Power saving for extending session lifetime is an important research subject in wireless sensor networks (WSNs). Recognizing the fact that Quality of Service can be deteriorated by insufficient transmit power, this work studies how to minimize power consumption while achieve a satisfactory QoS of data streams in WSNs. A cross-layer routing scheme is proposed to maximize session lifetime by adjusting individual transmit power on intermediate nodes. The thesis is divided into two major parts for analyzing our proposition. In the first part, we propose an efficient routing scheme with optimal power management and on-demand quality control for WSNs. When source node issues a QoS provision for route discovery, an adjustment of transmit power is computed for each pass-by node by taking into its individual wireless link account. Then, an optimal route associated with lowest power consumption and consistent QoS can be selected among all of the candidate routes. In the second part, by following the definition of QoS criterion in the first part, we further consider the problem of how to balance the needs on constraining end-to-end quality and prolonging lifetime in an established route. The problem can be interpreted as a non-linear optimization paradigm, which is then shown to be a max-min composite formulation. To solve the problem, we propose two methods, (1) route-associated power management (RAPM), and (2) link-associated power management (LAPM). Considering computation-restricted sensor nodes, the RAPM scheme is two-fold simplification; not only it can reduce power computation, but it also quickly determines the longest lifetime and proper transmit power for nodes. On the other hand, if computational cost is not a major concern in a sink node, the LAPM algorithm is more suitable than RAPM to solve the lifetime maximization problem, in terms of accuracy. Finally, we analyze the performance of these two methods. The results demonstrate that the LAPM scheme is very comparable to a heuristic approach.

Wireless sensor network has applications in environmental surveillance, healthcare, and military operations. Because the energy of sensor nodes is limited and nodes are unable to supply energy in real time, the purpose of many researches is to prolong lifetime of sensor network. Lifetime is times that the sink can collect data from all sensor nodes. When a user proposes a query, then the sink gathers data from all sensor nodes. The problem defined in the previous research is given a sensor network and residual energy of each node, and the energy consumption of transmitting a unit message between two nodes. Then this problem is to find a directed tree that maximize minimum residual energy. In this thesis, we define a new problem that given a sensor network and residual energy of each node, and the energy consumption of transmitting a unit message between two nodes. Then our problem is to find a path of each node, which maximize minimum residual energy. We prove this problem is NP-complete. We propose a heuristic algorithm and a similar heuristic algorithm for this problem.

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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.

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A masters thesis focussing on achieving improvements in transmission reliability and energy efficiency for a battery-powered wireless sensor node on the edge of an industrial heterogeneous wireless network that consists predominantly of mains-powered nodes. A router-switching technique is proposed to allow the sensor node to make gains in transmission reliability and energy efficiency by taking advantage of the scenario where multiple wireless routers are in range and switching between them, instead of only being able to transmit to one router. The research involves simulation of a number of network scenarios where the router-switching technique is enabled and disabled, to measure the advantage gained for the sensor in terms of its functional lifetime. The simulation is based on an abstract model that focusses on the edge of the mains-powered area of the network, where the battery-powered sensor is located. The simulation results show that for many cases, router-switching provides a higher level of transmission reliability and lower levels of energy consumption than the scenario where router-switching is disabled, as well as improvements in data loss rates.

This thesis looks at the problem of optimally placing binary directional proximity markers to assist a robot as it navigates waypoints through an environment. A simple planar fiducial marker is developed to serve as the binary directional proximity marker. A scoring function is proposed for marker placement as well as a method for random generation of hallway maps. Several common metaheuristic algorithms are run to find optimal marker placements with respect to the scoring function for a number of randomly generated hallway maps. From these results, placements are then evaluated by physical experimentation on an iRobot Create equipped with relatively inexpensive webcams. / Graduate

Emerging body-wearable sensor devices for continuous health monitoring are severely energy constrained and yet required to offer high communication reliability under fluctuating channel conditions. This thesis aims at investigating the opportunities and challenges in the use of dynamic radio transmit power control for prolonging the lifetime of such devices. We first present extensive empirical evidence that the wireless link quality can change rapidly in body area networks, and a fixed transmit power results in either wasted energy (when the link is good) or low reliability (when the link is bad). We then propose a class of schemes feasible for practical implementation that adapt transmit power in real-time based on feedback information from the receiver. We show conservative, balanced, and aggressive adaptations of our scheme that progressively achieve higher energy savings of 14%-30% in exchange for higher potential packet losses (up to 10%). We also provide guidelines on how the parameters can be tuned to achieve the desired trade-off between energy savings and reliability within the chosen operating environment. Finally, we implement and profile our scheme on a MicaZ mote based platform, demonstrating that energy savings are achievable even with imperfect feedback information, and report preliminary results on the ultra-low-power integrated healthcare monitoring platform from our collaborating partner Toumaz Technology. In conclusion, our work shows adaptive radio transmit power control as a low-cost way of extending the battery-life of severely energy constrained body wearable devices, and opens the door to further optimizations customized for specific deployment scenarios.

In this thesis we present LaSLAT, a sensor network algorithm thatsimultaneously localizes sensors, calibrates sensing hardware, andtracks unconstrained moving targets using only range measurementsbetween the sensors and the target. LaSLAT is based on a Bayesian filter, which updates a probabilitydistribution over the quantities of interest as measurementsarrive. The algorithm is distributable, and requires only a constantamount of space with respect to the number of measurementsincorporated. LaSLAT is easy to adapt to new types of hardware and newphysical environments due to its use of intuitive probabilitydistributions: one adaptation demonstrated in this thesis uses amixture measurement model to detect and compensate for bad acousticrange measurements due to echoes.We also present results from a centralized Java implementation ofLaSLAT on both two- and three-dimensional sensor networks in whichranges are obtained using the Cricket ranging system. LaSLAT is ableto localize sensors to within several centimeters of their groundtruth positions while recovering a range measurement bias for eachsensor and the complete trajectory of the mobile.