Low cost, low power wireless sensors (motes) promise to revolutionize environmental data collection, but are they currently refined enough for widespread use by hydrologists? Their viability as a replacement for traditional data collection techniques was investigated in a 7 ha forested watershed in south-western British Columbia. The watershed included 41 instrument clusters measuring air and soil temperature, humidity, throughfall, soil moisture content, overland flow and groundwater head. The foundation of each cluster was a data box containing a MDA300 data acquisition board and a MICA2 processor board from Crossbow Technologies, Inc.™ that allowed for short range wireless data collection. The 41 motes each recorded data every 15 minutes from July, 2006, to April, 2007. In addition to reporting on the reliability of the motes and sensors during the 10 months deployment, the high spatial and temporal resolution data collected by this study gave the opportunity for many analyses of catchment processes. As soil moisture and throughfall are two influential processes in the exchange of water between the earth and the atmosphere, these were the focus of the data analysis. The first analysis was a resampling experiment on seven different events selected from the full data set. Comparing 100 different subsamples each of 5, 10 and 20 points for throughfall and soil moisture showed if increasing the sample size eventually produced diminishing returns in the ability to reproduce the true catchment mean. With significant differences in prediction ability for both soil moisture and throughfall at times of differing hydrologic activity, this analysis provides further support for the theories of changing moisture states of soil moisture and threshold values for throughfall. The second analysis described how the organization of soil moisture and throughfall changed during a range of weather conditions and timescales. Spatial representation of normalized values and Pearson correlation coefficients showed that there were distinct differences between wet and dry periods for soil moisture and between long and short analysis periods for throughfall.

Planning device deployment is a fundamental issue in implementing wireless sensor network (WSN) applications. This design practice determines types, numbers and locations of devices in order to build a powerful and effective system using devices of limited energy supply and constrained capacities. The deployment plan decides the limits of many intrinsic properties of a WSN, such as coverage, connectivity, cost, and lifetime. In this thesis, we address the device deployment planning issues related to large-scale WSN systems. We consider a typical deployment planning scenario in a heterogeneous two-tier WSN composed of sensor nodes and relay nodes. Sensor nodes form the lower tier of the network and are responsible for providing satisfactory sensing coverage to the application. Relay nodes form the upper tier of the network and they are responsible for forwarding data from sensor nodes to the base station. As so, relay nodes should provide reliable connectivity to sensor nodes for an extended period of time. We therefore address the sensor node deployment in terms of the sensing coverage and relay node deployment in terms of the communication connectivity and system lifetime. For sensor node deployment, we propose a coverage-guaranteed sensor node deployment design technique. Using this technique, the sensing coverage is complete even if sensor nodes are randomly dispersed within a bounded range from its target locations according to a given grid pattern. In order to curb the increased cost due to extra sensor nodes that are used in the coverage-guaranteed deployment, while still maintaining a high-quality sensing coverage, we further study the probabilistic properties of the grid-based sensor node deployment in the presence of deployment errors. For relay node deployment, we propose to extend the system lifetime by distributing relay nodes according to a density function, which is optimized in response to the energy consumption rate, so that the energy is dissipated at an approximately same rate across the network. We further craft the deployment density function to reconcile the needs of balanced energy consumption and strong sensor node connectivity. The techniques proposed in this thesis fill the blank of available literature and can serve as guidelines for WSN designers, solution providers and system integrators of WSN applications. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2008-01-15 09:33:53.917

Wireless sensor networks have applications in many places from wildlife environments to urban areas. Implementation of such a network is a challenging task because each specific application may require different constraints and objectives. To better meet the application requirements, cognitive wireless sensor network has been recently introduced. However, almost all the previous work in this area has been in theory or by simulation. Hence there is a demand to provide implementable ideas of cognition, implement, and analyze the results. The goal of this thesis is to implement a cognitive wireless sensor network with application in environment monitoring which is aware of the surrounding environment, updates its information based on the dynamic changes in the network status, makes appropriate decisions based on the gained awareness, and forwards required actions to involving nodes. An implementable cognitive idea is proposed based on the characteristics and goals of a cognitive system. Since transmission is one of the most power consuming processes in sensor nodes and non-efficient transmissions of data can lead to a shorter lifetime, this work tries to schedule nodes' transmission rate by the means of cognition and benefits from efficient scheduling of the redundant nodes to improve lifetime. To enhance a wireless sensor network with cognition, new nodes should be added to the architecture called cognitive nodes. Cognitive nodes will take care of most of the tasks in the cognition process while still there is a need to add a level of cognition to each individual node. The main contribution of this work is that it provides an implementable approach to cognition in wireless sensor networks, proposes a low complexity and low cost implementable idea for cognition, addresses implementation issues, and provides experimental results of different setups of the cognitive wireless sensor network. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2011-09-27 00:38:12.455

Over-the-air reprogramming is an important aspect of managing large wireless sensor networks. However, reprogramming deployed sensor networks poses significant challenges due to the energy, processing power and memory limitation of sensor nodes. For improved energy efficiency, a reprogramming mechanism should use less transmission and flash writing overhead. Past research has proposed different mechanisms for reprogramming deployed sensor networks. However, all of these mechanisms produce large patches if software modifications involve changing program layouts and shifting global variables. In addition, existing mechanisms use large amounts of external flash and rewrite entire internal flash. In this thesis, we present a differential reprogramming mechanism called QDiff that mitigates the effects of program layout modifications and retains maximum similarity between old and new software using a clone detection mechanism. Moreover, QDiff organizes the global variables in a novel way that eliminates the effect of variable shifting. Our experiments show that QDiff requires near-zero external flash, and significantly lower internal flash rewriting and transmission overhead than leading existing differential reprogramming mechanisms. / Thesis (Master, Computing) -- Queen's University, 2011-11-29 14:11:44.138

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An understanding of network traffic behavior is essential in the evolution of today's wireless networks, and thus leads to a more efficient planning and management of the network's scarce bandwidth resources. Prior reservation of radio resources at the future locations of a user's mobile travel path can assist with optimizing the allocation of the network's limited resources. Such actions are intended to support the network with sustaining a desirable Quality-of-Service (QoS) level. To help ensure the availability of the network services to its users at anywhere and anytime, there is the need to predict when and where a user will demand any network usage. In this thesis, the mobility behavior of the wireless users are modeled as a Markov renewal process for predicting the likelihoods of the next-cell transition. The model also includes anticipating the duration between the transitions for an arbitrary user in a wireless network. The proposed prediction technique is further extended to compute the likelihoods of a user being in a particular state after $N$ transitions. This technique can also be applied for estimating the future spatial-temporal traffic load and activity at each location in a network's coverage area. The proposed prediction method is evaluated using some real traffic data to illustrate how it can lead to a significant improvement over some of the conventional methods. The work considers both the cases of mobile users with homogeneous applications (e.g. voice calls) and data connectivity with varying data loads being transferred between the different locations.

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