ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / Relay selection for optimal communication as well as multiple source localization is studied. We consider the use of dual-role nodes that can work both as relays and also as anchors. The dual-role nodes and multiple sources are placed at fixed locations in a two-dimensional space. Each dual-role node estimates its distance to all the sources within its radius of action. Dual-role selection is then obtained considering all the measured distances and the total SNR of all sources-to-destination channels for optimal communication and multiple source localization. Bit error rate performance as well as mean squared error of the proposed optimal dual-role node selection scheme are presented.

ITC/USA 2012 Conference Proceedings / The Forty-Eighth Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2012 / Town and Country Resort & Convention Center, San Diego, California / The selection of relay nodes (RNs) for optimal communication and source location estimation is studied. The RNs are randomly placed at fixed and known locations over a geographical area. A mobile source senses and collects data at various locations over the area and transmits the data to a destination node with the help of the RNs. The destination node not only needs to collect the sensed data but also the location of the source where the data is collected. Hence, both high quality data collection and the correct location of the source are needed. Using the measured distances between the relays and the source, the destination estimates the location of the source. The selected RNs must be optimal for joint communication and source location estimation. We show in this paper how this joint optimization can be achieved. For practical decentralized selection, an opportunistic RN selection algorithm is used. Bit error rate performance as well as mean squared error in location estimation are presented and compared to the optimal relay selection results.

Coverage in a Wireless Sensor Network reflects how well a sensor network monitors an area. Many times it is impossible to provide full coverage. The key challenges are to prolong the lifetime and ensure connectivity to provide a stable network. In this thesis we first define p-percent coverage problem in which we require only p% of the whole area to be monitored. We propose two algorithms, Connected P-Percent Coverage Depth First Search (CpPCA-DFS) and Connected P-Percent Connected Dominating Set (CpPCA-CDS). Through simulations we then compare and analyze them for their efficiency and lifetime. Finally in conclusion we prove that CpPCA-CDS provides 5 to 20 percent better active node ratio at low density. At high node density it achieves better distribution of covered area however the lifetime is only 5 to10 percent shorter then CpPCA-DFS. Overall CpPCA-CDS provides up to 30 percent better distribution of covered area.

Wireless Sensor Networks (WSNs) are ad-hoc networks consisting of tiny battery- operated wireless sensors. The sensor nodes are lightweight in terms of memory, computation, energy and communication. These networks are usually deployed in unsecured, open, and harsh environments, where it is difficult for humans to perform continuous monitoring. Consequently, it is very crucial to provide security mecha- nisms for authenticating data among sensor nodes. Key management is a pre-requisite for any security mechanism. Efficient distribution and management of keys in WSNs is a challenging task. Many standard key establishment techniques have been pro- posed using symmetric cryptosystems. Unfortunately, these systems often fail to pro- vide a good trade-off between memory and security and since WSNs are lightweight in nature, these cryptosystems are not feasible. On the other hand, public key in- frastructure (PKI) is infeasible in WSNs because of its continuous requirement of a trusted third party and heavy computational demands for certificate verification. Pairing-Based Cryptography (PBC) has paved the way for how parties can agree on keys without any interaction. It has relaxed the requirement of expensive certificate verification on PKI systems. In this thesis, we propose a new hybrid identity-based non-interactive key management protocol for WSNs, which leverages the benefits of both symmetric key based cryptosystems and pairing-based cryptosystems. The pro- posed protocol is scalable, suits many applications and can be deployed in multiple types of networks without modifications. We also provide mechanisms for key refresh when the network topology changes. A security analysis is presented to prove that the scheme is resilient to many types of attacks. To validate our scheme, we have implemented it on Crossbow TelosB motes running TinyOS and analyzed the perfor- mance in terms of memory, communication, computation and energy consumption. The results indicate that our scheme can be deployed efficiently to provide high level of security in a large-scale network without increasing memory, communication and energy overheads.

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Localization and coverage are two important and closely related problems in wireless ad hoc networks. Localization aims to determine the physical locations of devices in a network, while coverage determines if a region of interest is sufficiently monitored by devices. Localization systems require a high degree of coverage for correct functioning, while coverage schemes typically require accurate location information. This thesis investigates the relationship between localization and coverage such that new schemes can be devised which integrate approaches found in each of these well studied problems. This work begins with a thorough review of the current literature on the subjects of localization and coverage. The localization scheduling problem is then introduced with the goal to allow as many devices as possible to enter deep sleep states to conserve energy and reduce message overhead, while maintaining sufficient network coverage for high localization accuracy. Initially this sufficient coverage level for localization is simply a minimum connectivity condition. An analytical method is then proposed to estimate the amount of localization error within a certain probability based on the theoretical lower bounds of location estimation. Error estimates can then be integrated into location dependent schemes to improve on their robustness to localization error. Location error estimation is then used by an improved scheduling scheme to determine the minimum number of reference devices required for accurate localization. Finally, an optimal coverage preserving sleep scheduling scheme is proposed which is robust to localization error, a condition which is ignored by most existing solutions. Simulation results show that with localization scheduling network lifetimes can be increased by several times and message overhead is reduced while maintaining negligible differences in localization error. Furthermore, results show that the proposed coverage preserving sleep scheduling scheme results in fewer active devices and coverage holes under the presence of localization error.

Soft sensors are an essential component of process systems engineering schemes. While soft sensor design research is important, investigation into the relationships between soft sensors and other areas of advanced monitoring and control is crucial as well. This dissertation presents two new techniques that enhance the performance of fault detection and sensor network design by integration with soft sensor technology. In addition, a chapter is devoted to the investigation of the proper implementation of one of the most often used soft sensors. The performance advantages of these techniques are illustrated with several cases studies. First, a new approach for fault detection which involves soft sensors for process monitoring is developed. The methodology presented here deals directly with the state estimates that need to be monitored. The advantage of such an approach is that the nonlinear effect of abnormal process conditions on the state variables can be directly observed. The presented technique involves a general framework for using soft sensor design and computation of the statistics that represent normal operating conditions. Second, a method for determining the optimal placement of multiple sensors for processes described by a class of nonlinear dynamic systems is described. This approach is based upon maximizing a criterion, i.e., the determinant, applied to the empirical observability gramian in order to optimize certain properties of the process state estimates. The determinant directly accounts for redundancy of information, however, the resulting optimization problem is nontrivial to solve as it is a mixed integer nonlinear programming problem. This paper also presents a decomposition of the optimization problem such that the formulated sensor placement problem can be solved quickly and accurately on a desktop PC. Many comparative studies, often based upon simulation results, between Extended Kalman filters (EKF) and other estimation methodologies such as Moving Horizon Estimation or Unscented Kalman Filter have been published over the last few years. However, the results returned by the EKF are affected by the algorithm used for its implementation and some implementations may lead to inaccurate results. In order to address this point, this work provides a comparison of several different algorithms for implementation.

This thesis contributes toward the design of a reliable and energy-efficient transport system for Wireless Sensor Networks. Wireless Sensor Networks have emerged as a vital new area in networking research. In many Wireless Sensor Network systems, a common task of sensor nodes is to sense the environment and send the sensed data to a sink node. Thus, the effectiveness of a Wireless Sensor Network depends on how reliably the sensor nodes can deliver their sensed data to the sink. However, the sensor nodes are susceptible to loss for various reasons when there are dynamics in wireless transmission medium, environmental interference, battery depletion, or accidentally damage, etc. Therefore, assuring reliable data delivery between the sensor nodes and the sink in Wireless Sensor Networks is a challenging task. The primary contributions of this thesis include four parts. First, we design, implement, and evaluate a cross-layer communication protocol for reliable data transfer for data streaming applications in Wireless Sensor Networks. We employ reliable algorithms in each layer of the communication stack. At the MAC layer, a CSMA MAC protocol with an explicit hop-by-hop Acknowledgment loss recovery is employed. To ensure the end-to-end reliability, the maximum number of retransmissions are estimated and used at each sensor node. At the transport layer, an end-to-end Negative Acknowledgment with an aggregated positive Acknowledgment mechanism is used. By inspecting the sequence numbers on the packets, the sink can detect which packets were lost. In addition, to increase the robustness of the system, a watchdog process is implemented at both base station and sensor nodes, which enable them to power cycle when an unexpected fault occurs. We present extensive evaluations, including theoretical analysis, simulations, and experiments in the field based on Fleck-3 platform and the TinyOS operating system. The designed network system has been working in the field for over a year. The results show that our system is a promising solution to a sustainable irrigation system. Second, we present the design of a policy-based Sensor Reliability Management framework for Wireless Sensor Networks called SRM. SRM is based on hierarchical management architecture and on the policy-based network management paradigm. SRM allows the network administrators to interact with the Wireless Sensor Network via the management policies. SRM also provides a self-control capability to the network. This thesis restricts SRM to reliability management, but the same framework is also applicable for other management services by providing the management policies. Our experimental results show that SRM can offer sufficient reliability to the application users while reducing energy consumption by more than 50% compared to other approaches. Third, we propose an Energy-efficient and Reliable Transport Protocol called ERTP, which is designed for data streaming applications in Wireless Sensor Networks. ERTP is an adaptive transport protocol based on statistical reliability that ensures the number of data packets delivered to the sink exceeds the defined threshold while reducing the energy consumption. Using a statistical reliability metric when designing a reliable transport protocol guarantees the delivery of adequate information to the users, and reduces energy consumption when compared to the absolute reliability. ERTP uses hop-by-hop Implicit Acknowledgment with a dynamically updated retransmission timeout for packet loss recovery. In multihop wireless networks, the transmitter can overhear a forwarding transmission and interpret it as an Implicit Acknowledgment. By combining the statistical reliability and the hop-by-hop Implicit Acknowledgment loss recovery, ERTP can offer sufficient reliability to the application users with minimal energy expense. Our extensive simulations and experimental evaluations show that ERTP can reduce energy consumption by more than 45% when compared to the state-of- the-art protocol. Consequently, sensor nodes are more energy-efficient and the lifespan of the unattended Wireless Sensor Network is increased. In Wireless Sensor Networks, sensor node failures can create network partitions or coverage loss which can not be solved by providing reliability at higher layers of the protocol stack. In the final part of this thesis, we investigate the problem of maintaining the network connectivity and coverage when the sensor nodes are failed. We consider a hybrid Wireless Sensor Network where a subset of the nodes has the ability to move at a high energy expense. When a node has low remaining energy (dying node) but it is a critical node which constitutes the network such as a cluster head, it will seek a replacement. If a redundant node is located in the transmission range of the dying node and can fulfill the network connectivity and coverage requirement, it can be used for substitution. Otherwise, a protocol should be in place to relocate the redundant sensor node for replacement. We propose a distributed protocol for Mobile Sensor Relocation problem called Moser. Moser works in three phases. In the first phase, the dying node determines if network partition occurs, finds an available mobile node, and asks for replacement by using flooding algorithm. The dying node also decides the movement schedule of the available mobile node based on certain criteria. The second phase of the Moser protocol involves the actual movement of the mobile nodes to approach the location of the dying node. Finally, when the mobile node has reached the transmission of the dying node, it communicates to the dying nodes and moves to a desired location, where the network connectivity and coverage to the neighbors of the dying nodes are preserved.

We introduce Simultaneous Localization and Tracking (SLAT), the problem of tracking a target in a sensor network while simultaneously localizing and calibrating the nodes of the network. Our proposed solution, LaSLAT, is a Bayesian filter providing on-line probabilistic estimates of sensor locations and target tracks. It does not require globally accessible beacon signals or accurate ranging between the nodes. When applied to a network of 27 sensor nodes, our algorithm can localize the nodes to within one or two centimeters.