525 research outputs found

    Clustered wireless sensor networks

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    The study of topology in randomly deployed wireless sensor networks (WSNs) is important in addressing the fundamental issue of stochastic coverage resulting from randomness in the deployment procedure and power management algorithms. This dissertation defines and studies clustered WSNs, WSNs whose topology due to the deployment procedure and the application requirements results in the phenomenon of clustering or clumping of nodes. The first part of this dissertation analyzes a range of topologies of clustered WSNs and their impact on the primary sensing objectives of coverage and connectivity. By exploiting the inherent advantages of clustered topologies of nodes, this dissertation presents techniques for optimizing the primary performance metrics of power consumption and network capacity. It analyzes clustering in the presence of obstacles, and studies varying levels of redundancy to determine the probability of coverage in the network. The proposed models for clustered WSNs embrace the domain of a wide range of topologies that are prevalent in actual real-world deployment scenarios, and call for clustering-specific protocols to enhance network performance. It has been shown that power management algorithms tailored to various clustering scenarios optimize the level of active coverage and maximize the network lifetime. The second part of this dissertation addresses the problem of edge effects and heavy traffic on queuing in clustered WSNs. In particular, an admission control model called directed ignoring model has been developed that aims to minimize the impact of edge effects in queuing by improving queuing metrics such as packet loss and wait time

    Reliable cost-optimal deployment of wireless sensor networks

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    Wireless Sensor Networks (WSNs) technology is currently considered one of the key technologies for realizing the Internet of Things (IoT). Many of the important WSNs applications are critical in nature such that the failure of the WSN to carry out its required tasks can have serious detrimental effects. Consequently, guaranteeing that the WSN functions satisfactorily during its intended mission time, i.e. the WSN is reliable, is one of the fundamental requirements of the network deployment strategy. Achieving this requirement at a minimum deployment cost is particularly important for critical applications in which deployed SNs are equipped with expensive hardware. However, WSN reliability, defined in the traditional sense, especially in conjunction with minimizing the deployment cost, has not been considered as a deployment requirement in existing WSN deployment algorithms to the best of our knowledge. Addressing this major limitation is the central focus of this dissertation. We define the reliable cost-optimal WSN deployment as the one that has minimum deployment cost with a reliability level that meets or exceeds a minimum level specified by the targeted application. We coin the problem of finding such deployments, for a given set of application-specific parameters, the Minimum-Cost Reliability-Constrained Sensor Node Deployment Problem (MCRC-SDP). To accomplish the aim of the dissertation, we propose a novel WSN reliability metric which adopts a more accurate SN model than the model used in the existing metrics. The proposed reliability metric is used to formulate the MCRC-SDP as a constrained combinatorial optimization problem which we prove to be NP-Complete. Two heuristic WSN deployment optimization algorithms are then developed to find high quality solutions for the MCRC-SDP. Finally, we investigate the practical realization of the techniques that we developed as solutions of the MCRC-SDP. For this purpose, we discuss why existing WSN Topology Control Protocols (TCPs) are not suitable for managing such reliable cost-optimal deployments. Accordingly, we propose a practical TCP that is suitable for managing the sleep/active cycles of the redundant SNs in such deployments. Experimental results suggest that the proposed TCP\u27s overhead and network Time To Repair (TTR) are relatively low which demonstrates the applicability of our proposed deployment solution in practice

    Routing and scheduling approaches for energy-efficient data gathering in wireless sensor networks

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    Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2011.Thesis (Ph. D.) -- Bilkent University, 2011.Includes bibliographical references leaves 99-108.A wireless sensor network consists of nodes which are capable of sensing an environment and wirelessly communicating with each other to gather the sensed data to a central location. Besides the advantages for many applications, having very limited irreplaceable energy resources is an important shortcoming of the wireless sensor networks. In this thesis, we present effective routing and node scheduling solutions to improve network lifetime in wireless sensor networks for data gathering applications. Towards this goal, we first investigate the network lifetime problem by developing a theoretical model which assumes perfect data aggregation and power-control capability for the nodes; and we derive an upper-bound on the functional lifetime of a sensor network. Then we propose a routing protocol to improve network lifetime close to this upper-bound on some certain conditions. Our proposed routing protocol, called L-PEDAP, is based on constructing localized, self-organizing, robust and power-aware data aggregation trees. We also propose a node scheduling protocol that can work with our routing protocol together to improve network lifetime further. Our node scheduling protocol, called PENS, keeps an optimal number of nodes active to achieve minimum energy consumption in a round, and puts the remaining nodes into sleep mode for a while. Under some conditions, the optimum number can be greater than the minimum number of nodes required to cover an area. We also derive the conditions under which keeping more nodes alive can be more energy efficient. The extensive simulation experiments we performed to evaluate our PEDAP and PENS protocols show that they can be effective methods to improve wireless sensor network lifetime for data gathering applications where nodes have power-control capability and where perfect data aggregation can be used.Tan, Hüseyin ÖzgürPh.D

    Improved Coverage and Connectivity via Weighted Node Deployment in Solar Insecticidal Lamp Internet of Things

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    As an important physical control technology, Solar Insecticidal Lamp (SIL) can effectively prevent and control the occurrence of pests. The combination of SILs andWireless Sensor Networks (WSNs) initiates a novel agricultural Internet of Things (IoT), i.e., SIL-IoTs, to simultaneously kill pests and transmit pest information. In this paper, we study the weighted SIL Deployment Problem (wSILDP) in SIL-IoTs, where weighted locations on ridges are prespecified and some of them are selected to deploy SILs. Different from the existing studies whose optimization objective is to minimise the deployment cost, we consider the deployment cost and the total weight of selected locations jointly. We formulate the wSILDP as the Weighted Set Cover (WSC) problem and propose a Layered Deployment Method based on Greedy Algorithm (LDMGA) to solve the defined optimization problem. The LDMGA is composed of two phases. Firstly, SILs are deployed layer by layer from the boundary to the centre until the entire farmland is completely covered. Secondly, on the basis of three design operations, i.e., substitution, deletion and fusion, the suboptimal locations obtained in the first phase are fine-tuned to achieve the minimum deployment cost together with the maximum total weight for meeting the coverage and connectivity requirements. Simulation results clearly demonstrate that the proposed method outperforms three peer algorithms in terms of deployment cost and total weight

    Interference Reduction in Mobile Ad Hoc and Sensor Networks

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    There are still a lot of open questions in the field of MANETs and sensor networks. If a topology incurs a large interference, either many communication signals sent by nodes will collide, or the network may experience a serious delay at delivering the data for some nodes, and even consume more energy. So, we reach to the conclusion that interference imposes a potential negative impact on the performance of wireless networks. In the last few years, researchers actively explored topology control approaches for such networks. The motivation of topology control (TC) is to maintain the connectivity of the network, reduce the node degree and thereby reduce the interference, and reduce power consumption in the sensor nodes. Some literatures have pointed out that a node can interfere with another node even if it is beyond its communication range. To improve the network performance, designing topology control algorithms with consideration of interference is imminent and necessary. Since, it leads to fewer collisions and packet retransmissions, which indirectly reduces the power consumption and extends the lifetime of the network. In this thesis, we propose a new interference-aware connected dominating set-based topology construction algorithm, namely, IACDS algorithm, a simple, distributed, interference-aware and energy-efficient topology construction mechanism that finds a sub-optimal Connected Dominating Set (CDS) to turn unnecessary nodes off while keeping the network connected and providing complete communication coverage with minimum interference. IACDS algorithm utilizes a weighted (distance-energy-interference)-based metric that permits the network operator to trade off the lengths of the branches (distance) for the robustness and durability of the topology (energy and interference)

    Robust deployment and control of sensors in wireless monitoring networks

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    Advances in Micro Electro-Mechanical Systems (MEMS) technology, including MEMS sensors, have allowed the deployment of small, inexpensive, energy-efficient sensors with wireless networking capabilities. The continuing development of these technologies has given rise to increased interest in the concept of wireless sensor networks (WSNs). A WSN is composed of a large number (hundreds, even thousands) of sensor nodes, each consisting of sensing, data processing, and communication components. The sensors are deployed onto a region of interest and form a network to directly sense and report on physical phenomena. The goal of a monitoring wireless sensor network is to gather sensor data from a specified region and relay this information to a designated base station (BSt). In this study, we focus on deploying and replenishing wireless sensor nodes onto an area such that a given mission lifetime is met subject to constraints on cost, connectivity, and coverage of the area of interest. The major contributions of this work are (1) a technique for differential deployment (meaning that nodes are deployed with different densities depending on their distance from the base station); the resulting clustered architecture extends lifetime beyond network lifetime experienced with a uniform deployment and other existing differential techniques; (2) a characterization of the energy consumption in a clustered network and the energy remaining after network failure, this characterization includes the overhead costs associated with creating hierarchies and retrieving data from all sensors ; (3) a characterization of the effects and costs associated with hop counts in the network; (4) a strategy for replenishing nodes consisting of determining the optimal order size and the allocation over the deployment region. The impact of replenishment is also integrated into the network control model using intervention analysis. The result is a set of algorithms that provide differential deployment densities for nodes (clusterhead and non-clusterhead) that maximize network lifetime and minimize wasted energy. If a single deployment is not feasible, the optimal replenishment strategy that minimizes deployment costs and penalties is calculated.Ph.D., Electrical Engineering -- Drexel University, 201

    Optimal UAS Assignments and Trajectories for Persistent Surveillance and Data Collection from a Wireless Sensor Network

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    This research developed a method for multiple Unmanned Aircraft Systems (UAS) to efficiently collect data from a Wireless Sensor Networks (WSN). WSN are composed of any number of fixed, ground-based sensors that collect and upload local environmental data to over flying UAS. The three-step method first uniquely assigns aircraft to specific sensors on the ground. Second, an efficient flight path is calculated to minimize the aircraft flight time required to verify their assigned sensors. Finally, sensors reporting relatively higher rates of local environmental activity are re-assigned to dedicated aircraft tasked with concentrating on only those sensors. This work was sponsored by the Air Force Research Laboratory, Control Sciences branch, at Wright Patterson AFB. Based on simulated scenarios and preliminary flight tests, optimal flight paths resulted in a 14 to 32 reduction in flight time and distance when compared to traditional flight planning methods
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