Yes / With the advent of Wireless Sensor Networks (WSN) and its immense popularity in a wide range of applications, security has been a major concern for these resource-constraint systems. Alongside security, WSNs are currently being integrated with existing technologies such as the Internet, satellite, Wi-Max, Wi-Fi, etc. in order to transmit data over long distances and hand-over network load to more powerful devices. With the focus currently being on the integration of WSNs with existing technologies, security becomes a major concern. The main security requirement for WSN-integrated networks is providing end-to-end security along with the implementation of in-processing techniques of data aggregation. This can be achieved with the implementation of Homomorphic encryption schemes which prove to be computationally inexpensive since they have considerable overheads. This paper addresses the ID-issue of the commonly used Castelluccia Mykletun Tsudik (CMT) [12] homomorphic scheme by proposing an ID slotting mechanism which carries information pertaining to the security keys responsible for the encryption of individual sensor data. The proposed scheme proves to be 93.5% lighter in terms of induced overheads and 11.86% more energy efficient along with providing efficient WSN scalability compared to the existing scheme. The paper provides analytical results comparing the proposed scheme with the existing scheme thus justifying that the modification to the existing scheme can prove highly efficient for resource-constrained WSNs.

This thesis focuses on the least-squares formulation of the non-collaborative and collabo- rative position location problems. For the non-collaborative problem, characterization encompassing the number of minima and the causes thereof is provided. Based on these efforts, we propose an improvement to the existing modified parallel projection method (MPPM), the reflected parallel projection method (RPPM). We show that the global minimum to the non-collaborative objective function can nearly always be found using the non-optimal reflected parallel projection method (RPPM). For the collaborative position location problem, we provide a characterization that shows a heavy tail of root-mean-square (RMS) error due to a small percentage of simulated node/anchor layouts when solved by the iterative parallel projection method (IPPM). We provide an identification technique that successfully identifies most layouts that show large RMS error followed by a proposed solution to improve the accuracy in those problematic layouts. Finally, we report the findings of a measurement campaign that validates our Gaussian model for line-of-sight (LOS) noise and shows that, for these particular measurements, non-line-of-sight (NLOS) noise is difficult to accurately model and can be very large. This research was supported by a Bradley Fellowship from Virginia Tech's Bradley Department of Electrical and Computer Engineering, made possible by an endowment from the Harry Lynde Bradley Foundation. / Master of Science

We describe CoSMo, a Cognitively Inspired Service and Model Architecture for situational awareness and monitoring of vehicular traffic in urban transportation systems using a network of wireless sensors. The system architecture combines (i) a cognitively inspired internal representation for analyzing and answering queries concerning the observed system and (ii) a service oriented architecture that facilitates interaction among individual modules, of the internal representation, the observed system and the user. The cognitively inspired model architecture allows effective deductive as well as inductive reasoning by combining simulation based dynamic models for planning with traditional relational databases for knowledge and data representation. On the other hand the service oriented design of interaction allows one to build flexible, extensible and scalable systems that can be deployed in practical settings. To illustrate our concepts and the novel features of our architecture, we have recently completed a prototype implementation of CoSMo. The prototype illustrates advantages of our approach over other traditional approaches for designing scalable software for situational awareness in large complex systems. The basic architecture and its prototype implementation are generic and can be applied for monitoring other complex systems. This thesis describes the design of cognitively-inspired model architecture and its corresponding prototype. Two important contributions include the following: • The cognitively-inspired architecture: In contrast to earlier work in model driven architecture, CoSMo contains a number of cognitively inspired features, including perception, memory and learning. Apart from illustrating interesting trade-offs between computational cost (e.g. access time, memory), and correctness available to a user, it also allows users specified deductive and inductive queries. • Distributed Data Integration and Fusion: In keeping with the cognitively-inspired model-driven approach, the system allows for an efficient data fusion from heterogeneous sensors, simulation based dynamic models and databases that are continually updated with real world and simulated data. It is capable of supporting a rich class of queries. / Master of Science

Yes / Sensing coverage and network connectivity are two of the most fundamental issues to ensure that there are effective environmental sensing and robust data communication in a WSN application. Random positioning of nodes in a WSN may result in random connectivity, which can cause a large variety of key parameters within the WSN. For example, data latency and battery lifetime can lead to the isolation of nodes, which causes a disconnection between nodes within the network. These problems can be avoided by using mobile data sinks, which travel between nodes that have connection problems. This research aims to design, test and optimise a data collection system that addresses the isolated node problem, as well as to improve the connectivity between sensor nodes and base station, and to reduce the energy consumption simultaneously. In addition, this system will help to solve several problems such as the imbalance of delay and hotspot problems. The effort in this paper is focussed on the feasibility of using the proposed methodology in different applications. More ongoing experimental work will aim to provide a detailed study for advanced applications e.g. transport systems for civil purposes. / European Union’s Horizon 2020 research and innovation programme under grant agreement H2020-MSCA-ITN-2016 SECRET-722424.

Wireless sensor networks are an indispensable tool in this highly connected world. WSNs have been the focus of research efforts in areas of communication, electronics and control for many years. Advancements in the fields of MEMS, RF and digital circuit technology has led to the development of low cost and extremely power efficient smart sensors. This has led to the need of a fast, reliable and inexpensive method of consensus building for these sensor networks. Basic concepts of graph theory and consensus building are explained in this thesis. This thesis reviews the models and strategies for consensus building present in the literature. The shortcomings of these models are explained through examples and a leader-follower model based consensus building strategy is presented. Algorithm to convert any graph into a bipartite graph by edge removal and a strategy to select effective leaders based on a weighted combination of node centrality, ratio of leaders to the total number of nodes and presence of leaf nodes in the group is presented in this thesis. Proposed leader-follower model is compared against classic models for consensus building are compared and proven to be better. Mobility is studied using deterministic and random mobility models to show the improvement in convergence rate of the network. It is shown that mobility can turn any disconnected network into a connected network, which is able to reach consensus.

The ways that people use libraries have changed drastically over the past few decades. Proliferation of computers and the internet have led to the purpose of libraries expanding from being only places where information is stored, to spaces where people teach, learn, create, and collaborate. Due to this, the ways that people occupy the space in a library have also changed. To keep up with these changes and improve patron experience, institutions collect data to determine how their spaces are being used. This thesis involves the development a system that collects, stores, and analyzes data relevant to occupancy to learn how a space is being utilized. Data is collected from a temperature and humidity sensor, passive Infrared sensor, and an Infrared thermal sensor array to observe people as they occupy and move through a space. Algorithms were developed to analyze the collected sensor data to determine how many people are occupying a space or the directions that people are moving through a space. The algorithms demonstrate the ability to track multiple people moving through a space as well as count the number of people in a space with an RMSE of roughly 0.39 people.

The concept of Industrial Internet of Things (IIoT) is the tangible building block for the realisation of the fourth industrial revolution. It should improve productivity, efficiency and reliability of industrial automation systems, leading to revenue growth in industrial scenarios. IIoT needs to encompass various disciplines and technologies to constitute an operable and harmonious system. One essential requirement for a system to exhibit such behaviour is reliable exchange of information. In industrial automation, the information life-cycle starts at the field level, with data collected by sensors, and ends at the enterprise level, where that data is processed into knowledge for business decision making. In IIoT, the process of knowledge discovery is expected to start in the lower layers of the automation hierarchy, and to cover the data exchange between the connected smart objects to perform collaborative tasks. This thesis aims to assist the comprehension of the processes for information exchange in IIoT-enabled industrial automation- in particular, how reliable exchange of information can be performed by communication systems at field level given an underlying wireless sensor technology, and how data analytics can complement the processes of various levels of the automation hierarchy. Furthermore, this work explores how an IIoT monitoring system can be designed and developed. The communication reliability is addressed by proposing a redundancy-based medium access control protocol for mission-critical applications, and analysing its performance regarding real-time and deterministic delivery. The importance of the data and the benefits of data analytics for various levels of the automation hierarchy are examined by suggesting data-driven methods for visualisation, centralised system modelling and distributed data streams modelling. The design and development of an IIoT monitoring system are addressed by proposing a novel three-layer framework that incorporates wireless sensor, fog, and cloud technologies. Moreover, an IIoT testbed system is developed to realise the proposed framework. The outcome of this study suggests that redundancy-based mechanisms improve communication reliability. However, they can also introduce drawbacks, such as poor link utilisation and limited scalability, in the context of IIoT. Data-driven methods result in enhanced readability of visualisation, and reduced necessity of the ground truth in system modelling. The results illustrate that distributed modelling can lower the negative effect of the redundancy-based mechanisms on link utilisation, by reducing the up-link traffic. Mathematical analysis reveals that introducing fog layer in the IIoT framework removes the single point of failure and enhances scalability, while meeting the latency requirements of the monitoring application. Finally, the experiment results show that the IIoT testbed works adequately and can serve for the future development and deployment of IIoT applications. / SMART (Smarta system och tjänster för ett effektivt och innovativt samhälle)

Made available in DSpace on 2016-06-02T19:06:10Z (GMT). No. of bitstreams: 1 5631.pdf: 1787133 bytes, checksum: c363525148fa6a5fe71608e7a8ffcf4c (MD5) Previous issue date: 2012-09-28 / Universidade Federal de Sao Carlos / The Wireless Sensor Networks (WSNs) and Mobile Wireless Sensor Networks (MWSNs) are being increasingly used by different applications, such as monitoring of animals, monitoring of vital signs, environmental monitoring, surveillance and protection of critical infrastructure, leaking gas, among many others. Some of these applications are already making use of mobile sensor nodes, such as underwater monitoring, precision agriculture, among many others. Due to restricted resources of sensor nodes, especially in relation to energy consumption, the development for solutions based on WSN and MWSN becomes limited. The use of mobile sensor nodes, which typically has more computational resources, power and communication, can help to reduce the energy consumption of fixed nodes, increasing the lifetime of the network. Networks that use mobile sensor nodes (fixed and mobile) with different types of hardware are called Wireless Sensor Networks Heterogeneous Mobile. This paper presents the RAHMoN (Routing Algorithm for Heterogeneous Mobile Networks), which makes use of data aggregation technique to reduce the traffic transmissions on the network, hierarchy of nodes (clustering), and use of sensor nodes (fixed and mobile) that collaborate to deliver data to a sink node at high speed. In RAHMoN, the network is configured using the techniques of inundation (flooding) and inundation reverse (reverse flooding) to collect the fixed position of sensor nodes and form an adjacency matrix. This matrix helps to build routes for data delivery to the sink and is stored in the mobile sensor nodes. Results show that our solution can guarantee a high packages delivery rate, low latency and reduce the delay of packet delivery. The solution was compared with the WHISPER, present in the literature and also focused on the delivery of data to sink node at high speed. / As Redes de sensores sem Fio (RSSFs) e Redes de Sensores Sem Fio Móveis (RSSFMs) estão sendo cada vez mais utilizadas por diferentes aplicações, tais como: monitoramento de animais, monitoramento de sinais vitais, monitoramento ambiental, vigilância e proteção de infraestruturas críticas, vazamento de gás, dentre inúmeras outras. Algumas dessas aplicações já fazem uso de nós sensores móveis. Devido aos recursos restritos dos nós sensores, principalmente em relação ao consumo energético, o desenvolvimento de soluções baseadas em RSSF e RSSFM torna-se limitado. O uso de nós sensores móveis, que tipicamente têm mais recursos computacionais, de energia e de comunicação, pode ajudar a reduzir o consumo de energia dos nós fixos, aumentando o tempo de vida da rede. Redes que utilizam nós sensores (fixos e móveis) com diferentes tipos de hardware são denominadas Redes de Sensores Sem Fio Móvel Heterogênea. Neste trabalho é apresentado o RAHMoN (Routing Algorithm for Heterogeneous Mobile Networks), que faz uso da técnica de agregação de dados para reduzir o tráfego de transmissões na rede, da hierarquização de nós (clustering), da utilização de nós sensores (fixos e móveis) e de um sink em alta velocidade. No RAHMoN, a rede é configurada utilizando flooding e flooding reverse para coletar a posição dos nós sensores fixos e formar uma matriz de adjacência. Essa matriz auxilia na construção de rotas durante a entrega dos dados para o sink e será armazenada nos nós sensores móveis. Resultados de avaliação mostram que a nossa solução consegue garantir uma alta taxa de entrega de pacotes, diminuir a latência e reduzir o atraso de entrega dos pacotes. A solução foi comparada com o WHISPER, presente na literatura e também voltado à entrega de dados para o nó sink em alta velocidade.

Our work focuses on wireless networks in general, but deals specifically with security in wireless sensor networks and energy consumption in IEEE 802.11 infrastructure WLANs. In the first part of our work, we focus on secure communication among sensor nodes in a wireless sensor network. These networks consists of large numbers of devices having limited energy and memory. Public key cryptography is too demanding for these resource-constrained devices because it requires high computation. So, we focus on symmetric key cryptography to achieve secure communication among nodes. For this cryptographic technique to work, two nodes have to agree upon a common key. To achieve this, many key distribution schemes have been proposed in the literature. Recently, several researchers have proposed schemes in which they have used group-based deployment models and assumed predeployment knowledge of the expected locations of nodes. They have shown that these schemes achieve better performance than the earlier schemes, in terms of connectivity, resilience against node capture and storage requirements. But in many situations expected locations of nodes are not available. We propose a solution which does not use the group-based deployment model and predeployment knowledge of the locations of nodes, and yet performs better than schemes which make the aforementioned assumptions. In our scheme, groups are formed after the deployment of sensor nodes on the basis of their physical locations. Nodes in different groups sample keys from disjoint key pools, so that compromise of a node affects secure links of its group only. Because of this reason, our scheme performs better than earlier schemes as well as the schemes using predeployment knowledge, in terms of connectivity, storage requirement, and security. Moreover, the post-deployment key generation process completes sooner than in schemes like LEAP+. In the second part of our work, we develop analytical models for estimating the energy spent by stations (STAs) in infrastructure WLANs when performing TCP-controlled file downloads. We focus on the energy spent in radio communication when the STAs are in the Continuously Active Mode (CAM), or in the static Power Save Mode (PSM). Our approach is to develop accurate models for obtaining the fractions of times the STA radios spend in idling, receiving and transmitting. We discuss two traffic models for each mode of operation: (i) each STA performs one large file download, and (ii) the STAs perform short file transfers with think times (short duration of inactivity)between two transfers. We evaluate the rate of STA energy expenditure with long file downloads, and show that static PSM is worse than using just CAM. For short file downloads, we compute the number of file downloads that can be completed with a given battery capacity, and show that PSM performs better than CAM for this case. We provide a validation of our analytical models using the NS-2 simulator. Although the PSM performs better than the CAM when the STAs download short files over TCP with think times, its performance degrades as the number of STAs associated to the access point (AP) increases. To address this problem, we propose an algorithm, which we call opportunistic PSM (OPSM). We show through simulations that OPSM performs better than PSM. The performance gain achieved by OPSM increases as the file size requested by the STAs or the number of STAs associated with the AP increases. We implemented OPSM in NS-2.33, and to compare the performance of OPSM and PSM, we evaluate the number of file downloads that can be completed with a given battery capacity and the average time taken to download a file.

Internet of Things (IoT) är en kraftfull plattform för att koppla den fysiska världen till den digitala. IoT och modern sensorteknik möjliggör många nya applikationer inom till exempel industriell övervakning, hälsovård,miljöövervakning, smarta städer, smarta transport och smartlivsstil. I många av dessa applikationer är sensornoder utplacerade i utomhusmiljöer, där de bör fungera under långa tidsperioder. IoT-noder lider av kapacitetbergränsade batterier vilket innebär att deras funktion beror på batteriets livslängd. En lösning kan vara att implementera ett energikördsystem till IoT-noder utomhus. Solenergi är den mest lättillgängliga och användbara energikällan utomhus.Denna energi skördas med hjälp av en solcell (PV-cell). Energin som genereras av solcellspaneler varierar beroende på solstrålningsintensitet och andra faktorer. Syftet med denna undersökning har varit att utveckla en solcellsförsörjningsenhet för IoT-noder utomhus. Detta görs genom att hämta energi från omgivningen (solenergi) och använda den i samband med en Power ManagementIntegrated Circuit (PMIC) och en energilagringsenhet kan livslängden för IoT-noder förlängas samtidigt som underhållskostnader minskas.I undersökningen användes en uppskattningsmetod för att uppskatta solcellens totala energiproduktion, vilket hjälper för att konfigurera en solcellspanel som kan leverera lämplig energi till energiskördsystemet och minska energiförlusten i systemet. En lämplig energi krävs för att PMIC:n ska fungera väl samt systemet ska driva IoT-noder. Denna undersökning har visat att solenergiskördsystemet som består av en självgjord mindre panel, en BQ25570 och en energilagringsenhet (antingen en superkondensator eller ett batteri) kan översvämningsmätaren drivas under sommaren för det första fallet och under hela året för det andra fallet. Om två i parallell KXOB25-01X8F-TR används i systemet i stället för den mindre panelen kan luftkvalitetmätaren drivas under sommaren medan om tre iparallell KXOB25-01X8F-TR används i stället kan noden drivas under hela året. Energiskördsystemet ger mer än 80% effektivitet. / The Internet of Things (IoT) is a powerful platform for connecting the physical world to the digital. IoT and modern sensor technology enable many new applications in domains such as industrial monitoring, health care, environmentalmonitoring, smart cities and so on. In many of these applications, sensor nodes are deployed in outdoorenvironments, where they should operate for long periods oftime. But IoT nodes suffer from capacity-limited batteries,which means that their function depends on the battery life. One solution may be to implement an energy harvestingsystem for IoT nodes outdoors. Solar energy is the most readily available and useful source of energy outdoors. This energy is harvested using a solar cell (PV cell). The energy generated by solar cell panels varies depending on the solar radiation intensity and other factors. The purpose of this study has been to develop a solar cell supply unit for outdoor IoT nodes. This is done by extracting energy from the environment (solar energy) and using it in conjunction with a Power Management Integrating Circuit (PMIC) and energy storage device, the lifespan of IoT nodes can be extended while reducing maintenance costs. The study used an estimation method to estimate solar cell total energy production, which helps to configure a solar cellpanel that can supply suitable energy to the energyharvesting system and reduce the energy loss in the system. A suitable energy is required for the PMIC to work well and the system to power IoT nodes.This study has shown that the solar energy harvesting system consisting of a self-made smaller panel, a BQ25570 and an energy storage unit (either a supercapacitor or a battery), the flood meter can be operated during the summer for the first case and throughout the year for the second case. If two inparallel KXOB25-01X8F-TR are used in the system instead of the smaller panel, the air quality meter can be operated in the lower summer, while if three in parallel KXOB25-01X8F-TR areused instead, the node can be operated throughout the year. The energy harvesting system provides more than 80% efficiency.