of NC over the one of the most needed applications i.e., WSN, we come up to what this paper is discussing. We consider a WSN (or its cluster) that consists of M nodes that transmit equal-length information packets to a common destination node D over wireless Rayleigh block-fading channel where the instantaneous SNR is assumed to be constant over a single packet transmission period. Finite-State packet level Markov chain (FSMC) model is applied to give the channel more practical aspect. The simulation results showed that applying NC over the WSN cluster improved the channel bandwidth significantly by decreasing the number of the Automatic Repeat Request (ARQ), resulting in improving the power consumption significantly. The results are collected for different transmission distances to evaluate the behavior to the proposed scenario with regard to the bath losses effect.

Network Coding-Aware routing protocol in Wireless Mesh Networks

Network coding mechanisms, such as COPE, can improve network throughput effectively in Wireless Mesh Networks (WMN). While the Hybrid Wireless Mesh Protocol (HWMP) is suitable for WMN, its extension with COPE does not provide any added benefits; specifically, HWMP cannot establish paths with more coding opportunities. As a result, the advantages of network coding cannot be exploited sufficiently. This paper proposes improvements upon HWMP with a new, network Coding-Aware routing protocol (CAHWMP) for WMN. In the CAHWMP protocol, we propose a coding criterion based on data streams to devise an algorithm for actively detecting coding opportunities during path discovery. CAHWMP subsequently establishes paths using the coding-aware routing metric, which can balance channel resource consumption and the gain due to sharing resources introduced by network coding. Simulation results show that CAHWMP can establish paths with more coding opportunities; as a result, it improves network performance such as network throughput.

Fast Parallel Implementation for Random Network Coding on Embedded Sensor Nodes

Network coding is becoming essential part of network systems since it enhances system performance in various ways. To take full advantage of network coding, however, it is vital to guarantee low latency in the decoding process and thus parallelization of random network coding has drawn broad attention from the network coding community. In this paper, we investigate the problem of parallelizing random network coding for embedded sensor systems with multicore processors. Recently, general purpose graphics processing unit (GPGPU) technology has paved the way for parallelizing random network coding; however, it is not an option on embedded sensor nodes without GPUs and thus it is indispensable to leverage multicore processors which are becoming more common in embedded sensor nodes. We propose a novel random network coding parallelization technique that can fully exploit multicore processors. In our experiments, our parallel method exhibits over 150% throughput enhancement compared to existing state-of-the-art implementations on an embedded system.

Spatial Diversity with Network Coding for ON/OFF Satellite Channels

In this letter, we investigate the advantages of network coding (NC) combined with spatial diversity (SD) in scenarios with multiple sources, a single satellite and a single receiver. Each link source-satellite is modeled as an ON/OFF channel. We show that our system matches a wide number of realistic scenarios, from Wireless Sensor Networks (WSN) to Delay Tolerant Networks (DTN). We propose employing random linear network coding (RLNC) together with SD to reduce the system outage probability with respect to traditional SD scheme. The theoretical expressions we derive and the simulations performed show that the proposed scheme significantly reduces the system outage probability for a wide range of channel conditions. Moreover, we also propose a method for obtaining the optimal code rate constrained to a maximum system outage probability, which can serve as system design methodology.

Network coding-aware flow control in wireless ad-hoc networks with multi-path routing

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.

Distributed Robust Optimization for Scalable Video Multirate Multicast Over Wireless Networks

This paper proposes a distributed robust optimization scheme to jointly optimize overall video quality and traffic performance for scalable video multirate multicast over practical wireless networks. In order to guarantee layered utility maximization, the initial nominal joint source and network optimization is defined, where each scalable layer is tailored in an incremental order and finds jointly optimal multicast paths and associated rates with network coding. To enhance the robustness of the nominal convex optimization formulation with nonlinear constraints, we reserve partial bandwidth for backup paths disjoint from the primal paths. It considers the path-overlapping allocation of backup paths for different receivers to take advantage of network coding, and takes into account the robust multipath rate-control and bandwidth reservation problem for scalable video multicast streaming when possible link failures of primary paths exist. Specifically, an uncertainty set of the wireless medium capacity is introduced to represent the uncertain and time-varying property of parameters related to the wireless channel. The targeted uncertainty in the robust optimization problem is studied in a form of protection functions with nonlinear constraints, to analyze the tradeoff between robustness and distributedness. Using the dual decomposition and primal-dual update approach, we develop a fully decentralized algorithm with regard to communication overhead. Through extensive experimental results under critical performance factors, the proposed algorithm could converge to the optimal steady-state more quickly, and adapt the dynamic network changes in an optimal tradeoff between optimization performance and robustness than existing optimization schemes.

Efficient Wireless Broadcasting through Joint Network Coding and Beamforming

We develop a framework that exploits network coding (NC) and multiple-input/multiple-output (MIMO) techniques, jointly together, to improve throughput of downlink broadcast channels. Specifically, we consider a base station (BS) equipped with multiple transmit antennas that serves multiple mobile stations (MSs) simultaneously by generating multiple signal beams. Given the large number of MSs and the small number of transmit antennas, the BS must decide, at any transmission opportunity, which group of MSs it should transmit packets to, in order to maximize the overall throughput. We propose two algorithms for grouping MSs that take advantage of NC and the orthogonality of user channels to improve the overall throughput. Our results indicate that the proposed techniques increase the achievable throughput significantly, especially in highly lossy environments.