Energy Efficiency of Coding Schemes for Underwater Wireless Sensor Networks

Underwater Wireless Sensor Networks (UWSNs) are used in applications such as mineral exploration and environmental monitoring, and must offer reliability and energy efficiency. These are related to each other in the sense that the former requires error-correction which in turn requires energy, consuming battery life in an environment where battery replacement and recharging are difficult. This chapter thus addresses the energy efficiency of three suitable error correction methods for UWSNs, namely Automatic Repeat Request (ARQ), Forward Error Correction (FEC) and Network Coding (NC). The performance of the schemes as a function of transmission distance is determined for various packet sizes by using models of attenuation and noise that represent the underwater environment. ARQ offers the lowest efficiency and NC the highest but there is a distance at which FEC becomes the best option rather than NC suggesting a hybrid FEC/NC method.

Object Tracking Algorithms in Wireless Sensor Networks

Mobile target tracking is one of the most important applications of wireless sensor networks (WSNs). But, the use of sensor networks for object tracking faces a number of issues in which the limited energy supply is the most important. So in target tracking problem, using methods to decrease the energy consumption as well as high accuracy and quality of tracking is the main goal. Hence, reducing the number of participant nodes in tracking phase, increasing the sleep duration of noninvolved nodes and decreasing the number of transmitted packets to the sink are the most referred methods. In this chapter the authors introduce the most suitable methods for energy efficient mobile object tracking.

RSS-Based Outdoor Localization with Wireless Sensor Networks in Practice

In this chapter the authors discuss the feasibility of sensor node localization by exploiting the inherent resources of WSN technology, such as the received signal strength (RSS) of the exchanged messages. The authors also present a brief overview of various factors influencing the RSS, including the RF-signal propagation and other topology parameters which influence the localization process and accuracy. Moreover, the RSS variability due to internal factors, related to the hardware implementation of a sensor node, is investigated in order to be considered in simulations of RSS-based outdoor localization scenarios. Localization considerations referring to techniques, topology parameters and factors influencing the localization accuracy are combined in simulation examples to evaluate their significance concerning target positioning performance. Finally, the RF propagation model and the topology parameters being identified are validated in real outdoor localization scenario.

Network Design and Performance Evaluation of Wireless Sensor Network for Precision Agriculture

This chapter explores the design of wireless sensor networks for applications in precision agriculture. A short review of developments in precision agriculture and recent applications of wireless sensor networks in the area is presented. The authors present their design of medium access control and network layer protocols exploring the challenges and opportunities associated with the design of such a networked system. The physical layer in their network allows multiple power modes in both receive and transmit operations. The MAC layer employs these multiple power modes to implement a novel wake-up synchronization mechanism to reduce the energy overhead. The network layer ensures reliable collection of data while balancing the energy consumption among the nodes. Finally, the authors present an analytical approach to model the behavior of the MAC protocol developed and compare it against the duty-cycle based S-MAC protocol. The results are also confirmed using simulations.

HTNMote

The safety of rail transportation has always been the top priority for the Federal Railroad Administration (FRA). Legacy technology is still largely relied upon for detection of faults. Modern technology is mostly used to detect a particular railcar rather than to monitor it for problems. Wireless Sensor Network (WSN) technology is being evaluated by the railroads for real-time or near real-time monitoring of the railcar status for timely response to problems and for trend analysis. In this chapter the authors first highlight the importance of freight rail transportation, followed by briefly discussing specific wireless technologies of interest. In particular, the authors present the shortcomings of the ZigBee protocol in the application domain of railcar monitoring. The authors then introduce hybrid technology protocol. Finally, the authors discuss HTNMote, a hardware platform to implement hybrid technology network and present the results of tests showing the benefits of the new protocol and hardware.

Fault-Diagnosis and Decision Making Algorithm for Determining Faulty Nodes in Malicious Networks

This chapter addresses fault diagnosis agreement problem in a network with malicious members. The authors provide a new algorithm to reach an agreement among fault-free members about the faulty ones. The algorithm is designed for fully-connected networks and also can be easily adapted to partially connected networks. The authors contribution is to reduce bit complexity of Byzantine agreement process by detecting the same list of faulty units in all fault-free members. Therefore, the malicious units can be removed from other consensus processes. Also, each healthy unit detects a list of malicious units locally which results in lower packet transmission in the network. The authors provided algorithm solves fault diagnosis agreement problem in 2t+1 rounds and O(nt+1) bit complexity for each member.

Distributed Adaptive Parametric Power Spectral Estimation Using Wireless Sensor Networks

Spectrum analysis is one of the momentous fields in signal processing. It has a large variety of applications in radar, sonar, speech and image processing. Parametric methods have been proposed and employed for spectrum analysis including power spectral density (PSD) estimation. These methods estimate the parameters of a statistical model and compute the PSD, afterwards. In some circumstances one is obliged to deal with observations of numerous geographically dispersed sensors, to either increase the precision or based on application demands. Having a set of sensors linked together to take the advantages of cooperation and network topology, one obtains a more comprehensive estimation. In this chapter, the authors propose and study four different algorithms capable of facing spatio-temporal variations for parametric modeling and PSD estimation using wireless sensor networks (WSNs). For this purpose, the authors first validate the proposed algorithms using theoretical and mathematical formulations. Thereafter, performing simulation tasks demonstrates and supports the theoretical achievements. The next section of the chapter illustrates the concepts to a greater degree, the authors analyze and compare the performance of these algorithms with each other, as well as with the simple PSD estimation using individual sensors, wherein there is no cooperation among the nodes.

Reliability Evaluation Methods for Resilient Wireless Sensor Networks

Wireless sensor networks (WSNs) are deployed for various applications such as military applications, environmental monitoring, security and surveillance, health care applications and so on. In most of these applications, reliable data transport is of great importance and also a facet of quality of service (QoS). This chapter discusses reliable data transport approaches and protocols. The presented protocols should be energy efficient besides they guarantee reliability in data transmission. The authors review protocols mostly based on packet and event reliability taking advantage of retransmission and redundancy mechanisms. In addition, network component failures and fault tolerant techniques should be also considered in reliable WSN designs. Since different reliability evaluation modeling approaches is presented. Finally the authors highlight the challenges to WSNs reliability enhancement and some future research directions are addressed in particular.

Prevalence of Anomalies in Real World Sensor Network Deployments

Sensor network deployments have enabled automated data collection at a finer granularity compared to human-centric sparse deployments of traditional telemetric data loggers. However, this fine granularity cannot be achieved in the presence of failing nodes, frequent network failures, and/or potentially malicious network behaviors. Moreover, given a perfect and secure network with long-lived sensor nodes, the collected sensor data should be fault-free to guarantee quality of reasoning. Unlike traditional devices, wireless sensor motes are resource-constrained battery-powered devices equipped with few on-board sensors which are susceptible to failures, and batteries cannot always be reliably recharged. Over the years, sensor network deployments have materialized a large number of monitoring and event-detection applications. Researchers and decision makers have observed several anomalous patterns ranging from functional failures to pervasive sensing faults in most of these deployments. In this chapter, we discuss a few of these deployments to emphasize the need for an anomaly detection mechanism.

Adaptive IEEE 802.15.4 MAC Protocol for Wireless Sensor Networks

The energy efficiency is a main challenging issue for employing wireless sensor networks (WSNs) in extreme environments where the media access progress consumes the main part of network energy. The IEEE 802.15.4 is adopted in low complexity, ultra-low power and low data rate wireless sensor applications where the energy consumption of nodes should be managed carefully in harsh and inaccessible environments. The beacon-enabled mode of the IEEE 802.15.4 provides a power management scheme. When the network traffic is variable, this mode does not work as well and the coordinator is not capable for estimating the network traffic and adjusting proper duty cycle dynamically. In this chapter an approach for estimating network traffic in star topology is proposed to overcome this issue where the coordinator could estimate the network traffic and dynamically adjusts duty cycle proportion to the variation of network traffic. The simulation results demonstrate the superiority of proposed approach for improving the energy consumption, throughput and delay in comparison with the IEEE 802.15.4 under different traffic conditions.