Pervasive Service Discovery (SD) in Low-power and Lossy Networks (LLNs) is expected to play a major role in realising the Internet of Things (IoT) vision. Such a vision aims to expand the current Internet to interconnect billions of miniature smart objects that sense and act on our surroundings in a way that will revolutionise the future. The pervasiveness and heterogeneity of such low-power devices requires robust, automatic, interoperable and scalable deployment and operability solutions. At the same time, the limitations of such constrained devices impose strict challenges regarding complexity, energy consumption, time-efficiency and mobility. This research contributes new lightweight solutions to facilitate automatic deployment and operability of LLNs. It mainly tackles the aforementioned challenges through the proposition of novel component-based, automatic and efficient SD solutions that ensure extensibility and adaptability to various LLN environments. Building upon such architecture, a first fully-distributed, hybrid pushpull SD solution dubbed EADP (Extensible Adaptable Discovery Protocol) is proposed based on the well-known Trickle algorithm. Motivated by EADPs’ achievements, new methods to optimise Trickle are introduced. Such methods allow Trickle to encompass a wide range of algorithms and extend its usage to new application domains. One of the new applications is concretized in the TrickleSD protocol aiming to build automatic, reliable, scalable, and time-efficient SD. To optimise the energy efficiency of TrickleSD, two mechanisms improving broadcast communication in LLNs are proposed. Finally, interoperable standards-based SD in the IoT is demonstrated, and methods combining zero-configuration operations with infrastructure-based solutions are proposed. Experimental evaluations of the above contributions reveal that it is possible to achieve automatic, cost-effective, time-efficient, lightweight, and interoperable SD in LLNs. These achievements open novel perspectives for zero-configuration capabilities in the IoT and promise to bring the ‘things’ to all people everywhere.

Pervasive Service Discovery (SD) in Low-power and Lossy Networks (LLNs) is expected to play a major role in realising the Internet of Things (IoT) vision. Such a vision aims to expand the current Internet to interconnect billions of miniature smart objects that sense and act on our surroundings in a way that will revolutionise the future. The pervasiveness and heterogeneity of such low-power devices requires robust, automatic, interoperable and scalable deployment and operability solutions. At the same time, the limitations of such constrained devices impose strict challenges regarding complexity, energy consumption, time-efficiency and mobility. This research contributes new lightweight solutions to facilitate automatic deployment and operability of LLNs. It mainly tackles the aforementioned challenges through the proposition of novel component-based, automatic and efficient SD solutions that ensure extensibility and adaptability to various LLN environments. Building upon such architecture, a first fully-distributed, hybrid pushpull SD solution dubbed EADP (Extensible Adaptable Discovery Protocol) is proposed based on the well-known Trickle algorithm. Motivated by EADPs’ achievements, new methods to optimise Trickle are introduced. Such methods allow Trickle to encompass a wide range of algorithms and extend its usage to new application domains. One of the new applications is concretized in the TrickleSD protocol aiming to build automatic, reliable, scalable, and time-efficient SD. To optimise the energy efficiency of TrickleSD, two mechanisms improving broadcast communication in LLNs are proposed. Finally, interoperable standards-based SD in the IoT is demonstrated, and methods combining zero-configuration operations with infrastructure-based solutions are proposed. Experimental evaluations of the above contributions reveal that it is possible to achieve automatic, cost-effective, time-efficient, lightweight, and interoperable SD in LLNs. These achievements open novel perspectives for zero-configuration capabilities in the IoT and promise to bring the ‘things’ to all people everywhere.

The main goal in this thesis is to select and test Forward Error Correction (FEC) schemes suitable for network video transmission over RTP/UDP. There is a general concern in communication networks which is to achieve a tradeoff between reliable transmission and the delay that it takes. Our purpose is to look for techniques that improve the reliability while the realtime delay constraints are fulfilled. In order to achieve it, the FEC techniques focus on recovering the packet losses that come up along any transmission. The FEC schemes that we have selected are Parity Check algorithm, ReedSolomon (RS) codes and a Convolutional code. Simulations are performed to test the different schemes. The results obtained show that the RS codes are the more powerful schemes in terms of recovery capabilities. However they can not be deployed for every configuration since they go beyond the delay threshold. On the other hand, despite of the Parity Check codes being the less efficient in terms of error recovery, they show a reasonable low delay. Therefore, depending on the packet loss probability that we are working with, we may chose one or other of the different schemes. To summarize, this thesis includes a theoretical background, a thorough analysis of the FEC schemes chosen, simulation results, conclusions and proposed future work.

<p>The main goal in this thesis is to select and test Forward Error Correction (FEC) schemes suitable for network video transmission over RTP/UDP. There is a general concern in communication networks which is to achieve a tradeoff between reliable transmission and the delay that it takes. Our purpose is to look for techniques that improve the reliability while the realtime delay constraints are fulfilled. In order to achieve it, the FEC techniques focus on recovering the packet losses that come up along any transmission. The FEC schemes that we have selected are Parity Check algorithm, ReedSolomon (RS) codes and a Convolutional code. Simulations are performed to test the different schemes.</p><p>The results obtained show that the RS codes are the more powerful schemes in terms of recovery capabilities. However they can not be deployed for every configuration since they go beyond the delay threshold. On the other hand, despite of the Parity Check codes being the less efficient in terms of error recovery, they show a reasonable low delay. Therefore, depending on the packet loss probability that we are working with, we may chose one or other of the different schemes. To summarize, this thesis includes a theoretical background, a thorough analysis of the FEC schemes chosen, simulation results, conclusions and proposed future work.</p>

Low power and Lossy Networks (LLNs) such as wireless sensor networks are currently used in many important applications fields such as remote environment monitoring and target tracking. This deployment has been enabled by the availability, especially in recent years, of embedded micro-controller devices that are smaller and cheaper. These devices are equipped with wireless interfaces, with which they can communicate with each other to form a network. In this thesis we focus on studying the energy consumption of reliable transport protocols over LLNs. Recently, much research has been carried out to improve the reliability and the congestion control on low power networks. Some of these works have considered TCP inappropriate for this kind of networks. Indeed, the idea of deploying TCP was rejected due to its header overhead, its end-to-end retransmission mechanism, its large rate of acknowledgment, and the impact of the lower layers fragmentation on the energy consumption. Nonetheless, the use of standard TCP/IP protocols offers the advantage of a seamless connectivity between the wireless network and the Internet. TCP allows easily the use of standard applications (HTTP, SSH) for some tasks like reprogramming of nodes or firmware updates, without the need of deploying complex proxies in border routers. In the first part of this work, we study the energy consumption of TCP and the ways that reduce its energy consumption. We study one of the proposed TCP algorithms to reduce the end-to-end retransmissions cost and we propose some improvements that allow it to reduce the energy consumption. Then, we study the compression of the TCP header over low-power and lossy networks and we consider IPv6 over Low power Wireless Personnel Area Networks (6LoWPAN) as an example. We propose a new TCP header compression algorithm that reduces the TCP header size to about six bytes. In the second part, we propose a mathematical model that allows to estimate the energy consumption of wireless nodes. Using the model, we study the tradeoff between sending long and short TCP segments and their impact on the energy consumption. Finally, we study the impact of a new fragment recovery mechanism on the energy performance of TCP.

The size of the IoT network is expanding due to advancements in the IoT field, leading to increased interest in the multi-sink mechanism. The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is a representative IoT protocol that focuses on the Low-Power and Lossy Networks. However, research on comparing multi-sink strategies within the RPL network is limited. Therefore, this project aims to compare three common strategies: multiple-DODAG in one instance, virtual root, and multiple-instance. Using these strategies, we design and implement RPL networks and conduct simulations in various scenarios. Five different topologies are utilized in the experiments, considering different packet loss rates. Performance evaluation of each strategy is conducted using the Cooja simulator and Contiki-NG system, with a focus on the number of RPL control packets, Packet Delivery Ratio (PDR), and energy consumption. The results indicate that both the virtual root and multiple-DODAG strategies perform well with low packet loss, while the virtual root strategy outperforms the multiple-DODAG strategy with high packet loss. Additionally, the virtual root strategy incurs slightly higher energy costs than the multiple-DODAG strategy. Furthermore, the multiple-instance strategy demonstrates poor performance in most scenarios, except for the packet delivery ratio under high packet loss conditions. Besides the analysis, potential areas for future research on the RPL’s multi-sink mechanism are finally identified. / Storleken på IoT-nätverket expanderar på grund av framsteg inom IoT-området, vilket leder till ökat intresse för multi-sink-mekanismen. IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) är ett representativt IoT-protokoll som fokuserar på Nät med låg effekt och förluster. Forskningen om jämförelse av multi-sink-strategier inom RPL-nätverket är dock begränsad. Därför syftar detta projekt till att jämföra tre vanliga strategier: multiple - DODAG i en instans, virtuell rot och multi-instans. Med hjälp av dessa strategier designar och implementerar vi RPL-nätverk och genomför simuleringar i olika scenarier. Fem olika topologier används i experimenten, med olika packet loss rate. Prestationsutvärdering av varje strategi utförs med hjälp av Cooja-simulatorn och Contiki-NG-systemet, med fokus på antalet RPL control packets, Packet Delivery Ratio (PDR) och energiförbrukning. Resultaten indikerar att både virtuell rot och multiple-DODAG strategier fungerar bra vid låg datapaketförlust, medan den virtuella rotstrategin överträffar multiple-DODAG strategin vid hög datapaketförlust. Dessutom medför den virtuella rotstrategin något högre energikostnader än flera DODAG-strategin. Dessutom visar multi-instans-strategin dålig prestanda i de flesta scenarier, förutom när det gäller datapaketleveransförhållandet under höga datapaketförlustförhållanden. Utöver analysen identifieras slutligen potentiella områden för framtida forskning om RPL-protokollets multi-sink-mekanism.

La technologie des réseaux de capteurs sans fil (RCSF) est l’un des éléments constitutifs de l’Internet des objets (IoT). En raison de leurs caractéristiques de déploiement facile et de leur flexibilité, ils sont utilisés dans de nombreux domaines d’application. Les réseaux à faible consommation et à perte (LLN) sont un type spécial de WSN dans lequel les noeuds sont largement limités en ressources. Convergecast est l’un des modes de communication de base, dans lequel tout le trafic du réseau est destiné à une destination prédéfinie appelée collecteur. Tout en prenant en compte les domaines d’applications IoT, convergecast n’est pas le seul mode de communication sur le réseau. Le récepteur doit envoyer des commandes à certains capteurs pour effectuer des actions. Dans cette application, anycast est un autre mode de communication de base. Dans anycast, le trafic provenant du récepteur est destiné à tout membre d’un groupe de récepteurs potentiels du réseau.Les LLN sont formés de noeuds de capteurs statiques et changent rarement de position. En raison des contraintes de ressources strictes imposées au calcul, à l’énergie et à la mémoire des LLN, la plupart des protocoles de routage ne prennent en charge que les réseaux statiques. Cependant, la mobilité est devenue une exigence importante pour de nombreuses applications émergentes. Dans ces applications, certains noeuds sont libres de se déplacer et de s’organiser dans un réseau connecté. La topologie changerait continuellement en raison du mouvement des noeuds et de l’instabilité des liaisons radio. Il s’agit d’une tâche difficile pour la plupart des protocoles de routage des réseaux LLN afin de s’adapter rapidement au mouvement et de reconstruire la topologie en temps voulu. Le but de cette thèse est de proposer un support de mobilité efficace pour les protocoles de routage dans les réseaux LLN. Nous nous concentrons sur convergecast et anycast, qui sont les modes de communication les plus utilisés dans les réseaux LLN, dans les scénarios de réseau mobile. Nous proposons un mécanisme d’amélioration, nommé RL (RSSI and Level),pour prendre en charge les protocoles de routage dans les réseaux LLN convergecast en mobilité. Ce mécanisme aide le protocole de routage à prendre des décisions plus rapides pour la détection de la mobilité et la mise à jour des voisins du saut suivant,mais souffre d’une surcharge importante. Nous proposons une gestion dynamique des messages de contrôle pour améliorer les performances de RL et l’implémentons en plus du protocole de routage pour réseau à faible consommation (RPL) et nous l’avons nommé RRD (RSSI, Rank and Dynamic). Après une prise en compte de l’hystérésis de la zone de couverture de la plage de transmission des noeuds, nousavons optimisé RRD. Cette version améliorée s’appelle RRD +. Sur la base de RRD+, nous avons proposé MRRD + (Multiple, RSSI, Rank et Dynamic) pour prendre en charge plusieurs puits dans les réseaux LLN convergecast en mobilité. ADUP (Adaptive Downward / Upward Protocol) est une solution de routage prenant en charge simultanément convergecast et anycast dans les réseaux LLN. Nous avons évalué les performances de nos contributions à la fois en simulation avec le simulateur Cooja et en expérience (uniquement pour ADUP) sur des motosTelosB. Les résultats obtenus en simulation et en expérience confirment l’efficacité de nos protocoles de routage. / Wireless Sensor Networks (WSNs) technology is one of the building blocks ofthe Internet of Things (IoT). Due to their features of easy deployment and flexibility,they are used in many application domains. Low-Power and Lossy Networks(LLNs) are a special type of WSNs in which nodes are largely resources constrained.For LLNs, convergecast is one of the basic traffic modes, where all traffic in the networkis destined to a predefined destination called the sink. While considering theIoT application domains, convergecast is not the only traffic mode in the network.The sink needs to send commands to certain sensors to perform actions. In this application,anycast is another basic traffic mode. In anycast, the traffic from the sinkis destined to any member of a group of potential receivers in the network.Traditionally LLNs are formed by static sensor nodes and rarely change positions.Due to the strict resource constraints in computation, energy and memory ofLLNs, most routing protocols only support static network. However, mobility hasbecome an important requirement for many emerging applications. In these applications,certain nodes are free to move and organize themselves into a connectednetwork. The topology would continuously change due to the movement of nodesand radio links instability. This is a hard task for most routing protocols of LLNs toadapt rapidly to the movement and to reconstruct topology in a timely manner.The goal of this thesis is to propose an efficient mobility support for routingprotocols in LLNs. We focus on convergecast and anycast, which are the most usedtraffic modes in LLNs, in mobile network scenarios.We propose an enhancement mechanism, named RL (RSSI and Level), to supportrouting protocols in convergecast LLNs in mobility. This mechanism helps routingprotocol make faster decisions for detecting mobility and updating next-hop neighborsbut suffers from high overhead. We propose a dynamic control message managementto enhance the overhead performance of RL and implement it on top ofRouting Protocol for Low-power and Lossy network (RPL) and we named it RRD(RSSI, Rank and Dynamic). After taking into account hysteresis of the coveragezone of the transmission range of nodes, we optimized RRD. This enhanced versionis called RRD+. Based on RRD+, we proposed MRRD+ (Multiple, RSSI, Rankand Dynamic) to support multiple sinks in convergecast LLNs in mobility. ADUP(Adaptive Downward/Upward Protocol) is a routing solution that supports bothconvergecast and anycast in LLNs concurrently.We evaluated the performance of our contributions in both simulation usingCooja simulator and experiment (only for ADUP) on TelosB motes. The resultsobtained in both simulation and experiment confirm the efficiency of our routingprotocols.

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The use of Internet of Things systems has increased to meet the need for smart systems in various fields, such as smart homes, intelligent industries, medical systems, agriculture, and the military. IoT networks are expanding daily to include hundreds and thousands of IoT devices, which transmit information through other linked devices to reach the network sink or gateway. The information follows different routes to the network sink. Finding an ideal routing solution is a big challenge due to several factors, such as power, computation, storage, and memory limitation for IoT devices. In 2011, A new standardized routing protocol for low-power and lossy networks was released by the Internet Engineering task force (IETF). The IETF adopted a distance vector routing algorithm for the RPL protocol. RPL protocol utilizes the objective functions (OFs) to select the path depending on diffident metrics.These OFs with different metrics must be evaluated and tested to develop the best routing solution.This project aims to test the performance of standardized RPL objective functions in a simulation environment. Afterwards, a new objective function with a new metric will be implemented and tested in the same environmental conditions. The performance results of the standard objective functions and the newly implemented objective function will be analyzed and compared to evaluate whether the standard objective functions or the new objective function is better as a routing solution for the IoT devices network.