Wireless Sensor Network (WSN) has become a popular wireless technology in recent years. In WSN, a large number of sensors are used to collect data and forward data hop-by-hop to a sink. Due to the unbalancing of traffic load, some grid nodes may consume more energy and their packet loss ratio may be increased as well. In order to improve above-mentioned shortcomings, in this Thesis, we propose an Adaptive Grid-based Data Collection (AGDC) scheme. Because a mobile sink may move, it is possible the traffic load of primary grid nodes can be changed in WSN. According to the distribution of traffic load, the AGDC can adjust transmission range to allocate one or more temporary grid nodes between two primary grid nodes. Through the added temporary grid nodes, traffic load is evenly dispersed among different grid nodes. We allow the primary grid nodes to use smaller transmission power to save energy and allow the temporary grid nodes to buffer data to reduce packet loss ratio. For the purpose of evaluation, we perform simulation on NS-2. With the proposed AGDC scheme, the transmission range of a primary grid node can be set to an appropriate distance to reduce power consumption and packet loss ratio. Since the packet loss ratio is reduced, the throughput of entire WSN is increased.

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.

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.

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.

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.

Wireless sensor networks (WSNs) can provide new methods for information gathering for a variety of applications. In order to ensure the network quality of service, the quality of the measurements has to be guaranteed. Distributed fault detection and isolation schemes are preferred to centralized solutions to diagnose faulty sensors in WSNs. Indeed the first approach avoids the need for a central node that collects information from every sensor node, and hence it limits complexity and energy cost while improving reliability.In the case of state estimation over distributed architectures, the sensor faults can be propagated in the network during the information exchanging process. To build a reliable state estimate one has to make sure that the measurements issued by the different sensors are fault free. That is one of the motivations to build a distributed fault detection and isolation (FDI) system that generates an alarm as soon as a measurement is subject to a fault (has drift, cdots ). In order to diagnose faults with small magnitude in wireless sensor networks, a systematic methodology to design and implement a distributed FDI system is proposed. It resorts to distinguishability measures to indicate the performance of the FDI system and to select the most suitable node(s) for information exchange in the network with a view to FDI. It allows one to determine the minimum amount of data to be exchanged between the different nodes for a given FDI performance. In this way, the specifications for FDI can be achieved while the communication and computation cost are kept as small as possible. The distributed FDI systems are designed both in deterministic and stochastic frameworks. They are based on the parity space approach that exploits spacial redundancy as well as temporal redundancy in the context of distributed schemes. The decision systems with the deterministic method and the stochastic method are designed not only to detect a fault but also to distinguish which fault is occurring in the network. A case study with a WSN is conducted to verify the proposed method. The network is used to monitor the temperature and humidity in a computer room. The distributed FDI system is validated both with simulated data and recorded data. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

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.

The agricultural sector is an emerging application area for Wireless Sensor Networks (WSNs). This requires sensor nodes to be deployed in the outdoor environment so as to monitor pertinent natural features, such as soil condition or pest infestation. Limited energy supply and subsequent battery replacement are common issues for these agricultural sensor nodes. One possible solution is to use energy harvesting, where the ambient energy is extracted and converted into usable electrical form to energise the wireless sensors. The work presented in this thesis investigates the feasibility of using Radio Frequency (RF) energy harvesting for a specific application; that is powering a generic class of wireless ground-level, agricultural sensor networks operating in an outdoor environment. The investigation was primarily undertaken through a literature study of the subject. The first part of the thesis examines several energy harvesting/ wireless energy transfer techniques, which may be applicable to power the targeted agricultural WSN nodes. The key advantages and limitations of each technique are identified, and the rationale is being given for selecting far-field RF energy harvesting as the investigated technique. It is then followed by a theoretical-based system analysis, which seeks to identify all relevant design parameters, and to quantify their impact on the system performance. An RF link budget analysis was also included to examine the feasibility of using RF energy harvesting to power an exemplar WSN node - Zyrox2 Bait Station. The second part of the thesis focuses on the design of two energy harvesting antennas. The first design is an air-substrate-based folded shorted patch antenna (FSPA) with a solid ground plane, while the second design is a similar FSPA structure with four pairs of slot embedded into its ground plane. Both antennas were simulated, fabricated and tested inside an anechoic chamber, and in their actual operating environment - an outdoor field. In addition, a power harvester circuit, built using the commercially available off-the-shelf components, was tested in the laboratory using an RF signal generator source. The results from both the laboratory and field trial were analysed. The measurement techniques used were reviewed, along with some comments on how to improve them. Further work on the RF energy harvester, particularly on the improvement of the antenna design must be carried out before the feasibility and viable implementations for this application can be definitively ascertained.

Power management is an active area of research in wireless sensor networks (WSNs). Efficient power management is necessary because WSNs are battery-operated devices that can be deployed in mission-critical applications. From the communications perspective, one main approach to reduce energy is to maximize throughput so the data can be transmitted in a short amount of time. Frame fragmentation techniques aim to achieve higher throughput by reducing retransmissions. Using experiments on a WSN testbed, we show that frame fragmentation helps to reduce energy consumption. We then study and compare recent frame fragmentation schemes to find the most energy-efficient scheme. Our main contribution is to propose a new frame fragmentation scheme that is optimized to be energy efficient, which is originated from the chosen frame fragmentation scheme. This new energy-efficient frame fragmentation protocol is called (Green-Frag). Green-Frag uses an algorithm that gives sensor nodes the ability to transmit data with optimal transmit power and optimal frame structure based on environmental conditions. Green-Frag takes into consideration the channel conditions, interference patterns and level, as well as the distance between sender and receiver. The thesis discusses various design and implementation considerations for Green-Frag. Also, it shows empirical results of comparing Green-Frag with other frame fragmentation protocols in terms of energy efficiency. Green-Frag performance results shows that it is capable of choosing the best transmit according to the channel conditions. Subsequently, Green-Frag achieves the least energy consumption in all environmental conditions.