Planning device deployment is a fundamental issue in implementing wireless sensor network (WSN) applications. This design practice determines types, numbers and locations of devices in order to build a powerful and effective system using devices of limited energy supply and constrained capacities. The deployment plan decides the limits of many intrinsic properties of a WSN, such as coverage, connectivity, cost, and lifetime. In this thesis, we address the device deployment planning issues related to large-scale WSN systems. We consider a typical deployment planning scenario in a heterogeneous two-tier WSN composed of sensor nodes and relay nodes. Sensor nodes form the lower tier of the network and are responsible for providing satisfactory sensing coverage to the application. Relay nodes form the upper tier of the network and they are responsible for forwarding data from sensor nodes to the base station. As so, relay nodes should provide reliable connectivity to sensor nodes for an extended period of time. We therefore address the sensor node deployment in terms of the sensing coverage and relay node deployment in terms of the communication connectivity and system lifetime. For sensor node deployment, we propose a coverage-guaranteed sensor node deployment design technique. Using this technique, the sensing coverage is complete even if sensor nodes are randomly dispersed within a bounded range from its target locations according to a given grid pattern. In order to curb the increased cost due to extra sensor nodes that are used in the coverage-guaranteed deployment, while still maintaining a high-quality sensing coverage, we further study the probabilistic properties of the grid-based sensor node deployment in the presence of deployment errors. For relay node deployment, we propose to extend the system lifetime by distributing relay nodes according to a density function, which is optimized in response to the energy consumption rate, so that the energy is dissipated at an approximately same rate across the network. We further craft the deployment density function to reconcile the needs of balanced energy consumption and strong sensor node connectivity. The techniques proposed in this thesis fill the blank of available literature and can serve as guidelines for WSN designers, solution providers and system integrators of WSN applications. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2008-01-15 09:33:53.917

Wireless sensor networks have applications in many places from wildlife environments to urban areas. Implementation of such a network is a challenging task because each specific application may require different constraints and objectives. To better meet the application requirements, cognitive wireless sensor network has been recently introduced. However, almost all the previous work in this area has been in theory or by simulation. Hence there is a demand to provide implementable ideas of cognition, implement, and analyze the results. The goal of this thesis is to implement a cognitive wireless sensor network with application in environment monitoring which is aware of the surrounding environment, updates its information based on the dynamic changes in the network status, makes appropriate decisions based on the gained awareness, and forwards required actions to involving nodes. An implementable cognitive idea is proposed based on the characteristics and goals of a cognitive system. Since transmission is one of the most power consuming processes in sensor nodes and non-efficient transmissions of data can lead to a shorter lifetime, this work tries to schedule nodes' transmission rate by the means of cognition and benefits from efficient scheduling of the redundant nodes to improve lifetime. To enhance a wireless sensor network with cognition, new nodes should be added to the architecture called cognitive nodes. Cognitive nodes will take care of most of the tasks in the cognition process while still there is a need to add a level of cognition to each individual node. The main contribution of this work is that it provides an implementable approach to cognition in wireless sensor networks, proposes a low complexity and low cost implementable idea for cognition, addresses implementation issues, and provides experimental results of different setups of the cognitive wireless sensor network. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2011-09-27 00:38:12.455

Prolonging the battery lifetime of sensors has been one of the most important issues in wireless sensor networks (WSNs). With the development of Wireless Power Transfer (WPT) technology, sensors can be recharged and possibly have infinite lifetime. One common approach to achieving this is having a wireless charging vehicle (WCV) move in the system coverage area and charge sensors nearby when it stops. The duration that the WCV stays at each charging location, the amount of traffic that each sensor carries, and the transmission power of individual sensors are closely related, and their joint optimization affects not only the data transmissions in the WSN but also energy consumption of the system. This problem is formulated as a mixed integer and nonconvex optimization problem. Different from existing work that either solves similar problems using genetic algorithms or considers charging sensors based on clusters, we consider the optimum charging time for each sensor, and solve the joint communication and charging problem optimally. Numerical results demonstrate that our solution can significantly reduce the average power consumption of the system, compared to the cluster-based charging solution. / Thesis / Master of Applied Science (MASc) / In a wireless sensor network (WSN), sensor nodes monitor the physical environment and forward the collected data to a data sink for further processing. Sensors are battery powered and, therefore, prolonging the lifetime of their batteries is critically important. In a rechargeable WSN (RWSN), prolonging the battery lifetime of sensors is achieved through reducing communication energy and recharging the batteries periodically. Reducing the communication energy consumption is done through choosing the best forwarding sensors (i.e., routing) for data collected by each sensor and deciding the transmission power of each sensor (i.e., power allocation). Recharging the batteries is achieved through harvesting energy from external sources. In this thesis, we consider a RWSN that uses wireless power transfer as the energy harvesting technology and jointly optimizes charging and communications in order to minimize the power consumption of the RWSN.

The coverage and energy issues are the fundamental problems which prevent the development of wireless sensor networks. In order to accurately evaluate the monitoring quality (coverage), one needs to model the interactive of sensors, phenomenons and the environment. Furthermore, in collaborative with scheduling algorithm and computer optimization, protocols can improve the overall monitoring quality and prolong the lifetime of network. This thesis is an investigation of coverage problem and its relative applications in the wireless sensor networks. We first discuss the realistic of current boolean sensing model and propose an irregular sensing model used to determine the coverage in the area with obstacles. We then investigate a joint problem of maintaining the monitoring quality and extending the lifetime of network by using scheduling schemes. Since the scheduling problem is NP hard, genetic algorithm and Markov decision process are used to determine an achievable optimal result for the joint problem of coverage-preserving and lifetime-prolong. In order to avoid the cost of centralized or distributed scheduling algorithms, a localized coverage-preserving scheduling algorithm is proposed by exploring the construction process of Voronoi diagram. Besides exploring the coverage characteristic in a static wireless sensor network, we investigate the coverage problem when the mobile elements are introduced into network. We consider the single-hop mobile data gathering problem with the energy efficiency and data freshness concerns in a wireless sensor network where the connectivity cannot be maintained. We first investigate the upper/lower bound of the covering time for a single collector to cover the monitoring area. Through our investigation we show that for a bounded rectangle area a hexagon walk could explore the area more efficiently than a random walk when the edges of area are known. We then propose a virtual force mobile model (VFM) in which the energy consumption for data transmission is modeled as a virtual elastic force and used to guide of mobile collectors to move to optimal positions for energy saving.

Using multi-agent systems to execute a variety of missions such as environmental monitoring and target tracking has been made possible by the advances in control techniques and computational capabilities. Communication abilities between agents allow them to coact and execute several coordinated missions, among which there is optimal coverage. The optimal coverage problem has several applications in engineering theory and practice, as for example in environmental monitoring, which belongs to the broad class of resource allocation problems, in which a finite number of mobile agents have to be deployed in a given spatial region with the assignment of a sub-region to each agents with respect to a suitable coverage metric. The coverage metric encodes the sensing performance of individual agent with respect to points inside the domain of interest, and a distribution of risk density. Usually the risk density function measures the relative importance assigned to inner regions. The optimal coverage problem in which the risk density is time-invariant has been widely studied in previous research. The solution to this class of problems is centroidal Voronoi tessellation, in which each agent is located on the centroid of the related Voronoi cell. However, there are many scenarios that require to be modelled by time-varying risk density rather than time-invariant one, as for example in area coverage problems where the environment evolves independently of the evolution for the robotic agents deployed to cover the area. In this work, the changing environment is modeled by a time-varying density function which is governed by a convection-diffusion equation. Mixed boundary conditions are considered to model a scenario in which a diffusive substance (e.g., oil from a leaking event or radioactive material from a nuclear accident) enters the area with convective component from the boundary. A non-autonomous feed- back law is employed whose generated trajectories maximize the coverage metric. The asymptotic stability of the multi-agent system is proven by using Barbalat’s lemma, and then theoretical predictions are illustrated by several simulations that represent idealized scenarios.

The coverage and energy issues are the fundamental problems which prevent the development of wireless sensor networks. In order to accurately evaluate the monitoring quality (coverage), one needs to model the interactive of sensors, phenomenons and the environment. Furthermore, in collaborative with scheduling algorithm and computer optimization, protocols can improve the overall monitoring quality and prolong the lifetime of network. This thesis is an investigation of coverage problem and its relative applications in the wireless sensor networks. We first discuss the realistic of current boolean sensing model and propose an irregular sensing model used to determine the coverage in the area with obstacles. We then investigate a joint problem of maintaining the monitoring quality and extending the lifetime of network by using scheduling schemes. Since the scheduling problem is NP hard, genetic algorithm and Markov decision process are used to determine an achievable optimal result for the joint problem of coverage-preserving and lifetime-prolong. In order to avoid the cost of centralized or distributed scheduling algorithms, a localized coverage-preserving scheduling algorithm is proposed by exploring the construction process of Voronoi diagram. Besides exploring the coverage characteristic in a static wireless sensor network, we investigate the coverage problem when the mobile elements are introduced into network. We consider the single-hop mobile data gathering problem with the energy efficiency and data freshness concerns in a wireless sensor network where the connectivity cannot be maintained. We first investigate the upper/lower bound of the covering time for a single collector to cover the monitoring area. Through our investigation we show that for a bounded rectangle area a hexagon walk could explore the area more efficiently than a random walk when the edges of area are known. We then propose a virtual force mobile model (VFM) in which the energy consumption for data transmission is modeled as a virtual elastic force and used to guide of mobile collectors to move to optimal positions for energy saving.

This Master’s report presents the research leading to the development of a low power Wireless Sensor Network (WSN) and a discussion of an implementation of the WSN. This report assesses the power reduction techniques further by reviewing their influences upon functionality, throughput, latency, and data reliability. The software techniques were implemented on evaluation boards and actual performance gains were observed. Furthermore, the report provides insight into the selection of the processor, wireless protocol, and WSN architecture by comparing other options in regards to the power reduction, functionality, and data reliability. The architecture of the WSN consists of four sensor nodes, and a backbone router connected to a PC. The sensor nodes contain an application processor and a radio processor. The application processor is a Texas Instruments MSP430F5438 which is located on an MSP-EXP430F5438 evaluation board. The radio processor is a NIVIS Versa Node 210 that is located on a VS210 development board. The wireless protocol investigated is the ISA100.11a. / text

Detection of encroachment on pipeline right-of-way is important for pipeline safety. An effective system can provide on-time warning while reducing the probability of false alarms. There are a number of industry and academic developments to tackle this problem. This thesis is the first to study the use of a wireless sensor network for pipeline right-of-way encroachment detection. In the proposed method, each sensor node in the network is responsible for detecting and transmitting vibration signals caused by encroachment activities to a base station (computer center). The base station monitors and analyzes the signals. If an encroachment activity is detected, the base station will send a warning signal. We describe such a platform with hardware configuration and software controls, and the results demonstrate that the platform is able to report our preliminary experiments in detecting digging activities by a tiller in the natural and automotive noise.

The coverage and energy issues are the fundamental problems which prevent the development of wireless sensor networks. In order to accurately evaluate the monitoring quality (coverage), one needs to model the interactive of sensors, phenomenons and the environment. Furthermore, in collaborative with scheduling algorithm and computer optimization, protocols can improve the overall monitoring quality and prolong the lifetime of network. This thesis is an investigation of coverage problem and its relative applications in the wireless sensor networks. We first discuss the realistic of current boolean sensing model and propose an irregular sensing model used to determine the coverage in the area with obstacles. We then investigate a joint problem of maintaining the monitoring quality and extending the lifetime of network by using scheduling schemes. Since the scheduling problem is NP hard, genetic algorithm and Markov decision process are used to determine an achievable optimal result for the joint problem of coverage-preserving and lifetime-prolong. In order to avoid the cost of centralized or distributed scheduling algorithms, a localized coverage-preserving scheduling algorithm is proposed by exploring the construction process of Voronoi diagram. Besides exploring the coverage characteristic in a static wireless sensor network, we investigate the coverage problem when the mobile elements are introduced into network. We consider the single-hop mobile data gathering problem with the energy efficiency and data freshness concerns in a wireless sensor network where the connectivity cannot be maintained. We first investigate the upper/lower bound of the covering time for a single collector to cover the monitoring area. Through our investigation we show that for a bounded rectangle area a hexagon walk could explore the area more efficiently than a random walk when the edges of area are known. We then propose a virtual force mobile model (VFM) in which the energy consumption for data transmission is modeled as a virtual elastic force and used to guide of mobile collectors to move to optimal positions for energy saving.

In today’s era of the Internet of Things, it is crucial to study the real-time dependencies of the web, its failures and time delays. Today, smart grids, sensible homes, wise water networks, intelligent transportation, infrastructure systems that connect our world over are developing fast. The shared vision of such systems is typically associated with one single conception Internet of Things (IoT), where through the deployment of sensors, the entire physical infrastructure is firmly fastened with information and communication technologies; where intelligent observation and management is achieved via the usage of networked embedded devices. The performance of a real-time control depends not only on the reliability of the hardware and software used but also on the time delay in estimating the output, because of the effects of computing time delay on the control system performance. For a given fixed sampling interval, the delay and loss issues are the consequences of computing time delay. The delay problem occurs when the computing time delay is non-zero but smaller than the sampling interval, while the loss problem occurs when the computing time delay is greater than, or equal to, the sampling interval, i.e., loss of the control output. These two queries are analyzed as a means of evaluating real-time control systems. First, a general analysis of the effects of computing time delay is presented along with necessary conditions for system stability. In this thesis, we will focus on the experimental study of the closed loop control system in the internet of things to determine the cycle time constraints in case of link failure.