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Wireless sensor networks (WSNs) are employed in various applications from healthcare to military. Due to their limited, tiny power sources, energy becomes the most precious resource for sensor nodes in such networks. To optimize the usage of energy resources, researchers have proposed several ideas from diversified angles. Clustering of nodes plays an important role in conserving energy of WSNs. Clustering approaches focus on resolving the conflicts arising in effective data transmission. In this chapter, we have outlined a few modern energy-efficient clustering approaches to improve the lifetime of WSNs. The proposed clustering methods are: (i) fuzzy-logic-based cluster head election, (ii) efficient sleep duty cycle for sensor nodes, (iii) hierarchical clustering, and (iv) estimated energy harvesting. Classical clustering approaches such as low energy adaptive clustering hierarchy (LEACH) and selected contemporary clustering methods are considered for comparing the performance of proposed approaches. The proposed modern clustering approaches exhibit better lifetime compared to the selected benchmarked protocols.

Sensor nodes have limited processing power, small storage capacity and limited energy. These constraints make classical security algorithms unsuitable for WSNs (Wireless Sensor Networks). Therefore, new techniques that consider these limitations are needed. WSNs have a wide range of applications, including military field surveillance, healthcare, homeland security, industrial control, and intelligent green aircraft. Therefore, network security has become increasingly important. There are various types of attacks that may cause security problems, such as modification attacks and selective forwarding attacks. This thesis investigates three security problems in WSNs. Firstly, we investigate the problem of minimizing the failure rate of packet delivery in the presence of modification attacks and selective forwarding attacks in a static WSN with one base station without using expensive encryption/decryption algorithms. We propose a novel heuristic approach to this problem. Our approach is based on randomized multipath routing. Secondly, we investigate the problem of constructing a shortest path overhearing tree with the maximum lifetime for data collection. We propose three approaches for homogeneous WSNs and heterogeneous WSNs. The first one is a polynomial-time heuristic approach. The second one uses ILP (Integer Linear Programming) to iteratively find a monitoring node and a parent for each sensor node. The last one optimally solves the problem by using MINLP (Mixed- Integer Non-Linear Programming). Lastly, we investigate the reliable and secure end-to-end data aggregation problem considering selective forwarding attacks and modification attacks in homogeneous cluster-based WSNs, and propose three data aggregation approaches which can defend against both modification attacks and selective forwarding attacks. Our approaches use secret sharing and signatures to allow aggregators to aggregate the data without understanding the contents of messages and the base station to verify the aggregated data and retrieve the ...

Collaborative Resource Allocation in Wireless Sensor Networks The new millennium heralds the convergence of communication, computing and intelligent control of the physical environment. The rapid advancement of computing and wireless technologies will enable us to employ cooperative real-time nodes in hostile environments in order to accomplish different tasks ranging from space monitoring and surveillance, to environmental protection without human intervention. Under this challenging vision, there will be an extensive deployment of highly dynamic and physically constrained real-time nodes connected together. Cooperative mobile robots, equipped with visual sensing, used in hostile/dangerous environments to clean up highly polluted spots or to remove mines or to defuse bombs. Cooperative real-time nodes, equipped with acoustic and visual sensing, used for surveillance in wide open spaces. Network of multifunction phase array radars (this is an example of real-time systems with physical constraints) used for air-traffic control or for military purpose such as detecting/tracking hostile targets. It's worth noting that all the applications mentioned above are characterized by a high degree of fluctuation in terms of computational and/or networking resource requirements. However, the causes of such a dynamic behavior are different in fact; for example, visual tracking is the main cause of highly variable workload in cooperative robots equipped with visual sensing, while, on the other hand, variable number of tracked targets and state dependent tasks cause highly dynamic workload in radar systems. When several real-time nodes are connected together, the need for collaboration in a timely manner creates the following challenging problems: Handling highly dynamic workloads among collaborative nodes. Under the three major problems above identified, this thesis will focus primarily on issues like collaborative scheduling and prioritized medium access protocols. tasks running on different nodes can be tightly coupled in a system where several real-time nodes cooperate. The goal is to develop distributed rate adaptation and collaborative resource reclaiming techniques aimed at mitigating the effects of highly dynamic workloads in distributed real-time system composed of collaborative nodes. It is worth noting that the degradation of performance of one task might affect the performance of other tasks running on different nodes ( task problem due to local rate adaptation), or locally reclaimed resources could increase a task rate without improving the overall system performance. Prioritized Medium Access with rate adaptive messages: traditional medium access control (MAC) are not suitable to build wireless sensor networks of collaborative real-time nodes because messages exchanged inside the network are mainly periodic and need guaranteed bounded delay. As a consequence, we will try to address the following medium access issues: Prioritizing the medium access to provide messages with bounded delay, and Providing rate adaptive messages in order to achieve the concept of distributed rate adaptation.

Intro -- Contents -- 1 Introduction -- Abstract -- 2 Application of Dense Offshore Tsunami Observations from Ocean Bottom Pressure Gauges (OBPGs) for Tsunami Research and Early Warnings -- Abstract -- 1 Introduction and Background -- 2 Data and Different Types of OBS Pressure Gauges -- 3 Methodology -- 4 Case Study One: The 2012 Haida Gwaii Tsunami, Offshore Canada -- 5 Case Study Two: The 2009 Dusky Sound Tsunami, Offshore New Zealand -- 6 Conclusions -- Acknowledgements -- References -- 3 Remote Sensing for Natural or Man-Made Disasters and Environmental Changes -- Abstract -- 1 Introduction -- 2 St. Lucia Case Study -- 3 Papanice Case Study -- 4 Sendai Case Study -- 5 Discussion and Conclusions -- Acknowledgements -- References -- 4 Classification of Post-earthquake High Resolution Image Using Adaptive Dynamic Region Merging and Gravitational Self-Organizing Maps -- Abstract -- 1 Introduction -- 2 Methodology -- 2.1 Feature Extraction -- 2.2 Adaptive Region Descriptor -- 2.3 Dynamic Region Merging -- 2.4 gSOM Clustering -- 2.5 Clustering Ensemble -- 3 Experiments -- 3.1 Survey Area and Data Description -- 3.2 Experiment Setups -- 3.2.1 ADRM Segmentation Evaluation -- 3.2.2 gSOM Classification Evaluation -- 4 Conclusion -- Acknowledgments -- References -- 5 A Survey on the Role of Wireless Sensor Networks and IoT in Disaster Management -- Abstract -- 1 Introduction -- 2 WSN Driven Disaster Monitoring and Management Systems -- 2.1 Applications of Sensor Networks in Disasters Management -- 2.2 5G and Device to Device Communication -- 2.3 Software Defined Radio -- 2.4 Cognitive Radio (CR) -- 2.5 Indoor Position Technologies -- 2.6 Disaster Situation Aware Protocols for Mobile Devices -- 2.7 Mobile Phone Disaster Mode -- 3 Existing IoT Standards: LoRa/4G LTE -- 3.1 LoRa -- 3.1.1 Limitations of LoRaWAN -- 3.2 4G LTE -- 3.2.1 Limitations of 4G LTE.

Wireless sensor networks have garnered considerable attention recently. Networks typically have many sensor nodes, and are used in commercial, medical, scientific, and military applications for sensing and monitoring the physical world. Many researchers have attempted to improve wireless sensor network management efficiency. A Simple Network Management Protocol (SNMP)-based sensor network management system was developed that is a convenient and effective way for managers to monitor and control sensor network operations. This paper proposes a novel WSNManagement system that can show the connections stated of relationships among sensor nodes and can be used for monitoring, collecting, and analyzing information obtained by wireless sensor networks. The proposed network management system uses collected information for system configuration. The function of performance analysis facilitates convenient management of sensors. Experimental results show that the proposed method enhances the alive rate of an overall sensor node system, reduces the packet lost rate by roughly 5%, and reduces delay time by roughly 0.2 seconds. Performance analysis demonstrates that the proposed system is effective for wireless sensor network management.

Over the past fifteen years, advances in Micro-Electro-Mechanical Systems (MEMS) technology have enabled rapid development of wireless sensor networks (WSNs). A WSN consists of a large number of sensor nodes that are typically powered by batteries. Each sensor node collects useful information from its environment, and forwards this data to a base station through wireless communications. Applications of WSNs include environmental monitoring, industrial monitoring, agriculture, smart home monitoring, military surveillance, to name a few. Due to battery constraint at each sensor node, a fundamental challenge for a WSN is its limited operational lifetime -- the amount of time that the network can remain operational before some or all of the sensor nodes run out of battery. To conserve energy and prolong the lifetime of a WSN, there have been active research efforts across all network layers. Although these efforts help conserve energy usage and prolong network lifetime to some extent, energy and lifetime remain fundamental bottlenecks and are the key factors that hinder the wide-scale deployment of WSNs. This dissertation addresses the energy problem of a WSN by exploiting a recent breakthrough in wireless energy transfer (WET) technology. This breakthrough WET technology is based on the so-called magnetic resonant coupling (MRC), which allows electric energy to be transferred from a source coil to a receive coil without any plugs or wires. The advantages of MRC are high energy transfer efficiency even under omni-direction, not requiring line-of-sight (LOS), and being robust against environmental conditions. Inspired by this enabling WET technology, this dissertation focuses on applying MRC to a WSN and on studying how to optimally use this technology to address lifetime problem for a WSN. The goal is to fundamentally remove lifetime bottleneck for a WSN. The main contributions of this dissertation are summarized as follows: 1. Single-node Charging for a Sparse WSN. We first investigate how MRC can be applied to a WSN so as to remove the lifetime performance bottleneck in a WSN, i.e., allowing a WSN to remain operational forever. We consider the scenario of a mobile wireless charging vehicle (WCV) periodically traveling inside the sensor network and charging each sensor node's battery wirelessly. We introduce the concept of renewable energy cycle and offer both necessary and sufficient conditions for a sensor node to maintain its renewable energy cycle. We study an optimization problem, with the objective of maximizing the ratio of the WCV's vacation time over the cycle time. For this problem, we prove that the optimal traveling path for the WCV is the shortest Hamiltonian cycle and uncover a number of important properties. Subsequently, we develop a near-optimal solution by a piecewise linear approximation technique and prove its performance guarantee. This first study shows that network lifetime bottleneck can be fundamentally resolved by WET. 2. Multi-node Charging for a Dense WSN. We next exploit recent advances in MRC that allows multiple sensor nodes to be charged at the same time, and show how MRC with multi-node charging capability can address the scalability problem associated with the single-node charging technology. We consider a WCV that periodically travels inside a WSN and can charge multiple sensor nodes simultaneously. Based on the charging range of the WCV, we propose a cellular structure that partitions the two-dimensional plane into adjacent hexagonal cells. We pursue a formal optimization framework by jointly optimizing the traveling path of the WCV, flow routing among the sensor nodes, and the charging time with each hexagonal cell. By employing discretization and a novel Reformulation-Linearization Technique (RLT), we develop a provably near-optimal solution for any desired level of accuracy. Through numerical results, we demonstrate that our solution can indeed address the scalability problem for WET in a dense WSN. 3. Bundling Mobile Base Station and Wireless Energy Transfer: The Pre-planned Path Case. Our aforementioned work is based on the assumption that the location of base station is fixed and known in the WSN. On the other hand, it has been recognized that a mobile base station (MBS) can offer significant advantages over a fixed one. But employing two separate vehicles, one for WET and one for MBS, could be expensive and hard to manage. So a natural question to ask is: can we bundle WET and MBS on the same vehicle? This is the focus of this study. Here, our goal is to minimize energy consumption of the entire system while ensuring that none of the sensor nodes runs out of energy. To simplify the problem, we assume that the path for the vehicle is given a priori. We develop a mathematical model for this problem. Instead of studying the general problem formulation (called CoP-t), which is time-dependent, we show that it is sufficient to study a special subproblem (called CoP-s), which only involves space-dependent variables. Subsequently, we develop a provable near-optimal solution to CoP-s with the development of several novel techniques including discretizing a continuous path into a finite number of segments and representing each segment with worst-case energy bounds. 4. Bundling Mobile Base Station and Wireless Energy Transfer: The Unconstrained Path Case. Based on our experience for the pre-planned path case, we further study the problem where the traveling path of the WCV (also carrying the MBS) can be unconstrained. That is, we study an optimization problem that jointly optimizes the traveling path, stopping points, charging schedule, and flow routing. For this problem, we propose a two-step solution. First, we study an idealized problem that assumes zero traveling time, and develop a provably near-optimal solution to this idealized problem. In the second step, we show how to develop a practical solution with non-zero traveling time and quantify the performance gap between this solution and the unknown optimal solution to the original problem. This dissertation offers the first systematic investigation on how WET (in particular, the MRC technology) can be exploited to address lifetime bottleneck of a WSN. It lays the foundation of exploring WET for WSNs and other energy-constrained wireless networks. On the mathematical side, we have developed or applied a number of powerful techniques such as piecewise linear approximation, RLT, time-space transformation, discretization, and logical point representation that may be applicable to address a broad class of optimization problems in wireless networks. We expect that this dissertation will open up new research directions on many interesting networking problems that can take advantage of the WET technology. ; Ph. D.

Over the past decades, the progress inWirelss Sensor Network (WSN) technology, both in terms of processing capability and energy consumption reduction, has evolved WSNs into complex systems that can gather information about the monitored environment and make prompt and intelligent decisions. In the beginning, military applications drove the research and development of WSNs, with large-scale acoustic systems for underwater surveillance, radar systems for the collection of data on air targets, and Unattended Ground Sensor (UGS) systems for ground target detection. Typical civil WSNs are basically not complex monitoring systems, whose applications encompass environment and habitat monitoring, infrastructure security and terror threat alerts, industrial sensing for machine health monitoring, and traffic control. In these WSNs, sensors gather the required information, mostly according to a fixed temporal schedule, and send it to the sink, which interfaces with a server or a computer. Only at this point data from sensors can be processed, before being stored. Recent advances in Micro-Eletro-Mechanical Systems (MEMS), low power transceivers and microprocessor dimensions have led to cost effective tiny sensor devices that combine sensing with computation, storage and communication. These developments have contributed to the efforts on interfacing WSNs with other technologies, enabling them to be one of the pillars of the Internet of Things (IoT) paradigm. In this context, WSNs take a key role in application areas such as domotics, assisted living, e-health, enhanced learning automation and industrial manufacturing logistics, business/process management, and intelligent transportation of people and goods. In doing so, a horizontal ambient intelligent infrastructure is made possible, wherein the sensing, computing and communicating tasks can be completed using programmable middleware that enables quick deployment of different applications and services. One of the major issues with WSNs is the energy scarcity, due to the fact that sensors are mainly battery powered. In several cases, nodes are deployed in hostile or unpractical environments, such as underground or underwater, where replacing battery could be an unfeasible operation. Therefore, extending the network lifetime is a crucial concern. Lifetime improvement has been approached by many recent studies, from different points of view, including node deployment, routing schemes, and data aggregation Recently, with the consistent increase in WSN application complexity, the way distributed applications are deployed in WSNs is another important component that affects the network lifetime. For instance, incorrect execution of data processing in some nodes or the transmission of big amounts of data with low entropy in some nodes could heavily deplete battery energy without any benefit. Indeed, application tasks are usually assigned statically to WSN nodes, which is an approach in contrast with the dynamic nature of future WSNs, where nodes frequently join and leave the network and applications change over the time. This brings to issue talked in this thesis, which is defined as follows. Dynamic deployment of distributed applications in WSNs: given the requirements of WSN applications, mostly in terms of execution time and data processing, the optimal allocation of tasks among the nodes should be identified so as to reach the application target and to satisfy the requirements while optimizing the network performance in terms of network lifetime. This issue should be continuously addressed to dynamically adapt the system to changes in terms of application requirements and network topology.

Mobile sensor networking technology has attracted considerable attention in various research communities in recent years due to their widespread applications in civilian and military environments. One objective when using mobile sensors is to obtain maximum field coverage by properly deploying sensor nodes. In many real-world applications a priori knowledge about the best deployment position for the sensors is not available. However, the motion capability of the sensors could allow each node to adjust its position (i.e. relocate) so that a better (and ultimately maximal) coverage is achieved. In this paper, a novel autonomous joint sensing range and relocation control algorithm is presented that achieves improved coverage and network lifetime at the same time. In the proposed algorithm, the sensing range of each sensor is adjusted iteratively based on its residual energy. At the same time, the sensor is directed to move within its corresponding multiplicatively weighted Voronoi (MW-Voronoi) region to ultimately increase sensing coverage in the field. Simulation results demonstrate the efficacy of the technique.

With the growing use of underwater acoustic communications (UWAC) for both industrial and military operations, there is a need to ensure communication security. A particular challenge is represented by underwater acoustic networks (UWANs), which are often left unattended over long periods of time. Currently, due to physical and performance limitations, UWAC packets rarely include encryption, leaving the UWAN exposed to external attacks faking legitimate messages. In this paper, we propose a new algorithm for message authentication in a UWAN setting. We begin by observing that, due to the strong spatial dependency of the underwater acoustic channel, an attacker can attempt to mimic the channel associated with the legitimate transmitter only for a small set of receivers, typically just for a single one. Taking this into account, our scheme relies on trusted nodes that independently help a sink node in the authentication process. For each incoming packet, the sink fuses beliefs evaluated by the trusted nodes to reach an authentication decision. These beliefs are based on estimated statistical channel parameters, chosen to be the most sensitive to the transmitter-receiver displacement. Our simulation results show accurate identification of an attacker's packet. We also report results from a sea experiment demonstrating the effectiveness of our approach. ; pub

Designing secure sensor networks is difficult. We propose an approach that uses multicast communications and requires fewer encryptions than pairwise communications. The network is partitioned into multicast regions; each region is managed by a sensor node chosen to act as a keyserver. The keyservers solicit nodes in their neighborhood to join the local multicast tree. The keyserver generates a binary tree of keys to maintain communication within the multicast region using a shared key. Our approach supports a distributed key agreement protocol that identifies the compromised keys and supports membership changes with minimum system overhead. We evaluate the overhead of our approach by using the number of messages and encryptions to estimate power consumption. Using data from field tests of a military surveillance application, we show that our multicast approach needs fewer encryptions than pair-wise keying approaches. We also show that this scheme is capable of thwarting many common attacks.

21 pages, 21 figures.-- Journal special issue on Visual Sensor Networks. ; The recent interest in the surveillance of public, military, and commercial scenarios is increasing the need to develop and deploy intelligent and/or automated distributed visual surveillance systems. Many applications based on distributed resources use the so-called software agent technology. In this paper, a multi-agent framework is applied to coordinate videocamera-based surveillance. The ability to coordinate agents improves the global image and task distribution efficiency. In our proposal, a software agent is embedded in each camera and controls the capture parameters. Then coordination is based on the exchange of high-level messages among agents. Agents use an internal symbolic model to interpret the current situation from the messages from all other agents to improve global coordination. ; This work was funded by projects CICYT TSI2005-07344, CICYT TEC2005-07186, and CAM MADRINET S-0505/TIC/0255. ; Publicado

Localization in Wireless Sensor Network (WSN) plays a vital role in applications such as military, medical, healthcare, civil and environmental applications etc. Since all the sensor nodes in wireless sensor network are battery powered it is highly required to effectively utilize the sensor nodes in such a way that the lifetime of WSN is higher. Due to the limited availability of battery power in sensor nodes, energy consumption, computation speedup and memory consumption of localization algorithms are to be considered. In this paper a novel decision tree based approach (DTBL) for locating the nodes in WSN is discussed. The proposed approach is energy efficient in nature and high level of accuracy is obtained when compared with other localization techniques.

Localization in Wireless Sensor Network (WSN) plays a vital role in applications such as military, medical, healthcare, civil and environmental applications etc. Since all the sensor nodes in wireless sensor network are battery powered it is highly required to effectively utilize the sensor nodes in such a way that the lifetime of WSN is higher. Due to the limited availability of battery power in sensor nodes, energy consumption, computation speedup and memory consumption of localization algorithms are to be considered. In this paper a novel decision tree based approach (DTBL) for locating the nodes in WSN is discussed. The proposed approach is energy efficient in nature and high level of accuracy is obtained when compared with other localization techniques.