In this thesis, we propose and evaluate algorithms for solving the worst-case-coverage deployment problem in ad-hoc wireless sensor networks. The worst-case-coverage deployment problem is to deploy additional sensors in the wireless sensor field to optimize the worst-case coverage. We derive a duality theorem that reveals the close relation between the maximum breach path and the minimum Delaunay cut. The duality theorem is similar to the well-known max-flow-min-cut theorem in the field of network optimization. The major difference lies in the fact that the object function we study in this paper is nonlinear rather than linear. Based on the duality theorem, we propose an efficient dual algorithm to solve the worst-case-coverage deployment problem. In addition, we propose a genetic algorithm for deploying a number of additional sensors simultaneously. We use analytical proofs and simulation results to justify the usage of the proposed approaches.

The baseband part of IEEE 802.15.4 operated in 2.45 GHz mode is designed and implemented in this essay. First, the features of IEEE 802.15.4 WPAN(Wireless Personal Area Network), PHY layer and MAC Layer are introduced. Then the algorithm and VHDL of the baseband part of transceiver are designed and verified by FPGA board and logical analyzer.

Under the current environment of Wireless Senor Networks (WSN), security is always one of the topics that everyone discussed about. Because of the limitations of WSN¡¦s unique resource, this results in the security of WSN needs to especially consider the calculating ability, memory capacity, characteristics of wireless communication, limited battery power supply, etc. Random key pre-distribution (RKP) is the one of the key distribution that is developed for the sake of safe communication of WSN, the characteristic of RKP is that there must have at least one common pre-distributed key in the two independent nodes in order to compose a pair-wise key, so that the safe communication can be carried out. However, if the nodes are distributed in the loose environment, the numbers of neighbors would be lower due to the decrease of average node degree. Then the connectivity of the entire network would decrease because it is not easy for the RKP to establish the pair-wise key. This paper would set the improvement of the entire network¡¦s connectivity under the loose environment as the starting point to extend the RKP-DE that only considers one-hop neighbor information, and reverse the flow path of RKP-DE and propose RKP- DEinverse from the viewpoint of two-hop neighbor information. Then RKP-DE and RKP- DEinverse are merged and become a new method ¡V RKP- DEtwo_hop, so as to try to prove that we can raise the connectivity of the whole network effectively.

In the environment of wireless sensor network, while one node want to send a message to another node, the most natural way is used broadcasting to distribute the message to the whole network. In the other words, as long as one node sends messages to the other node, its neighbor nodes can also listen to these messages, and then receive them. The advantage of broadcast networks is that can efficiently distribute data to multiple receivers. However, it has some drawbacks. A sensor network may be deployed in hostile environment where there are malicious attacks. The malicious attacker can send false messages to his neighbor nodes, and then rely on these neighbor nodes to distribute over the network. So if there are not any schemes of the security authentication in the message when a node wants to use broadcast, everyone can impersonate the sender and broadcast false messages. We call this a packet injection attack. So security is a main challenge in broadcast network. In order to authenticate a broadcast message¡Ait would conform to two conditions. First, insure that the data is transmitted from the claimed source. Second, the messages are not be modified en route. TESLA has been proposed to provide such services for sensor networks¡Ait mainly use time synchronization and delay disclosure key to protect encryption key¡CHowever, this scheme still has some drawbacks, so we propose some schemes to modify TESLA in this paper, and we will show these schemes can achieve better performance than previous ones.

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.

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