In this thesis, we propose a suite of Evolutionary Algorithms (EA)-based protocols to solve the problems of clustering and routing in Wireless Sensor Networks (WSNs). At the beginning, the problem of the Cluster Heads (CHs) selection in WSNs is formulated as a single-objective optimization problem. A centralized weighted-sum multi-objective optimization protocol is proposed to find the optimal set of CHs. The proposed protocol finds a predetermined number of CHs in such way that they form one-hop clusters. The goal of the proposed protocol is to enhance the network's energy efficiency, data delivery reliability and the protocol's scalability. The formulated problem has been solved using three evolutionary approaches: Genetic Algorithms (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) and we assessed each of their performance. Then, a PSO-based hierarchical clustering protocol that forms two-hop clusters is proposed to investigate the effect of the number of CHs on network's energy efficiency. This protocol enhances the WSN's energy efficiency by setting an upper bound on the number of CHs and trying to minimize the number of CHs compared to that upper bound. It also maximizes the protocol's scalability by using two-hop communication between the sensor nodes and their respective CHs. Then, a centralized weighted-sum PSO-based protocol is proposed for finding the optimal inter-cluster routing tree that connects the CHs to the Base Station (BS). This protocol is appropriate when the CHs are predetermined in advance. The proposed protocol uses a particle encoding scheme and defines an objective function to find the optimal routing tree. The objective function is used to build the trade-off between the energy-efficiency and data delivery reliability of the constructed tree. Finally, a centralized multi-objective Pareto-optimization approach is adapted to find the optimal network configuration that includes both the optimal set of CHs and the optimal routing tree. A new individual encoding scheme that represents a joint solution for both the clustering and routing problems in WSNs is proposed. The proposed protocol uses a variable number of CHs, and its objective is to assign each network node to its respective CH and each CH to its respective next hop. The joint problem of clustering and routing in WSNs is formulated as a multi-objective minimization problem with a variable number of CHs, aiming at determining an energy efficient, reliable ( in terms of data delivery) and scalable clustering and routing scheme. The formulated problem has been solved using two state-of-the-art Multi-Objective Evolutionary Algorithms (MOEA), and their performance has been compared. The proposed protocols were developed under realistic network settings. No assumptions were made about the nodes' location awareness or transmission range capabilities. The proposed protocols were tested using a realistic energy consumption model that is based on the characteristics of the Chipcon CC2420 radio transceiver data sheet. Extensive simulations on 50 homogeneous and heterogeneous WSN models were evaluated and compared against well-known cluster-based sensor network protocols.

Wireless Sensor Networks (WSNs) have been applied to a wide range of application areas, including battle fields, transportation systems, and hospitals. The security issues in WSNs are still hot research topics. The constrained capabilities of sensors and the environments in which sensors are deployed, such as hostile and non-reachable areas, make the security more complicated. This dissertation describes the development and testing of a novel two-phase security mechanism for hierarchical WSNs that is capable of defending both outside and inside attacks. For the outside attacks, the attackers are usually malicious intruders that entered the network. The computation and communication capabilities of the sensors restrict them from directly defending the harmful intruders by performing traditionally encryption, authentication, or other cryptographic operations. However, the sensors can assist the more powerful nodes in a hierarchical structured WSN to track down these intruders and thereby prevent further damage. To fundamentally improve the security of a WSN, a multi-target tracking algorithm is developed to track the intruders. For the inside attacks, the attackers are compromised insiders. The intruders manipulate these insiders to indirectly attack other sensors. Therefore, detecting these malicious insiders in a timely manner is important to improve the security of a network. In this dissertation, we mainly focus on detecting the malicious insiders that try to break the normal communication among sensors, which creates holes in the WSN. As the malicious insiders attempt to break the communication by actively using HELLO flooding attack, we apply an immune-inspired algorithm called Dendritic Cell Algorithm (DCA) to detect this type of attack. If the malicious insiders adopt a subtle way to break the communication by dropping received packets, we implement another proposed technique, a short-and-safe routing (SSR) protocol to prevent this type of attack. The designed security mechanism can be applied to different sizes of both static and dynamic WSNs. We adopt a popular simulation tool, ns-2, and a numerical computing environment, MATLAB, to analyze and compare the computational complexities of the proposed security mechanism. Simulation results demonstrate effective performance of the developed corrective and preventive security mechanisms on detecting malicious nodes and tracking the intruders.

No / Wireless sensor networks are an emerging technology for low-cost, unattended monitoring of a wide range of environments. Their importance has been enforced by the recent delivery of the IEEE 802.15.4 standard for the physical and MAC layers and the forthcoming ZigBee standard for the network and application layers. The fast progress of research on energy efficiency, networking, data management and security in wireless sensor networks, and the need to compare with the solutions adopted in the standards motivates the need for a survey on this field.

The work described in this thesis is concerned with self-localisation (automated estimation of sensor locations) and source-localisation (location of a target) using Wireless Sensor Networks (WSNs). The motivation for the research in this thesis is the on-line localisation of marmots from their alarm calls. The application requires accurate 3D self-localisation (within a small percentage of sensor spacing) as well as timely operation. Further challenges are added by the high data-rate involved: sensor nodes acquire data at a rate that is greater than the available network bandwidth. This data cannot be streamed over a multi-hop network, implying a need for data reduction through in-network event detection and local data compression or filtering techniques. The research approach adopted in this thesis combined simulation, emulation and real-life experimentation. Real-life deployment and experimentation highlighted problems that could not be predicted in controlled experiments or simulation. Emulation used data gathered from controlled, real-life experimentation to simulate proposed system refinements; this was sufficient to provide a proof-of-concept validation for some of the concepts developed. Simulation allowed the understanding of underlying theoretical behaviour without involving the complex environmental effects caused by real-life experimentation. This thesis details contributions in two distinct aspects of localisation: acoustic ranging and end-toend deployable acoustic source localisation systems. With regard to acoustic ranging and 3D localisation, two WSN platforms were evaluated: one commercially available, but heavily constrained (Mica2) and one custom-built for accurate localisation (Embedded Networked Sensing Box (ENSBox)). A new proof of concept platform for acoustic sensing (based on the Gumstix single-board computer) was developed by the author (including the implementation of a ranging mechanism), based on experiences with the platforms above. Furthermore, the literature was found to lack a specific procedure for evaluation and comparison of self-localisation algorithms from theoretical conception to real-life testing. Therefore, an evaluation cycle for self-localisation algorithms that encompassed simulation, emulation and real-life deployment was developed. With respect to source localisation, a hardware and software platform named VoxNet was designed and implemented.

We use tools and techniques from information theory to improve the design of Wireless Sensor Networks (WSNs). We do this by first developing a model for WSNs that is analogous to models of communication systems in information theory. In particular, we define the notion of WSN Coding, which is analogous to source coding from information theory, and the Collection Channel, which is analogous to a transport channel in information theory. We then use source coding theorems from information theory to develop three results that aid in WSN design. First, we propose a new top-level design metric for WSNs. Second, we develop an efficiency measure for the sensing process in a WSN. Finally, we use techniques from source coding schemes to suggest new designs for WSNs and the sensors they contain. We strive for tools that apply under the most general conditions possible so that designers can use them in any WSN. However, we also apply each tool to a specific example WSN illustrate the tool's value.

Recent advances in Micro Electro-Mechanical Systems technology, wireless communications, and digital electronics have enabled the development of low-cost, low-power, multifunctional sensor nodes that are small in size and communicate untethered in short distances. These tiny sensor nodes, which consist of sensing, data processing, and communicating components, leverage the idea of sensor networks based on collaborative effort of a large number of nodes. A wide range of applications utilizing low-end sensor nodes to collaborative work together is envisioned for sensor networks. Some of the application areas are health, military, and security. For example, sensor networks can be used to detect foreign chemical agents in the air and the water. They can help to identify the type, concentration, and location of pollutants. In essence, sensor networks will provide the end user with intelligence and a better understanding of the environment. Realization of these and other sensor network applications require certain fundamental protocols and schemes. The objective of this thesis is to provide some of the basic building blocks that are necessary for sensor networks. These basic blocks are in the areas of routing, time synchronization, and localization. The routing protocol allows different types of traffics to be delivered and fused during delivery to lower the amount of information exchange. The time synchronization protocol enables the sensor nodes to maintain a similar time while the localization technique provides a way to find the sensor nodes in the sensor field. The routing, time synchronization, and localization schemes may be used to provide Quality-of-Service when data is gathered from the sensor networks.

Thesis (M.S.)--Auburn University, 2008. / Abstract. Vita. Includes bibliographical references (p. 94-101).

Includes bibliographical references (p. 115-121).

Sensor networks including opportunistic networks of sensor-equipped smartphones as well as networks of embedded sensors can enable a wide range of applications including environmental monitoring, smart grids, intelligent transportation, and healthcare. In most real-world applications, to meet end-user requirements, the network operator needs to define and update the sensors' tasks dynamically, such as updating the parameters for sensor data collection or updating the sensors' code. Tasking sensor networks is necessary to reduce the effort in programming sensor networks. However, it is challenging due to dynamics and scale in terms of number of nodes, number of tasks, and sensing regions of the networks. In addition, tasking sensor networks must also be efficient in terms of bandwidth, latency, energy consumption, and memory usage. This dissertation identifies and addresses the problems of scalability and efficiency in tasking sensor networks. The first challenge in tasking sensor networks is to define a mechanism that represents multiple tasks and sensor groups efficiently taking into account the heterogeneity and mobility of sensors deployed over a large geographical region. Another challenge in tasking sensor networks in general, and embedded sensor networks in particular, is to design protocols that can not only efficiently disseminate tasks but also maintain a consistent view of the task to be performed among inherently unreliable and resource-limited sensors. We believe that a scalable and efficient tasking framework can greatly benefit the development and deployment of sensor network applications. Our thesis is that decoupling the task specification from task implementation using a spatial two-dimensional (2D) representation of a tasking region such as maps enables scalable, efficient, and resource-adaptive tasking over heterogeneous mobile sensor networks. In addition, reducing overhead in detecting inconsistencies across nodes enables scalable and efficient task dissemination and maintenance. We present the design, implementation, and evaluation of Zoom, a multiresolution tasking framework that efficiently encapsulates multiple tasks and sensor groups for sensor networks deployed in a large geographical region. The key ideas in Zoom are (i) decoupling task specification and task implementation to support heterogeneity, (ii) using maps for representing spatial sensor groups and tasks to scale with the number of sensor groups and sensing regions, and (iii) using image encoding techniques to reduce the map size and provide adaptation to sensor platforms with different resource capabilities. We present the design, implementation, and evaluation of our protocol, DHV, which efficiently disseminates task content and ensures that all nodes have up-to-date task content in sensor networks. It achieves this by minimizing both the redundant information in each message and the number of transmitted messages in the networks. DHV has been included in the official distribution of TinyOS, a popular operating system for embedded sensor networks. As sensor networks continue to develop, they will evolve from dedicated and single-purpose systems to open and multi-purpose large scale systems. Nodes in the network will be retasked frequently to support multiple applications and multiple users. We believe that this work is an important step in enabling seamless interaction between users and sensor networks and to make sensor networks more widely adopted.

International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California / Sensor network applications typically require continuous monitoring of physical phenomena for extended periods of time under severe energy resource constraints. Accordingly, design considerations for sensor Media Access Control (MAC) protocols depart significantly from those of traditional wireless MAC protocols that largely ignore the energy factor. In this paper, we reexamine the design space of wireless sensor MAC protocols and modify IEEE 802.11 Distributed Coordination Function (DCF) to incorporate energy-adaptive contention mechanisms for prolonging sensor lifetime. Performance of the proposed schemes is evaluated with DCF as a baseline and results indicate the benefits of energy-aware mechanisms for sensor MAC protocols.