International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California / This paper presents the design and development of a fluorometry sensor network with LED excitation. The design of the electronics in junction with the capability of LED excitation will significantly reduce the size and costs of the flrorometer units. The coverage and effectiveness of the sensing and monitoring capability will also be greatly enhanced by the addition of the wireless networks.

Wireless sensor actuator networks (WSANs) are becoming a solution for the implementation of control applications. Sensors and actuators can be deployed forming a large or dense network to monitor and control physical parameters or systems. However, this comes with challenges. Reliable data transmission and real-time communication constraints are the most significant challenges in WSANs for control applications because wireless networks are characterised by harsh transmission conditions. The use of WSANs for critical control applications has not gained sufficient progress as wireless networks are perceived to be totally unreliable and hence unsuitable. This makes reliable data transmission a priority in this research. Control applications will have a number of quality of service (QoS) requirements, such as requiring a very low packet-loss rate (PLR), minimum delay and guaranteed packet delivery. The overall goal of this research is to develop a framework that ensures reliable and real-time communication within the sensor network. A totally reliable network design involves ensuring reliability in areas such as the medium access control, connectivity, scalability, lifetime, clustering and routing with trade-offs such as energy consumption, system throughput and computational complexity. In this thesis, we introduce a unique method of improving reliability and real-time communication for control applications using a link quality routing mechanism which is tied into the ZigBee addressing scheme. ZigBee routing protocols do not consider link quality when making routing decisions. The results based on common network test conditions give a clear indication of the impact on network performance for various path loss models. The proposed link quality aware routing (LQAR) showed a highly significant 20.5% improvement in network delays against the ZigBee hierarchical tree routing (HTR) protocol. There is also a 17% improvement in the PLR. We also investigate variable sampling to mitigate the effects of delay in WSANs using a neural network delay predictor and observer based control system model. Our focus on variable sampling is to determine the appropriate neural network topology for delay prediction and the impact of additional neural network inputs such as PLR and throughput. The major contribution of this work is the use of typical obtainable delay series for training the neural network. Most studies have used random generated numbers which are not a correct representation of delays actually experienced in a wireless network. In addition, results show that the use of network packet loss information improves the prediction accuracy of delay. Our results show that adequate prediction of the time-delay series using the observer based variable sampling model influences the performance of the control system model under the assumptions and stated conditions.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / The use of wireless data networks is ubiquitous in the consumer world. They have gained significant traction due to advantages afforded by the lack of wires. These same advantages can prove valuable in Flight Test for data acquisition. Sensor nodes are ideal candidates for low bandwidth wireless networks. Located in remote, hard to reach and hostile environments, wirelessly acquiring data from such sensor can solve a number of existing issues for FTI engineers. Implementing such wireless communication introduces a number of challenges such as guaranteeing reliable transfer of the sensor data and time synchronization of the remote nodes. This paper addresses wireless sensor acquisition, the associated challenges and discusses approaches and solutions to these problems.

published_or_final_version / Computer Science / Master / Master of Philosophy

Rapid advances in hardware technology are making it possible to manufacture different types of Sensor Nodes (SN) that results in fast growing heterogeneous Wireless Sensor Networks (WSNs). These WSN’s are applicable for a wide range of applications relevant for military, industry and domestic use. However, WSNs have particular features such as scarce resources which can affect their performance. In addition, WSNs are subject to experience changes that can occur both within the condition of the network, due to factors such as node mobility or node failure (prevalent in harsh environments), and with regards to user requirements. Consequently, it is vital for WSNs to sense the current network conditions and user requirements to be able to perform efficiently. Cognition is necessarily introduced in WSNs as a response to this need. Cognition in the context of WSNs deals with the ability to be aware of the environment and user requirements and to proactively adapt to changes. This thesis proposes a hierarchical architecture along with a cognitive network management protocol capable of enabling cognition in WSNs. Specifically; this research introduces Cognitive Nodes (CN) into WSNs so that they can manage the cognitive network. The cognitive network management process is composed of three sub-processes: 1) scanning the network, 2) decision-making, and 3) updating the nodes from taken decisions.Scanning the network process aims to provide an awareness of current network conditions. Therefore, at the first execution, each CN creates a profile table for each node in its purview and updates the tables periodically during the network operation. In decision making process, CNs make necessary decisions in terms of the working state of SNs (active/sleep), the duration of this state, and the Frequency of Sensing (FoS). Decision making process uses an optimization scheme to find the optimal number of active SNs in order to prolong the lifetime of the network. Finally, the nodes will be informed of the taken decisions. Based on the simulation and implementation results, the proposed cognitive WSN shows a significant enhancement in terms of the network’s longevity, its ability to negotiate competing objectives, and its ability to serve users more efficiently. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2013-03-04 12:39:24.502

The resilience of wireless sensor networks is investigated. A key concept is that scale-free network principles can be adapted to artificially create resilient wireless sensor networks. As scale-free networks are known to be resilient to errors but vulnerable to attack, a strategy using "cold-start" diversity is proposed to reduce the vulnerability to attacks. The IEEE 802.15.4 MAC and ZigBee protocols are investigated for their ability to form resilient clusters. Our investigation reveals there exists deficiencies in these protocols and the possibility of selfdirected and attack-directed denial-of-service is significant. Through insights gained, techniques are recommended to augment the protocols, increasing their resilience without major changes to the standard itself. Since both topological and protocol resilience properties are investigated, our results reveal important insights. Simulation of the physical and media access control layers using ns-2 is carried out to validate key concepts and approach.

A wireless sensor network is a network consisting of spatially distributed, sometimeautonomous sensors, communicating wirelessly to cooperatively achieve some task. For example, a wireless sensor network may be used for habitat monitoring to ascertain the environment’s temperature, pressure, humidity, etc. In order for a wireless sensor network to provide such data, one needs to ensure there is connectivity between nodes. That is, nodes can communicate to exchange information. To analyze connectivity between sensors, the radio communication range of each sensor, also called the communication footprint, needs to be known. To date, the models used to analyze a sensor’s radio communication footprint have been overly simplistic (i.e., isotropic) and thus yield results not found in practice. Footprints are highly dependent on the deployment environments, which are typically heterogeneous and non-isotropic in structure. In this work, a ‘weak-monotonicity’ (W-M) model is leveraged to represent a footprint’s non-isotropic behavior. The work also considers the heterogeneity of the environment through the use of the log-normal shadowing model. In particular, the usable percentage of the W-M footprint (the area where the power exceeds the receiver threshold) in such environments is considered through analysis and simulation. We then develop an enhanced footprint model which overlays multiple W-M patterns and use this method to represent experimental propagation data. The work also considers the use of graph theory methods to analyze the connectivity of randomly deployed networks in nonhomogeneous, non-isotropic environments.

University of Macau / Faculty of Science and Technology. / Department of Electrical and Computer Engineering

Recent advances in micro-electro-mechanical systems (MEMS) fabrication have made it possible to construct miniature devices containing an embedded system with strong computing capabilities. New generations of low cost sensor nodes can be created small with powerful computing and sensing capabilities. The small sensor nodes together with distributed wireless networking techniques enable the creation of innovative self-organized and peer-to-peer large scale wireless sensor networks (WSNs). A coordinated network of sensor nodes can perform distributed sensing of environmental phenomena over large-scale physical spaces and enable reliable monitoring and control in various applications. WSNs provide bridges between the virtual world of information technology and the real physical world. They represent a fundamental paradigm shift from traditional inter-human personal communications to autonomous inter-device communications. This thesis investigates the problems of target detection and tracking in WSNs. WSNs have some unique advantages over traditional sensor networks. However, the severe scarcity of power, communication and computation resources imposes some major challenges on the design and applications of distributed protocols for WSNs. In particular, this thesis focuses on two aspects of remote target detection and tracking in WSNs: distributed source coding (DSC) and sensor node localization. The primary purpose is to improve the application performance while minimizing energy consumption and bandwidth overhead.

This document presents the Centralized Energy Management System (CEMS), a dynamic fault-tolerant reclustering protocol for wireless sensor networks. CEMS reconfigures a homogeneous network both periodically and in response to critical events (e.g. cluster head death). A global TDMA schedule prevents costly retransmissions due to collision, and a genetic algorithm running on the base station computes cluster assignments in concert with a head selection algorithm. CEMS' performance is compared to the LEACH-C protocol in both normal and failure-prone conditions, with an emphasis on each protocol's ability to recover from unexpected loss of cluster heads.