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The work discussed in this thesis provides a review of pertinent literature, a design methodology, analytical model, concept generation and development, and conclusions about energy harvesting to provide long-term power for bridge health monitoring. The methodology gives structure for acquiring information and parameters to create effective energy harvesters. The methodology is used to create a wind energy harvester to provide long-term power to a wireless communication network. An analytical model is developed so the system can be scaled for different aspects of the network. A proof of concept is constructed to test the methodology's effectiveness, and validate the feasibility and analytical model. / text

To predict the lifetime of wireless sensor networks before their installation is an important concern. The IEEE 802.15.4 standard is specifically meant to support long battery life time; still there are some precautions to be taken by which a sensor network system application based on the standard can be made to run for longer time periods. This thesis defines a holistic approach to the problem of energy consumption in sensor networks and suggests a choice of node architecture, network structure and routing algorithm to support energy saving in the network. The idea and thrust of the thesis is that stand-alone measures such as selecting a low-power microcontroller with embedded transceiver will not alone be sufficient to achieve energy saving over the entire network. A comprehensive design study with energy saving as a primary task must be made. Focus given on the design objectives needs to look at different aspects – application code, network configuration code, routing algorithms etc to come up with an energy efficient network.

abstract: Distributed wireless sensor networks (WSNs) have attracted researchers recently due to their advantages such as low power consumption, scalability and robustness to link failures. In sensor networks with no fusion center, consensus is a process where all the sensors in the network achieve global agreement using only local transmissions. In this dissertation, several consensus and consensus-based algorithms in WSNs are studied. Firstly, a distributed consensus algorithm for estimating the maximum and minimum value of the initial measurements in a sensor network in the presence of communication noise is proposed. In the proposed algorithm, a soft-max approximation together with a non-linear average consensus algorithm is used. A design parameter controls the trade-off between the soft-max error and convergence speed. An analysis of this trade-off gives guidelines towards how to choose the design parameter for the max estimate. It is also shown that if some prior knowledge of the initial measurements is available, the consensus process can be accelerated. Secondly, a distributed system size estimation algorithm is proposed. The proposed algorithm is based on distributed average consensus and L2 norm estimation. Different sources of error are explicitly discussed, and the distribution of the final estimate is derived. The CRBs for system size estimator with average and max consensus strategies are also considered, and different consensus based system size estimation approaches are compared. Then, a consensus-based network center and radius estimation algorithm is described. The center localization problem is formulated as a convex optimization problem with a summation form by using soft-max approximation with exponential functions. Distributed optimization methods such as stochastic gradient descent and diffusion adaptation are used to estimate the center. Then, max consensus is used to compute the radius of the network area. Finally, two average consensus based distributed estimation algorithms are introduced: distributed degree distribution estimation algorithm and algorithm for tracking the dynamics of the desired parameter. Simulation results for all proposed algorithms are provided. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017

The need to achieve extended service life by battery powered Wireless Sensor Networks (WSNs) requires new concepts and technqiues beyond the state-of-the-art low-power designs based on fixed hardware platforms or energy-efficient protocols. This thesis investigates reconfiguration techniques that enable sensor hardware to adapt its energy consumption to external dynamics, by means of Dynamic Voltage Scaling (DVS), Dynamic Modulation Scaling (DMS), and other related concepts. For sensor node-level reconfiguration, an integration of DVS and DMS techniques was proposed to minimize the total energy consumption. A dynamic time allocation algorithm was developed, demonstrating an average of 55% energy reduction. For network-level reconfiguration, a node activation technique was presented to reduce the cost of recharging energy-depleted sensor nodes. Network operation combined with node activation was modeled as a stochastic decision process, where the activation decisions directly affected the energy efficiency of the network. An experimental test bed based on the Imote2 sensor node platform was realized, which demonstrated energy reduction of up to 50%. Such energy saving can be effectively translated into prolonged service life of the sensor network.

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<p>Mobile communication systems are experiencing a huge growth. While traditional communication paradigms deal with fixed networks, mobility raises a new set of questions, techniques, and solutions. This work focuses on wireless sensor networks (WSNs) where each node is a mobile device. The main objectives of this thesis have been to develop algorithms and protocols enabling WSNs with a special interest in overcoming mobility support limitations of standards such as Bluetooth and Zigbee. The contributions of this work may be divided in four major parts related to mobility support. The first part describes the implementation of local positioning services in Bluetooth since local positioning is not supported in Bluetooth v1.1. The obtained results are used in later implemented handover algorithms in terms of deciding when to perform the handover. Moreover local positioning information may be used in further developed routing protocols. The second part deals with handover as a solution to overcome the getting out of range problem. Algorithms for handover have been implemented enabling mobility in Bluetooth infrastructure networks. The principal achievement in this part is the significant reduction of handover latency since sensor cost and quality of service are directly affected by this parameter. The third part solves the routing problems originated with handovers. The main contribution of this part is the impact of the Bluetooth scatternet formation and routing protocols, for multi-hop data transmissions, in the system quality of service. The final part is a comparison between Bluetooth and Zigbee in terms of mobility support. The main outcome of this comparison resides on the conclusions, which can be used as a technology election guide.</p><p>The main scientific contribution relies on the implementation of a mobile WSN with Bluetooth v1.1 inside the scope of the ”Multi Monitoring Medical Chip (M3C) for Homecare Applications” European Union project (Sixth Framework Program (FP6) Reference: 508291) offering multi-hop routing support and improvements in handover latencies with aid of local positioning services.</p>

Recent surveys on medical service systems show that the cost of patient monitoring has grown significantly. The widespread use of portable digital medical device makes it possible to provide a more comprehensive tracking of patient conditions. However, the development of a full scale, distributed health monitoring system is much delayed due to the lack of efficient wireless communication in a large distributed network. This becomes a challenging research topic which is to find a way to provide accurate and real time patient information to medical experts in a fast, efficient and cost effective fashion. This paper proposes a novel solution on building a system which links patients and doctors together using embedded system technology and wireless sensor network. The content presented in this thesis introduces the design and implement of such a system.

Many domains, such as geographical and biological sciences, can benefit from the ability of wireless sensor networks to provide long term, high temporal and spatial resolution sensing. Such networks must be able to trade off various requirements against each other to extend network lifetime while still providing useful, good quality data. The challenges faced by equipment in the field can very unpredictable and therefore a wireless sensor network should be able to cope with these challenges and return to a balanced state. Using readily available, low-cost components, this work was inspired by the human endocrine systems ability to maintain homeostasis, or balance, in a large number of parameters simultaneously. This work developed a number of endocrine inspired methods. These were aimed both at improving the power usage of nodes in a wireless sensor network and improving the quality of the data collected. Methods for improving power consumption and data quality were achieved. These methods were successfully deployed, for the purposes of environmental monitoring on a mesh network consisting of 20 nodes, for a period of almost 6 months. Analysis showed that the use of power by individual nodes was improved and that the endocrine inspired methods, aimed at improving data quality, were successful. Node lifetimes were extended, duplicate data reduced and the quality of data improved. The use of low-cost, readily available components was largely successful, and challenges and changes to these components were discussed.