There has been a quick development in the wireless network area during the last decade. Mostly these days the focus in the wireless area is on very high speed and long range applications. This thesis describes how ZigBee is suitable for wireless sensor networks in logistic telemetry applications for global managing and monitoring of goods. ZigBee has been developed by the organization named as ‘ZigBee Alliance’ as a new wireless standard for the wireless solutions based upon the IEEE 802.15.4 Standard [2]. ZigBee is a new technology as compared to the other wireless technologies such as Bluetooth, but it has certain characteristics such as low cost, low power, support for mesh networking e.t.c which makes its chances to be more successful than others. The other aim of this thesis is to examine different issues related to ZigBee to see its fitness for logistic telemetry applications like multi-hop routing issues, routing strategies and design requirements. ZigBee is relatively new wireless technology, so there are great deals of promises associated with it. In this thesis, a comparison between ZigBee and Bluetooth technologies will also be made.

X3 C is a Swedish company which develops a world wide good tracking system by using ARFID tags placed on every item which has to be delivered and base stations as gateway in a wireless sensor network. The requirement of a long lifespan of their ARFID tags made it difficult to implement security. Firstly an evaluation of possible security mechanisms and their power consumption was done by measuring the avalanche effect and character frequency of the sym- metric algorithms Blowfish, RC2 and XTEA. Secondly, the required CPU time which is needed by each algorithm for encrypting a demo plaintext, was measured and analyzed. Summariz- ing both analysis, the XTEA algorithm, run in CBC mode, is the recommendation for the XC ARFID tags. The testing processes and the results are presented in detail in this thesis.

This thesis focuses on three fundamental issues that concern data aggregation protocols for periodic data collection in sensor networks: <i>which</i> sensor nodes should report their data, <i>when</i> should they report it, and should they use <i>unicast</i> or <i>broadcast</i> based protocols for this purpose. <p> The issue of when nodes should report their data is considered in the context of real-time monitoring applications. The first part of this thesis shows that asynchronous aggregation, in which the time of each nodes transmission is determined adaptively based on its local history of past packet receptions from its children, outperforms synchronous aggregation by providing lower delay for a given end-to-end loss rate. <p> Second, new broadcast-based aggregation protocols that minimize the number of packet transmissions, relying on multipath delivery rather than automatic repeat request for reliability, are designed and evaluated. The performance of broadcast-based aggregation is compared to that of unicast-based aggregation, in the context of both real-time and delay-tolerant data collection. <p> Finally, this thesis investigates the potential benefits of dynamically, rather than semi-statically, determining the set of nodes reporting their data, in the context of applications in which coverage of some monitored region is to be maintained. Unicast and broadcast-based coverage-preserving data aggregation protocols are designed and evaluated. The performance of the proposed protocols is compared to that of data collection protocols relying on node scheduling.

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Conguring a network system to operate at optimal levels of performance re-quires a comprehensive understanding of the eects of a variety of system parameterson crucial metrics like connectivity and resilience to network attacks. Traditionally,omni-directional antennas have been used for communication in wireless sensor net-works. In this thesis, a hybrid communication model is presented where-in, nodes ina network are capable of both omni-directional and uni-directional communication.The eect of such a model on performance in randomly deployed wireless sensor net-works is studied, specically looking at the eect of a variety of network parameterson network performance.The work in this thesis demonstrates that, when the hybrid communication modelis employed, the probability of 100% connectivity improves by almost 90% and thatof k-connectivity improves by almost 80% even at low node densities when comparedto the traditional omni-directional model. In terms of network security, it was foundthat the hybrid approach improves network resilience to the collision attack by almost85% and the cost of launching a successful network partition attack was increased byas high as 600%. The gains in connectivity and resilience were found to improve withincreasing node densities and decreasing antenna beamwidths.

Time synchronization in wireless sensor networks (WSNs) is essential and significant for maintaining data consistency, coordination, and performing other fundamental operations, such as power management, security, and localization. Energy efficiency is the main concern in designing time synchronization protocols for WSNs because of the limited and generally nonrechargeable power resources. In this dissertation, the problem of time synchronization is studied in three different aspects to achieve energy efficient time synchronization in WSNs. First, a family of novel joint clock offset and skew estimators, based on the classical two-way message exchange model, is developed for time synchronization in WSNs. The proposed joint clock offset and skew correction mechanisms significantly increase the period of time synchronization, which is a critical factor in the over-all energy consumption required for global network synchronization. Moreover, the Cramer-Rao bounds for the maximum likelihood estimators are derived under two different delay assumptions. These analytical metrics serve as good benchmarks for the experimental results thus far reported. Second, this dissertation proposes a new time synchronization protocol, called the Pairwise Broadcast Synchronization (PBS), which aims at minimizing the number of message transmissions and implicitly the energy consumption necessary for global synchronization of WSNs. A novel approach for time synchronization is adopted in PBS, where a group of sensor nodes are synchronized by only overhearing the timing messages of a pair of sensor nodes. PBS requires a far smaller number of timing messages than other well-known protocols and incurs no loss in synchronization accuracy. Moreover, for densely deployed WSNs, PBS presents significant energy saving. Finally, this dissertation introduces a novel adaptive time synchronization protocol, named the Adaptive Multi-hop Timing Synchronization (AMTS). According to the current network status, AMTS optimizes crucial network parameters considering the energy efficiency of time synchronization. AMTS exhibits significant benefits in terms of energy-efficiency, and can be applied to various types of sensor network applications having different requirements.

Time-synchronization in wireless ad-hoc sensor networks is a crucial piece of infrastructure. Thus, it is a fundamental design problem to have a good clock syn- chronization amongst the nodes of wireless ad-hoc sensor networks. Motivated by this fact, in this thesis, the joint maximum likelihood (JML) estimator for relative clock phase offset and skew under the exponential noise model for the reference broadcast synchronization protocol is formulated and found via a direct algorithm. The Gibbs Sampler is also proposed for joint estimation of relative clock phase offset and skew, and shown to provide superior performance compared to the JML-estimator. Lower and upper bounds for the mean-square errors (MSE) of the JML-estimator and the Gibbs Sampler are introduced in terms of the MSE of the uniform minimum variance unbiased estimator and the conventional best linear unbiased estimator, respectively. The suitability of the Gibbs Sampler for estimating additional unknown parameters is shown by applying it to the problem in which synchronization of clock drift is also needed.

The use of a wireless sensor network (WSN) to monitor an historic structure under rehabilitation is the focus of this research. To thoroughly investigate the issue, two main objectives are addressed: the development of a reliable WSN tailored for use in historic structures, and the implementation of the monitoring system in the field to test the feasibility of the WSN and its applicability for structural health monitoring (SHM). Three field studies are undertaken in this research. The Frankford Church, an historic wooden church which required foundation replacement, is the first field study. Sensors monitor tilt of the church’s walls throughout construction. During the construction process, the entire floor of the church is removed and the tree stump foundations are replaced by concrete masonry unit (CMU) blocks and steel pedestals. The tilt in the walls is correlated to the construction process. St. Paul Lutheran, an historic masonry church with timber-framed roof, constitutes the second field study. In this structure, the foundations along the exterior walls are underpinned and the floors are removed and replaced with a floating concrete slab. Detected movements are also correlated to the construction efforts. The Johanniskirche, an historic masonry church with moisture problems, is the final field study case. Real-time and past measured WSN climate data is used to determine the most appropriate solution for the humid climate and resulting condensation problems in this structure. From these results, a moisture migration risk analysis protocol is created for use with a WSN to address condensation issues. The results of the tilt monitoring indicate that the approach is realistic to monitor tilt in the walls of historic structures. For future research, it is recommended to implement motes with higher tilt sensitivity. Also, further development of energy saving algorithms and energy harvesting methods will improve the WSN’s performance. Climate monitoring results show it is feasible to monitor climate conditions of historic structures. The moisture migration protocol provides a basis for further improvement. Implementation of this tool will help predict condensation events and prevent future damage to the historic structure.

In this thesis, we propose and evaluate algorithms for solving the worst-case-coverage deployment problem in ad-hoc wireless sensor networks. The worst-case-coverage deployment problem is to deploy additional sensors in the wireless sensor field to optimize the worst-case coverage. We derive a duality theorem that reveals the close relation between the maximum breach path and the minimum Delaunay cut. The duality theorem is similar to the well-known max-flow-min-cut theorem in the field of network optimization. The major difference lies in the fact that the object function we study in this paper is nonlinear rather than linear. Based on the duality theorem, we propose an efficient dual algorithm to solve the worst-case-coverage deployment problem. In addition, we propose a genetic algorithm for deploying a number of additional sensors simultaneously. We use analytical proofs and simulation results to justify the usage of the proposed approaches.

The baseband part of IEEE 802.15.4 operated in 2.45 GHz mode is designed and implemented in this essay. First, the features of IEEE 802.15.4 WPAN(Wireless Personal Area Network), PHY layer and MAC Layer are introduced. Then the algorithm and VHDL of the baseband part of transceiver are designed and verified by FPGA board and logical analyzer.