Recent advancements in sensory devices are presenting various opportunities for widespread applications of wireless sensor networks (WSNs). The most distinguishing characteristic of a WSN is the fact that its sensors have nite and non-renewable energy resources. Many research e orts aim at developing energy e cient network topology and routing schemes for prolonging the network lifetime. However, we notice that, in the majority of the literature, topology control and routing problems are handled separately, thus overlooking the interrelationships among them. In this dissertation, we consider an integrated topology control and routing problem in WSNs which are unique type of data gathering networks characterized by limited energy resources at the sensor nodes distributed over the network. We suggest an underlying hierarchical topology and routing structure that aims to achieve the most prolonged network lifetime via e cient use of limited energy resources and addressing operational speci cities of WSNs such as communication-computation trade-o , data aggregation, and multi-hop data transfer for better energy e ciency. We develop and examine three di erent objectives and their associated mathematical models that de- ne alternative policies to be employed in each period of a deployment cycle for the purpose of maximizing the number of periods so that the network lifetime is prolonged. On the methodology side, we develop e ective solution approaches that are based on decomposition techniques, heuristics and parallel heuristic algorithms. Furthermore, we devise visualization tools to support our optimization e orts and demonstrate that visualization can be very helpful in solving larger and realistic problems with dynamic nature. This dissertation research provides novel analytical models and solution methodologies for important practical problems in WSNs. The solution algorithms developed herein will also contribute to the generalized mixed-discrete optimization problem, especially for the problems with similar characteristics.

With the constant expansion of the industrial monitoring system, there is an urgent requirement to reduce investment and operating costs for the development of industrial communication technology. For industrial real-time monitoring systems, wireless technology can be used in a practical industrial production to take advantages of its flexibility and robustness. As wireless sensor networks have many advantages such as low investment costs, flexible structure and ease of transformation, it has become the focus with regards to industrial areas. THVRG is a routing algorithm that selects the routing path based on two-hop information. Since different information sensed by the sensors may have different requirements in order to reach the sink, a priority-based routing algorithm is required in order to adapt to this kind of situation. This thesis has proposed a priority routing algorithm based on the THVRG (Priority-based THVRG). In addition, a simulation of this algorithm was performed in OPNET. Finally, the report provides an evaluation of the proposed algorithm in industrial wireless sensor networks.

Wireless Sensor Networks have to be very flexible and self-organizing, providing an ease way to be deployed. This feature is required due to a wide variety of possible applications and deployment scenarios in which they can be used. They can support different kinds of tools and applications in distinct areas, such as in agriculture, military, health care, home or factory automation, among other. An assisted living system supported by a WSN is presented in this work. The main feature of this system is to locate and track inhabitant’s behaviour. The system has been implemented using Mica2 Motes, which were placed in different rooms in a house. In order to make the use of the WSN easier, this project investigated and used a middleware called TinyDB, which represents a key technology to improve the usability of WSN.

A significant challenge in the Wireless Sensor Networks (WSN) research field is to find flexible and energy efficient strategies to perform the network setup and configuration to accomplish specified sensing missions. This thesis presents an approach which uses mobile agents to disseminate and allocate sensing missions to the sensor nodes. The addressed problem refers to the selection of appropriate nodes to perform the sensing mission, by using a decentralized approach supported by mobile software agents. Traditional approaches to deal with WSN setup use the pre-planned strategies, which are deliberately modelled, designed and tuned before the network deployment, and thus are not flexible. This thesis presents an alternative approach based on Belief Desire Intention-model agents using JASON, instead of traditional approaches. Simulation results provides evidences that this approach can achieve the goals of a sensing mission setup by decisions autonomously taken by the sensor node, diminishing then the need for communication among the sensor nodes, hence saving energy resources.

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.