Cooperative network-coding system for wireless sensor networks

Describes a cooperative network coding system for wireless sensor networks. In this paper, we propose two practical power) and bandwidth)efficient systems based on amplify)and)forward (AF) and decode)and)forward (DF) schemes to address the problem of information exchange via a relay. The key idea is to channel encode each source’s message by using a high)performance non)binary turbo code based on Partial Unit Memory (PUM) codes to enhance the bit)error)rate performance, then reduce the energy consumption and increase spectrum efficiency by using network coding (NC) to combine individual nodes’ messages at the relay before forwarding to the destination. Two simple and low complexity physical layer NC schemes are proposed based on combinations of received source messages at the relay. We also present the theoretical limits and numerical analysis of the proposed schemes. Simulation results under Additive White Gaussian Noise, confirm that the proposed schemes achieve significant bandwidth savings and fewer transmissions over the benchmark systems which do not resort to NC. Theoretical limits for capacity and Signal to Noise Ratio behaviour for the proposed schemes are derived. The paper also proposes a cooperative strategy that is useful when insufficient combined messages are received at a node to recover the desired source messages, thus enabling the system to retrieve all packets with significantly fewer retransmission request messages

High-resolution distributed sampling of bandlimited fields with low-precision sensors

The problem of sampling a discrete-time sequence of spatially bandlimited fields with a bounded dynamic range, in a distributed, communication-constrained, processing environment is addressed. A central unit, having access to the data gathered by a dense network of fixed-precision sensors, operating under stringent inter-node communication constraints, is required to reconstruct the field snapshots to maximum accuracy. Both deterministic and stochastic field models are considered. For stochastic fields, results are established in the almost-sure sense. The feasibility of having a flexible tradeoff between the oversampling rate (sensor density) and the analog-to-digital converter (ADC) precision, while achieving an exponential accuracy in the number of bits per Nyquist-interval per snapshot is demonstrated. This exposes an underlying ``conservation of bits'' principle: the bit-budget per Nyquist-interval per snapshot (the rate) can be distributed along the amplitude axis (sensor-precision) and space (sensor density) in an almost arbitrary discrete-valued manner, while retaining the same (exponential) distortion-rate characteristics. Achievable information scaling laws for field reconstruction over a bounded region are also derived: With N one-bit sensors per Nyquist-interval, $\Theta(\log N)$ Nyquist-intervals, and total network bitrate $R_{net} = \Theta((\log N)^2)$ (per-sensor bitrate $\Theta((\log N)/N)$), the maximum pointwise distortion goes to zero as $D = O((\log N)^2/N)$ or $D = O(R_{net} 2^{-\beta \sqrt{R_{net}}})$. This is shown to be possible with only nearest-neighbor communication, distributed coding, and appropriate interpolation algorithms. For a fixed, nonzero target distortion, the number of fixed-precision sensors and the network rate needed is always finite.Comment: 17 pages, 6 figures; paper withdrawn from IEEE Transactions on Signal Processing and re-submitted to the IEEE Transactions on Information Theor

S-RLNC based MAC Optimization for Multimedia Data Transmission over LTE/LTE-A Network

The high pace emergence in communication systems and associated demands has triggered academia-industries to achieve more efficient solution for Quality of Service (QoS) delivery for which recently introduced Long Term Evolution (LTE) or LTE-Advanced has been found as a promising solution. However, enabling QoS and Quality of Experience (QoE) delivery for multimedia data over LTE has always been a challenging task. QoS demands require reliable data transmission with minimum signalling overheads, computational complexity, minimum latency etc, for which classical Hybrid Automatic Repeat Request (HREQ) based LTE-MAC is not sufficient. To alleviate these issues, in this paper a novel and robust Multiple Generation Mixing (MGM) assisted Systematic Random Linear Network Coding (S-RLNC) model is developed to be used at the top of LTE MAC protocol stack for multimedia data transmission over LTE/LTE-A system. Our proposed model incorporated interleaving and coding approach along with MGM to ensure secure, resource efficient and reliable multiple data delivery over LTE systems. The simulation results reveal that our proposed S-RLNC-MGM based MAC can ensure QoS/QoE delivery over LTE systems for multimedia data communication

Telecommunications Networks

This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

Network Coding: Exploiting Broadcast and Superposition in Wireless Networks

In this thesis we investigate improvements in efficiency of wireless communication networks, based on methods that are fundamentally different from the principles that form the basis of state-of-the-art technology. The first difference is that broadcast and superposition are exploited instead of reducing the wireless medium to a network of point-to-point links. The second difference is that the problem of transporting information through the network is not treated as a flow problem. Instead we allow for network coding to be used.\ud \ud First, we consider multicast network coding in settings where the multicast configuration changes over time. We show that for certain problem classes a universal network code can be constructed. One application is to efficiently tradeoff throughput against cost.\ud \ud Next, we deal with increasing energy efficiency by means of network coding in the presence of broadcast. It is demonstrated that for multiple unicast traffic in networks with nodes arranged on two and three dimensional rectangular lattices, network coding can reduce energy consumption by factors of four and six, respectively, compared to routing.\ud \ud Finally, we consider the use of superposition by allowing nodes to decode sums of messages. We introduce different deterministic models of wireless networks, representing various ways of handling broadcast and superposition. We provide lower and upper bounds on the transport capacity under these models. For networks with nodes arranged on a hexagonal lattice it is found that the capacity under a model exploiting both broadcast and superposition is at least 2.5 times, and no more than six times, the transport capacity under a model of point-to-point links

IEEE 802.15.4e: a Survey

Several studies have highlighted that the IEEE 802.15.4 standard presents a number of limitations such as low reliability, unbounded packet delays and no protection against interference/fading, that prevent its adoption in applications with stringent requirements in terms of reliability and latency. Recently, the IEEE has released the 802.15.4e amendment that introduces a number of enhancements/modifications to the MAC layer of the original standard in order to overcome such limitations. In this paper we provide a clear and structured overview of all the new 802.15.4e mechanisms. After a general introduction to the 802.15.4e standard, we describe the details of the main 802.15.4e MAC behavior modes, namely Time Slotted Channel Hopping (TSCH), Deterministic and Synchronous Multi-channel Extension (DSME), and Low Latency Deterministic Network (LLDN). For each of them, we provide a detailed description and highlight the main features and possible application domains. Also, we survey the current literature and summarize open research issues

Wireless sensor networks using network coding for structural health monitoring

Wireless Sensor Networks (WSNs) have been deployed for the purpose of structural health monitoring (SHM) of civil engineering structures, e.g. bridges. SHM applications can potentially produce a high volume of sensing data, which consumes much transmission power and thus decreases the lifetime of the battery-run networks. We employ the network coding technique to improve the network efficiency and prolong its lifetime. By increasing the transmission power, we change the node connectivity and control the number of nodes that can overhear transmitted messages so as to hopefully realize the capacity gain by use of network coding. In Chapter 1, we present the background, to enable the reader to understand the need for SHM, advantages and drawbacks of WSNs and potential the application of network coding techniques has. In Chapter 2 we provide a review of related research explaining how it relates to our work, and why it is not fully applicable in our case. In Chapter 3, we propose to control transmission power as a means to adjust the number of nodes that can overhear a message transmission by a neighbouring node. However, too much of the overhearing by high power transmission consumes aggressively limited battery energy. We investigate the interplay between transmission power and network coding operations in Chapter 4. We show that our solution reduces the overall volume of data transfer, thus leading to significant energy savings and prolonged network lifetime. We present the mathematical analysis of our proposed algorithm. By simulation, we also study the trade-offs between overhearing and power consumption for the network coding scheme. In Chapter 5, we propose a methodology for the optimal placement of sensor nodes in linear network topologies (e.g., along the length of a bridge), that aims to minimise the link connectivity problems and maximise the lifetime of the network. Both simple packet relay and network coding are considered for the routing of the collected data packets towards two sink nodes positioned at both ends of the bridge. Our mathematical analysis, verified by simulation results, shows that the proposed methodology can lead to significant energy saving and prolong the lifetime of the underlying wireless sensor network. Chapter 6 is dedicated to the delay analysis. We analytically calculate the gains in terms of packet delay obtained by the use of network coding in linear multi-hop wireless sensor network topologies. Moreover, we calculate the exact packet delay (from the packet generation time to the time it is delivered to the sink nodes) as a function of the location of the source sensor node within the linear network. The derived packet delay distribution formulas have been verified by simulations and can provide a benchmark for the delay performance of linear sensor networks. In the Chapter 7, we propose an adaptive version of network coding based algorithm. In the case of packet loss, nodes do not necessary retransmit messages as they are able to internally decide how to cope with the situation. The goal of this algorithm is to reduce the power consumption, and decrease delays whenever it can. This algorithm achieves the delay similar to that of three-hop direct-connectivity version of the deterministic algorithm, and consumes power almost like one-hop direct-connectivity version of deterministic algorithm. In very poor channel conditions, this protocol outperforms the deterministic algorithm both in terms of delay and power consumption. In Chapter 8, we explain the direction of our future work. Particularly, we are interested in the application of combined TDMA/FDMA technique to our algorithm.Open Acces

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

Performance assessment & synergic operation of algorithmic solutions enabling opportunistic networks– D4.2

Deliverable D4.2 del projecte europeu OneFITPeer ReviewedPostprint (updated version

Compressive Data Gathering in Wireless Sensor Networks

The thesis focuses on collecting data from wireless sensors which are deployed randomly in a region. These sensors are widely used in applications ranging from tracking to the monitoring of environment, traffic and health among others. These energy constrained sensors, once deployed may receive little or no maintenance. Hence gathering data in the most energy efficient manner becomes critical for the longevity of wireless sensor networks (WSNs). Recently, Compressive data gathering (CDG) has emerged as a useful method for collecting sensory data in WSN; this technique is able to reduce global scale communication cost without introducing intensive computation, and is capable of extending the lifetime of the entire sensor network by balancing the forwarding load across the network. This is particularly true due to the benefits obtained from in-network data compression. With CDG, the central unit, instead of receiving data from all sensors in the network, it may receive very few compressed or weighted sums from sensors, and eventually recovers the original data. To prolong the lifetime of WSN, in this thesis, we present data gathering methods based on CDG. More specifically, we propose data gathering schemes using CDG by building up data aggregation trees from sensor nodes to a central unit (sink). Our problem aims at minimizing the number of links in the forwarding trees to minimize the number of overall transmissions. First, we mathematically formulate the problem and solve it using optimization program. Owing to its complexity, we present real-time algorithmic (centralized and decentralized) methods to efficiently solve the problem. We also explore the benefits one may obtain when jointly applying compressive data gathering with network coding in a wireless sensor network. Finally, and in the context of compressive data gathering, we study the problem of joint forwarding tree construction and scheduling under a realistic interference model, and propose some efficient distributed methods for solving it. We also present a primal dual decomposition method, using the theory of column generation, to solve this complex problem