Wireless sensor networks have become increasingly popular in many applications such as environment monitoring and law enforcement. Data aggregation is a method used to reduce network traffic but cannot be used together with conventional encryption schemes because it is not secure and introduces extra overhead. Homomorphic encryption is an encryption scheme that allows data processing on encrypted data as opposed to plaintext. It has the benefit that each intermediate node does not have to decrypt each packet, but the resulting cyphertext is usually much larger than the original plaintext. This could negatively affect system performance because the energy consumption of each node is directly proportional to the amount of data it transmits. This study investigates the benefits and drawback of using homomorphic encryption in the aggregation process particularly in the context of scalable networks. It was found that conventional encryption outperforms the homomorphic encryption for smaller networks, but as the network size grows, homomorphic encryption starts outperforming conventional encryption. It was also found that the homomorphic encryption scheme does significantly reduce the performance of plaintext aggregation. This performance reduction will however be acceptable for most applications where security is a concern. / Draadlose sensornetwerke raak toenemend meer gewild vir heelwat verskillende toepassings, soos byvoorbeeld opgewingsmonitering en wetstoepassing. Data-aggregasie is n metode wat gebruik word om netwerkverkeer te verminder, maar kan nie gebruik word saam met konvensionele enkripsie-skemas nie, omdat dit nie veilig is nie en oorhoofse koste verhoog. Homomorfiese enkripsie is n enkripsie-skema wat dataverwerking toelaat op geënkripteerde in teenstelling met gewone-teks. Dit het die voordeel dat elke intermediêre nie nodig het om elke pakkie te dekripteer nie, maar die resulterende kodeteks is gewoonlik heelwat groter as die gewone-teks. Dit kan die stelselgedrag negatief beÏnvloed omdat die energieverbruik van elke node eweredig is aan die hoeveelheid data wat dit versend. Hierdie studie ondersoek die voor- en nadele van homomorfiese enkripsie in die aggregasieproses, veral in die konteks van skaleerbare netwerke. Daar is gevind dat konvensionele enkripsie beter vaar as homomorfies enkripsie in kleiner netwerke. Die omgekeerde is waar vir groter netwerke. Dit is ook gevind dat homomorfiese enkripsie gewone-teks-aggregasie negatief beÏnvloed, maar dit word as aanvaarbaar beskou vir toepassings waar sekuriteit belangrik is. / Dissertation (MEng)--University of Pretoria, 2015. / Electrical, Electronic and Computer Engineering / Meng / Unrestricted

Recently, wireless sensor networks (WSNs), consisted of battery-powered sensor nodes, are widely adopted by various civilian/military applications for implementing real-time monitoring or long-term surveillance tasks. One of the critical issues of WSNs is energy efficiency. Due to the limited battery capacity, the network lifetime and performance of WSNs are constrained. Also, once the sensor is deployed into a risky/remote environment, the replacement of its battery is hard. Therefore, how to improve the energy efficiency of the WSN is a critical issue and has gained tremendous attention from researchers around the world. To address this problem, by taking advantage of the emerging high-mobility devices (e.g., unmanned aerial vehicle (UAV)), we propose energy-efficient mobile device-assisted schemes in different-scale WSNs. Thanks to the rapid development of wireless techniques, two emerging approaches, i.e., data gathering technique and wireless charging technique, are beneficial to balance the workloads among all sensors or replenish energy to achieve the semi-permanent WSN. First, we design data gathering schemes using the mobile data collector. In order to meet the performance requirements of systems with different scales, our algorithms have two working modes: single- and multiple-data-collector scenarios. For the small-scale system, a single data collector is adopted to access and collect data from the deployed node, and we propose single mobile data collector-assisted (SDCA) data collection schemes for small-scale WSNs. For the large-scale system, multiple data collectors are utilized to gather sensed data from deployed nodes, and two-mode multiple mobile data collector-assisted (MDCA) data collection scheme is designed for balancing between the system energy consumption and the data forwarding latency. Second, the joint data collection and energy charging scheme is developed by adopting mobile chargers (MCs) as mobile devices that are responsible for energy charging and data collection simultaneously. For facing the different performance requirements of systems, a two-mode MC scheduling algorithm is presented. To evaluate our works, extensive simulation experiments are conducted on the OMNeT++ simulator. The results demonstrate that the proposed algorithms achieve better performance than the control group regarding system-wide energy efficiency, network lifetime and average end-to-end delay.

Wireless sensor networks, networks of nodes communicating wirelessly with sensing capabilities, are becoming more popular and are utilized by an increasing number of applications. Some wireless sensor networks are implemented because the usual network solutions of an always connected network could not be applied. Specifically this thesis is concerned with the case when the connection between the end-user and the network is not always available, i.e., there is only intermittent connectivity. This masters thesis gives an introduction and provides some background knowledge concerning wireless sensor networks, specifically focusing on disconnected operation. A set of building blocks will be presented to help programmers deal with programming disconnected operations. Examples to demonstrate our solution is implemented as shell commands using the Contiki operating system. Our solution was tested in the field and compared against a common, monolithic, programming approach. This practical example shows the potential significance of this thesis project in real world applications and allowed an evaluation of both the qualitative and quantitative aspects of our solution. The results of our evaluation prove that our solution offers an easier interface for the programmer to work with at the cost of possible less memory space. / Trådlösa sensornätverk, nätverk med noder som kommunicerar trådlöst och har sensorer, blir mer populära och används av i ett ökande antal applikationer. Några trådlösa sensornätverk används för att en vanlig nätverkslösning med ständigt uppkopplade noder inte går att genomföra. Det här examensjobbet är specifikt inriktat på fall när en uppkoppling mellan slutanvändaren och nätverket inte alltid är tillgängligt, t.ex. när det bara är tillfällig uppkoppling. Detta examensarbete ger en introduktion och bakgrund till trådlösa sensornätverk med fokus på programmering av frånkopplade operationer. Ett antal byggstenar har tagits fram för att hjälpa programmerare att programmera frånkopplade operationer. Exempel för att styrka vår lösning i vår rapport kommer att implementeras som shellkommandon i operativsystemet Contiki. Vår lösning kommer att testas i verkligheten och jämföras med ett vanligt, monolitisk, programmeringsangreppssätt. Detta praktiska exempel kommer visa den potentiella nyttan av detta examensarbete i verkliga applikationer och tillåta utvärdering av kvalitativa och kvantitativa aspekter på vår lösning. Resultaten från vår utvärdering bevisar att vår lösning erbjuder ett enkelt gränssnitt för programmeraren att arbeta med till en kostnad av möjligen mindre minnesplats.

The great interest in monitoring everything around us has increased the number of sensors that we utilize in our daily lives. Furthermore, the evolution of wireless technologies has facilitated their ubiquity. Moreover, is in locations such as homes and offices where exploitation of the data from these sensors has been more important. For example, we want to know if the temperature in our home is adequate, otherwise we want to turn on the heating (or cooling) system automatically and we want to be able to monitor the environment of the home or office remotely. The knowledge from these sensors and the ability to actuate devices, summon human assistance, and adjust contracts for electrical power, heating, cooling, etc. can facilitate a myriad of ways to improve the quality of our life and potentially even reduce resource consumption. This master‘s thesis project created a gateway that sniffs wireless sensor traffic in order to collect data from existing sensors and to provide this data as input to various services. These sensors work in the 868 MHz band. Although these wireless sensors are frequently installed in homes and offices, they are generally not connected to any network. We designed a gateway capable of identifying these wireless sensors and decoding the received messages, despite the fact that these messages may use a vendor‘s proprietary protocol. This gateway consists of a microcontroller, a radio transceiver (868-915 MHz), and an Ethernet controller. This gateway enables us to take advantage of all the data that can be captured. Thinking about these possibilities, simultaneously acquiring data from these various sensors could open a wide range of alternatives in different fields, such as home automation, industrial controlling… Not only can the received data be interesting by itself; but when different sensors are located in the same environment we can exploit this data using sensor fusion. For example, time differences in arrival and differences in signal strength as measured t multiple receivers could be used to locate objects. The final aim of this thesis project is to support diverse applications that could be developed using the new gateway. This gateway creates a bridge between the information that is already around us and our ability to realize many new potential services. A wide range of opportunities could be realized by exploiting the wireless sensors we already have close to us. / Det stora intresset för att övervaka allt omkring oss har ökat antalet sensorer som vi använder i vårt dagliga liv. Dessutom har utvecklingen av trådlösa tekniker underlättat de har stor utbredning. Dessutom är på platser som hem och kontor där utnyttjandet av data från dessa sensorer har varit viktigare. Till exempel vill vi veta om temperaturen i vårt hem är tillräcklig, annars vill vi slå på värmen (eller kyla) automatiskt och vi vill kunna övervaka miljön i hemmet eller på kontoret på distans. Data från dessa sensorer och förmåga att aktivera enheter kalla mänsklig assistans och justera avtal för el, värme, kyla, osv. kan underlätta en myriad av olika sätt att förbättra kvaliteten på våra liv och potentiellt även minska resursförbrukningen. Detta examensarbete syftar till att sniffa trådlösa sensorn trafik i syfte att samla in data från befintliga sensorer och att tillhandahålla sådan information som underlag till olika tjänster. Dessa sensorer arbetar i 868 MHz-bandet. Även om dessa ofta installeras i hem och kontor, är de i allmänhet inte ansluten till något nätverk. För att förverkliga vårt mål kommer vi att utforma en gateway som kan identifiera dessa trådlösa sensorer och avkoda den mottagna meddelanden, trots att dessa meddelanden kan använda en leverantör egenutvecklade protokoll. Denna brygga består av en mikrokontroller, en sändtagare (868 till 915 MHz), och en Ethernet-styrenhet. Gateway bör göra det möjligt för oss att dra nytta av alla de uppgifter som möjligen kan fångas. Funderar om dessa möjligheter, samtidigt insamling av data från dessa olika sensorer kan öppna ett brett spektrum av alternativ i olika områden, såsom hem automation, industriell kontrollerande ... Inte bara kan de mottagna uppgifterna vara intressant i sig självt, men när olika sensorer finns i samma miljö kan vi utnyttja detta data med hjälp av sensor fusion. Till exempel skulle tidsskillnader i ankomst och skillnader i signalstyrka uppmätt med flera mottagare användas för att lokalisera föremål. Det slutliga målet med denna avhandling är att stödja olika applikationer som skulle kunna utvecklas med hjälp av utformade gateway. Denna gateway kommer att skapa en initial brygga mellan all information omkring oss och vår förmåga att förverkliga många tjänsteleverantörer möjligheter. Ett brett utbud av möjligheter kan realiseras genom att utnyttja de trådlösa sensorerna vi redan har nära till oss.

We study the scheduling problem for data collection from sensor nodes to the sink node in wireless sensor networks, also referred to as the convergecast problem. The convergecast problem in general network topology has been proven to be NP-hard. In this paper, we propose our heuristic algorithm (finding the minimum scheduling time for convergecast (FMSTC)) for general network topology and evaluate the performance by simulation. The results of the simulation showed that the number of time slots to reach the sink node decreased with an increase in the power. We compared the performance of the proposed algorithm to the optimal time slots in a linear network topology. The proposed algorithm for convergecast in a general network topology has 2.27 times more time slots than that of a linear network topology. To the best of our knowledge, the proposed method is the first attempt to apply the optimal algorithm in a linear network topology to a general network topology.

The General Direction Routing Protocol (GDRP) is a Wireless Sensor Network (WSN) multi-path routing protocol which abstracts localization information (commonly GPS coordinates) into relative direction information in order to perform routing decisions. By generating relative direction information GDRP is able to operate with fewer precision requirements than other protocols. This abstraction also allows the integration of other emerging hardware-based localization techniques, for example, Beamforming Sensor Arrays. GDRP does not specifically address the next hop a packet should take, but instead specifies a direction it should travel. This direction abstraction allows for multiple paths to be taken through the network thus enhancing network robustness to node mobility and failures. This indirect addressing scheme also provides a solution to sensor node unique identification. GDRP is simulated in a custom simulator written in Java. This simulator supports interfaces for multiple protocols for layers 1, 2, 3, and 7 of the OSI model. For performance comparisons, GDRP is compared against multiple WSN routing protocols. GDRP operates with a significantly lower setup cost in terms of bytes transmitted and a lower setup latency for networks of varying sizes. It also demonstrates an exponentially lower routing cost when compared to another multi- path routing protocol due to a more efficient packet propagation in the network.

Les réseaux de capteurs sans fil sont une collection de nœuds non connectés qui sont installés pour la détection de certains phénomènes intéressants. Après avoir pris des mesures un capteur sans fil retransmet ces mesures à la station de base. La station de base collecte les données de tous les capteurs et les analyse. Pour économiser l’énergie il est souvent utilise de grouper les capteurs en clusters, chaque cluster ayant une tête de cluster qui communique avec la station de base. Au début, on commence par analyser la simulation des réseaux Zigbee où il y a quelques nœuds qui transmettent avec différentes puissances. Les résultats montrent que dans les réseaux de capteurs mobiles et hétérogènes et à cause du phénomène d’isolation des nœuds et du coût très élevé du routage et la maintenance, les performances sont moins bonnes que celles des réseaux homogènes. Le but principal de cette thèse est de faire une analyse empirique des réseaux de capteurs. A cause de leurs ressources limitées les réseaux de capteurs doivent faire face à plusieurs défis techniques. Beaucoup de protocoles fonctionnent très bien dans les simulateurs mais pas aussi bien en implémentation réelle. Par exemple, les capteurs déposés sur un objet élevé subissent moins d’atténuation que les autres capteurs placés sur le sol. Dans cette thèse, on montre qu’il y a un impact des liens asymétriques sur la topologie des réseaux de capteurs sans fil et que la qualité des liens (LQI) varie en permanence. On propose deux méthodes pour améliorer les performances des algorithmes basés sur la qualité des liens des réseaux de capteurs avec des liens asymétriques. Dans la première méthode, le réseau n’a pas d’autre choix que d’avoir des nœuds qui transmettent à des grandes distances et deviennent des clusters Head. Le nombre de clusters Head peut être donné par Matérn Hard-core process. Dans la seconde méthode, on propose HybridLQI qui améliore les algorithmes basés sur LQI sans ajouter des entêtes au réseau. Ensuite, on applique les approches de clustérisassions théoriques sur le réseau de capteurs réel. On applique Matérn Hard Core process et Max-Min heuristique de formation des clusters sur des nœuds «Tmote » dans des réseaux denses et des réseaux de faible densité. Les résultats empiriques ont montré la supériorité de Matérn sur Max-Min dans les besoins d’espace mémoire, la simplicité de l’implémentation et le nombre de messages de signalisation. Enfin, en utilisant les chaînes de Markov absorbantes et des mesures, on étudie les performances des techniques de la distribution de charge dans des réseaux de capteurs réels / Wireless sensor networks are the collection of wireless nodes that are deployed to monitor certain phenomena of interest. Once the node takes measurements it transmits to a base station over a wireless channel. The base station collects data from all the nodes and do further analysis. To save energy, it is often useful to build clusters, and the head of each cluster communicates with the base station. Initially, we do the simulation analysis of the Zigbee networks where few nodes are more powerful than the other nodes. The results show that in the mobile heterogeneous sensor networks, due to phenomenon orphaning and high cost of route discovery and maintenance, the performance of the network degrades with respect to the homogeneous network. The core of this thesis is to empirically analyze the sensor network. Due to its resource constraints, low power wireless sensor networks face several technical challenges. Many protocols work well on simulators but do not act as we expect in the actual deployments. For example, sensors physically placed at the top of the heap experience Free Space propagation model, while the sensors which are at the bottom of the heap have sharp fading channel characteristics. In this thesis, we show that impact of asymmetric links in the wireless sensor network topology and that link quality between sensors varies consistently. We propose two ways to improve the performance of Link Quality Indicator (LQI) based algorithms in the real asymmetric link sensor networks. In the first way, network has no choice but to have some sensors which can transmit over the larger distance and become cluster heads. The number of cluster heads can be given by Matérn Hard-Core process. In the second solution, we propose HybridLQI which improves the performance of LQI based algorithm without adding any overhead on the network. Later, we apply theoretical clustering approaches in sensor network to real world. We deploy Matérn Hard Core Process and Max-Min cluster Formation heuristic on real Tmote nodes in sparse as well as highly dense networks. Empirical results show clustering process based on Matérn Hard Core Process outperforms Max-Min Cluster formation in terms of the memory requirement, ease of implementation and number of messages needed for clustering. Finally, using Absorbing Markov chain and measurements we study the performance of load balancing techniques in real sensor networks.

Sensor networks including opportunistic networks of sensor-equipped smartphones as well as networks of embedded sensors can enable a wide range of applications including environmental monitoring, smart grids, intelligent transportation, and healthcare. In most real-world applications, to meet end-user requirements, the network operator needs to define and update the sensors' tasks dynamically, such as updating the parameters for sensor data collection or updating the sensors' code. Tasking sensor networks is necessary to reduce the effort in programming sensor networks. However, it is challenging due to dynamics and scale in terms of number of nodes, number of tasks, and sensing regions of the networks. In addition, tasking sensor networks must also be efficient in terms of bandwidth, latency, energy consumption, and memory usage. This dissertation identifies and addresses the problems of scalability and efficiency in tasking sensor networks. The first challenge in tasking sensor networks is to define a mechanism that represents multiple tasks and sensor groups efficiently taking into account the heterogeneity and mobility of sensors deployed over a large geographical region. Another challenge in tasking sensor networks in general, and embedded sensor networks in particular, is to design protocols that can not only efficiently disseminate tasks but also maintain a consistent view of the task to be performed among inherently unreliable and resource-limited sensors. We believe that a scalable and efficient tasking framework can greatly benefit the development and deployment of sensor network applications. Our thesis is that decoupling the task specification from task implementation using a spatial two-dimensional (2D) representation of a tasking region such as maps enables scalable, efficient, and resource-adaptive tasking over heterogeneous mobile sensor networks. In addition, reducing overhead in detecting inconsistencies across nodes enables scalable and efficient task dissemination and maintenance. We present the design, implementation, and evaluation of Zoom, a multiresolution tasking framework that efficiently encapsulates multiple tasks and sensor groups for sensor networks deployed in a large geographical region. The key ideas in Zoom are (i) decoupling task specification and task implementation to support heterogeneity, (ii) using maps for representing spatial sensor groups and tasks to scale with the number of sensor groups and sensing regions, and (iii) using image encoding techniques to reduce the map size and provide adaptation to sensor platforms with different resource capabilities. We present the design, implementation, and evaluation of our protocol, DHV, which efficiently disseminates task content and ensures that all nodes have up-to-date task content in sensor networks. It achieves this by minimizing both the redundant information in each message and the number of transmitted messages in the networks. DHV has been included in the official distribution of TinyOS, a popular operating system for embedded sensor networks. As sensor networks continue to develop, they will evolve from dedicated and single-purpose systems to open and multi-purpose large scale systems. Nodes in the network will be retasked frequently to support multiple applications and multiple users. We believe that this work is an important step in enabling seamless interaction between users and sensor networks and to make sensor networks more widely adopted.

Indiana University-Purdue University Indianapolis (IUPUI) / Wireless Sensor Networks (WSN) is being used in various applications including environmental monitoring, site inspection and military. WSN is a distributed network of sensor devices that can be used to monitor temperature, humidity, light and other important metrics. The software that runs on the sensor devices define how the device should operate. In real world WSN deployment, device software update is required to maintain optimal operation. In this thesis, we propose a novel idea of updating the software of the sensor nodes using a mobile device running on Android Operating System. Our implementation builds upon Mobile Deluge with few enhancement which is a method of re-programming WSN with laptop computer. We have evaluated our application performance by lab experiments and in real world deployments of WSN and found the application stable and battery efficient.

The aim of this thesis is to design and implement modules for wireless sensor network ZigBee. These modules could communicate together and share information about measured values. The network will be managed by coordinator of network, which will process data from sensor modules and will decide about next steps around the network.