Thesis (M.S. in computer science)--Washington State University, December 2009. / Title from PDF title page (viewed on Jan. 20, 2010). "School of Electrical Engineering and Computer Science." Includes bibliographical references (p. 60-64).

Dissertation (Ph.D.)--Auburn University, 2009. / Abstract. Vita. Includes bibliographic references (p.131-139).

Thesis (M. Sc.)--University of Alberta, 2009. / Title from PDF file main screen (viewed on Feb. 19, 2010). A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science, Department of Computing Science, University of Alberta. Includes bibliographical references.

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

Wireless sensor network localization opens the door to many location based applications. In this thesis, some solutions obtained from localization algorithms are investigated. There are two categories of problem on localization. Range-based methods are applied to the situation in which information on the distances between each pair of nodes is available. Algorithms are developed to estimate the location of each sensor in the network. Usually, the distance between each pair of nodes is estimated by the signal strength received between them, and this information is very noisy. Range-free methods, which are also called connectivity-based methods, assume that the distances between any two nodes are unknown but the connectivity information between them is known. If the distance between any two nodes in the network is within a communication range, connectivity between these two nodes is said to be established. In a range-based scenario, with the information of inter-sensor distance measurements as well as the absolute locations of the anchors, the objective is to obtain the location of all the unknown nodes. Two new localization methods based on gradient descent are shown in the thesis. The gradient descent methods would minimize the difference between the measured distances and the distances obtained from the estimated locations. From a comparison with other well-known localization methods, the two newly developed gradient descent algorithms can reach better accuracy at the expense of computational complexity. This is not surprising as the proposed algorithms are iterative in nature. For range-free scenario, a new model utilizing all the information derived from connectivity-based sensor network localization is introduced. Unlike other algorithms which only utilize the information on connections, this model makes use of both information on connections and disconnections between any pair of nodes. The connectivity information between any pair of nodes is modeled as convex and non-convex constraints. The localization problem is solved by an optimization algorithm to obtain a solution that would satisfy all the constraints established in the problem. The simulation has shown that better accuracy is obtained when compared with algorithms developed by other researchers. Another solution for the range-free scenario is obtained with the use of a two-objective evolutionary algorithm called Pareto Archived Evolution Strategy (PAES). In an evolutionary algorithm, the aim is to search for a solution that would satisfy all the convex and non-convex constraints of the problem. The number of wrong connections and the summation of corresponding distances are set as the two objectives. A starting point on the location of the unknown nodes is obtained using a solution from the result of all convex constraints. The final solution can reach the most suitable configuration of the unknown nodes as all the information on the constraints (convex and non-convex) related to connectivity have been used. From the simulation results, a relationship between the communication range and accuracy is obtained. In this thesis, another evolutionary algorithm has been examined to obtain a solution for our problem. The solution is based on a modified differential evolution algorithm with heuristic procedures peculiar to our domain of application. The characteristics of the sensor network localization are thoroughly investigated and utilized to produce corresponding treatment to search for the reasonable node locations. The modified differential evolution algorithm uses a new crossover step that is based on the characteristics of the problem. With the combination of some heuristics, the solution search can move the node to jump out of local minimums more easily, and give better accuracy than current algorithms. In the last part of the thesis, a novel two-level range connectivity-based sensor network localization problem is proposed, which would enrich the connectivity information. In this new problem, the information of the connectivity between any pair of nodes is either strong, weak or zero. Again, a two-objective evolutionary algorithm is used to search for a solution that would satisfy all the convex and non-convex constraints of the problem. Based on simulations on a range of situations, a suitable range value for the second range is found. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / This paper describes some of the security challenges faced by Wireless Sensor Networks (WSN). A classification and analysis of prominent attacks on the routing protocols of WSN is provided, along with a review of recent developments in the field to help mitigate the impact of these attacks.

Along with the rapid growth of Wireless Sensor Networks, a wide range of challenges have come to existence to make the network more robust and versatile. Gaining energy efficiency and maximizing network lifetime are the most important of all that can affect the performance of the network directly. In this thesis, a number of research aspects related to energy efficient data gathering have been investigated and some promising proposals are presented. In large, hierarchical multi-hop Wireless Sensor Networks, power consumption characteristics of the static sensor nodes and data traffic distribution across the network are largely determined by the node position and the adopted routing protocol. In this thesis, these phenomena of the network are addressed analytically and we proposed some methods to divide the monitoring field into partitions that act as the basis for even load distribution in the network. We proposed an algorithm to calculate the area of the partitions that exploits the energy efficient features of optimal transmission range. The partition works as the bedrock of the other proposals in this thesis. Considering the influential factors of the proximity and the recent state of the network, we also developed a routing protocol that minimises over all energy consumption of the network and is able to dynamically select a route to the sink. Further, we proposed a rotational order for data gathering scheme that works along with the routing protocol to ensure load balancing and to alleviate data congestion around the sink. Clustered organization of the nodes in sensor networks can further save energy consumption and facilitates scope for better network management. In this thesis, we address the fact that equal sized clusters can cause unbalanced data traffic around the sink. So, we propose a method to calculate suitable cluster radii in different regions of the monitoring field in order to form clusters of different sizes. To ensure unequal clusters in the field, a cluster construction procedure is also proposed targeting minimal data generation, minimal energy consumption and providing capacity for reliability preservation. Furthermore, the notion of redundant nodes and the outlines of a possible solution to identify and deactivate redundant nodes are explained in this thesis. Since the clusterheads play an important role as coordinators in the clusters, it is vital that there is a clusterhead in every cluster all the time. In this thesis, a message optimal and distributed leader election algorithm is proposed to select a new clusterhead in case of unexpected and unnoticed failure of a clusterhead node. Detailed analysis and simulation of the proposed methods clarify the effectiveness of the research. In comparison with other methods of similar kind, our methods confirm better balanced energy dissipation, energy efficient route selection, message optimal clusterhead selection and prolonged lifetime of the network.

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.

Recent advances in wireless and sensing technologies have enabled the deployment of large scale Wireless Sensor Networks (WSNs) which have a wide range of scientific and commercial applications. However, due to the limited energy supply of sensor nodes, extending the network lifetime has become crucial for WSNs to deliver their promised benefits. Several proposals have aimed at this objective by designing energy efficient protocols at the physical, medium access, and network layers. While the proposed protocols achieve significant energy savings for individual sensor nodes, they fail to solve topology-related problems. An example of such problems is the bottlenecks around the sink, which is a direct result of multi-hop relaying: sensor nodes around the sink relay data generated all over the network which makes them deplete their energy much faster than other nodes. A natural solution to this problem is to have multiple mobile data collectors so that the load is distributed evenly among all nodes. We investigate this promising direction for balancing the load and, hence, prolonging the lifetime of the network. We design optimization schemes for routing and placement of mobile data collectors in WSNs. We show, by theoretical analysis and simulations, that our approach has the potential to prolong the lifetime of the network significantly. / Thesis (Ph.D, Computing) -- Queen's University, 2009-04-26 21:58:55.152