Medium Access Control for Wireless Sensor Networks based on Impulse Radio Ultra Wideband

This paper describes a detailed performance evaluation of distributed Medium Access Control (MAC) protocols for Wireless Sensor Networks based on Impulse Radio Ultra Wideband (IR-UWB) Physical layer (PHY). Two main classes of Medium Access Control protocol have been considered: Slotted and UnSlotted with reliability. The reliability is based on Automatic Repeat ReQuest (ARQ). The performance evaluation is performed using a complete Wireless Sensor Networks (WSN) simulator built on the Global Mobile Information System Simulator (GloMoSim). The optimal operating parameters are first discussed for IR-UWB in terms of slot size, retransmission delay and the number of retransmission, then a comparison between IR-UWB and other transmission techniques in terms of reliability latency and power efficiency

Distributed Power Allocation for Sink-Centric Clusters in Multiple Sink Wireless Sensor Networks

Due to the battery resource constraints, saving energy is a critical issue in wireless sensor networks, particularly in large sensor networks. One possible solution is to deploy multiple sink nodes simultaneously. Another possible solution is to employ an adaptive clustering hierarchy routing scheme. In this paper, we propose a multiple sink cluster wireless sensor networks scheme which combines the two solutions, and propose an efficient transmission power control scheme for a sink-centric cluster routing protocol in multiple sink wireless sensor networks, denoted as MSCWSNs-PC. It is a distributed, scalable, self-organizing, adaptive system, and the sensor nodes do not require knowledge of the global network and their location. All sinks effectively work out a representative view of a monitored region, after which power control is employed to optimize network topology. The simulations demonstrate the advantages of our new protocol

Signal processing for distributed nodes in smart networks

With increasing environmental concern for energy conservation and mitigating climate change, next generation smart networks are bound to provide improved performance in terms of security, reliability, and energy efficiency. For instance, future smart networks will work in highly complex and dynamic environments and will have distributed nodes that need to interact with each other and may also interact with an energy provider in order to improve their performance. In this context, advanced signal processing tools such as game theory and distributed transmit beamforming can yield tremendous performance gains in terms of energy efficiency for demand management and signal trans-mission in smart networks. The central theme of this dissertation is the modeling of energy usage behavior of self-seeking distributed nodes in smart networks. The thesis mainly looks into two key areas of smart networks: 1) smart grid networks and 2) wireless sensor networks, and contains: an analytical framework of the economics of electric vehicle charging in smart grids in an energy constrained environment; a study of a consumer-centric energy management scheme for encouraging the consumers in a smart grid to voluntarily take part in energy management; an outage management scheme for efficiently curtailing energy from the consumers in smart grids in the event of a power outage; a comprehensive study of power control of sensors in a wireless sensor network using game theory and distributed transmit beamforming; and finally, an energy aware distributed transmit beamfoming technique for long distance signal transmission in a wireless sensor network. This thesis addresses the challenges of modeling the energy usage behavior of distributed nodes through studying the propriety of energy users in smart networks, 1) by capturing the interactions between the energy users and energy provider in smart grids using non-cooperative Stackelberg and generalized Nash games, and showing that the socially optimal energy management for users can be achieved at the solution of the games, and 2) by studying the power control of sensors in wireless sensor networks, using a non-cooperative Nash game and distributed transmit beamforming that demonstrates significant transmit energy savings for the sensors. To foster energy efficient transmission, the thesis also studies a distributed transmit beamforming technique that does not require any channel state information for long distance signal transmission in sensor networks. The contributions of this dissertation are enhanced by proposing suitable system models and appropriate signal processing techniques. These models and techniques can capture the different cost-benefit tradeoffs that exist in these networks. All the proposed schemes in this dissertation are shown to have significant performance improvement when compared with existing solutions. The work in this thesis demonstrates that modeling power usage behavior of distributed nodes in smart networks is both possible and beneficial for increasing the energy efficiency of these networks

Distributed Successive Approximation Coding using Broadcast Advantage: The Two-Encoder Case

Traditional distributed source coding rarely considers the possible link between separate encoders. However, the broadcast nature of wireless communication in sensor networks provides a free gossip mechanism which can be used to simplify encoding/decoding and reduce transmission power. Using this broadcast advantage, we present a new two-encoder scheme which imitates the ping-pong game and has a successive approximation structure. For the quadratic Gaussian case, we prove that this scheme is successively refinable on the {sum-rate, distortion pair} surface, which is characterized by the rate-distortion region of the distributed two-encoder source coding. A potential energy saving over conventional distributed coding is also illustrated. This ping-pong distributed coding idea can be extended to the multiple encoder case and provides the theoretical foundation for a new class of distributed image coding method in wireless scenarios.Comment: In Proceedings of the 48th Annual Allerton Conference on Communication, Control and Computing, University of Illinois, Monticello, IL, September 29 - October 1, 201

Energy efficient wireless sensor network protocols for monitoring and prognostics of large scale systems

In this work, energy-efficient protocols for wireless sensor networks (WSN) with applications to prognostics are investigated. Both analytical methods and verification are shown for the proposed methods via either hardware experiments or simulation. This work is presented in five papers. Energy-efficiency methods for WSN include distributed algorithms for i) optimal routing, ii) adaptive scheduling, iii) adaptive transmission power and data-rate control --Abstract, page iv

Novel Medium Access Control (MAC) Protocols for Wireless Sensor and Ad Hoc Networks (WSANs) and Vehicular Ad Hoc Networks (VANETs)

Efficient medium access control (MAC) is a key part of any wireless network communication architecture. MAC protocols are needed for nodes to access the shared wireless medium efficiently. Providing high throughput is one of the primary goals of the MAC protocols designed for wireless networks. MAC protocols for Wireless Sensor and Ad hoc networks (WSANs) must also conserve energy as sensor nodes have limited battery power. On the other hand, MAC protocols for Vehicular Ad hoc networks (VANETs) must also adapt to the highly dynamic nature of the network. As communication link failure is very common in VANETs because of the fast movement of vehicles so quick reservation of packet transmission slots by vehicles is important. In this thesis we propose two new distributed MAC algorithms. One is for WSANs and the other one is for VANETs. We demonstrate using simulations that our algorithms outperform the state-of-the-art algorithms

Intelligent energy efficient localization using variable range beacons in industrial wireless sensor networks

In many applications of industrial wireless sensor networks, sensor nodes need to determine their own geographic position coordinates so that the collected data can be ascribed to the location from where it was gathered. We propose a novel intelligent localization algorithm which uses variable range beacon signals generated by varying the transmission power of beacon nodes. The algorithm does not use any additional hardware resources for ranging and estimates position using only radio connectivity by passively listening to the beacon signals. The algorithm is distributed, so each sensor node determines its own position and communication overhead is avoided. As the beacon nodes do not always transmit at maximum power and no transmission power is used by unknown sensor nodes for localization, the proposed algorithm is energy efficient. It also provides control over localization granularity. Simulation results show that the algorithm provides good accuracy under varying radio conditions

Sidelobe Control in Collaborative Beamforming via Node Selection

Collaborative beamforming (CB) is a power efficient method for data communications in wireless sensor networks (WSNs) which aims at increasing the transmission range in the network by radiating the power from a cluster of sensor nodes in the directions of the intended base station(s) or access point(s) (BSs/APs). The CB average beampattern expresses a deterministic behavior and can be used for characterizing/controling the transmission at intended direction(s), since the mainlobe of the CB beampattern is independent on the particular random node locations. However, the CB for a cluster formed by a limited number of collaborative nodes results in a sample beampattern with sidelobes that severely depend on the particular node locations. High level sidelobes can cause unacceptable interference when they occur at directions of unintended BSs/APs. Therefore, sidelobe control in CB has a potential to increase the network capacity and wireless channel availability by decreasing the interference. Traditional sidelobe control techniques are proposed for centralized antenna arrays and, therefore, are not suitable for WSNs. In this paper, we show that distributed, scalable, and low-complexity sidelobe control techniques suitable for CB in WSNs can be developed based on node selection technique which make use of the randomness of the node locations. A node selection algorithm with low-rate feedback is developed to search over different node combinations. The performance of the proposed algorithm is analyzed in terms of the average number of trials required to select the collaborative nodes and the resulting interference. Our simulation results approve the theoretical analysis and show that the interference is significantly reduced when node selection is used with CB.Comment: 30 pages, 10 figures, submitted to the IEEE Trans. Signal Processin

Fixed chain-based wireless sensor network for intelligent transportation systems

Wireless Sensor Networks (WSNs) are distributed and interconnected wirelessly sensors that are used in a variety of fields of our daily life, such as the manufacturing, utility operations and traffic monitoring. Many WSN applications come with some technical weaknesses and issues, especially when they are used in Intelligent Transportation Systems (ITS). For ITS applications that use a fixed chain topology which contains road studs deployed at ground level, there are some challenges related to radio propagation, energy constraints and the Media Access Control (MAC) protocol. This thesis develops a ground level radio propagation model for communication between road studs, and energy efficiency metrics to manage the resources to overcome the energy constraints, as well as a MAC protocol compatible with chain topology and ground level communication. For the challenges of the physical layer, this thesis investigates the use of a WSN for communicating between road-based nodes. These nodes are situated at ground level, and two-way wireless communication is required between the nodes and from the nodes to a roadside control unit. Field measurements have been carried out to examine the propagation close to the ground to determine the maximum distance between road-based nodes as a function of the antenna height. The results show that for a frequency of 2.4 GHz, a range of up to 8m is achievable with 2mW equivalent isotropically radiated power (EIRP). An empirical near-ground level radio propagation model has been derived, and the predicted results from this model are shown to match closely to the measured results. Since wireless sensor networks have power constraints, green energy efficiency metrics have been proposed for low-power wireless sensors operating at ground level. A numerical analysis is carried out to investigate the utilisation of the green energy efficiency metrics for ground level communication in wireless sensor networks. The proposed metrics have been developed to calculate the optimal sensor deployment, antenna height and energy efficiency level for the near ground wireless sensor. As an application of the proposed metrics, the relationship between the energy efficiency and the spacing between the wireless sensor nodes has been studied. The results provide guidance for energy efficient deployment of near ground level wireless sensors. To manage the communication between large numbers of nodes deployed on a chain topology, this research presents a time division multiple access (TDMA) MAC protocol that is specifically designed for applications requiring periodic sensing of the sensor field. Numerical analysis has been conducted to investigate the optimum transmission scheduling based on the signal-to-interference-plus-noise-ratio (SINR) for ground level propagation model applied on wireless chain topology. The optimised transmission schedule considers the SINR value to enable simultaneous transmission from multiple nodes. The most significant advantages of this approach are reduced delay and improved Packet Received Ratio (PRR). Simulation is performed to evaluate the proposed protocol for intelligent transport system applications. The simulation results validate the MAC protocol for a fixed chain topology compared with similar protocols