Distributed localisation algorithm for wireless ad hoc networks of moving nodes

Existing ad hoc network localisation solutions rely either on external location references or network-wide exchange of information and centralised processing and computation of location estimates. Without these, nodes are not able to estimate the relative locations of other nodes within their communication range. This thesis defines a new distributed localisation algorithm for ad hoc networks of moving nodes. The Relative Neighbour Localisation (RNL) algorithm works without any external localisation signal or systems and does not assume centralised information processing. The idea behind the location estimates produced by the RNL algorithm is the relationship between the relative locations of two nodes, their mobility parameters and the signal strengths measured between them. The proposed algorithm makes use of the data available to each node to produce a location estimate. The signal strength each node is capable of measuring is used as one algorithm input. The other input is the velocity vector of the neighbouring node, composed of its speed and direction of movement, which each node is assumed to periodically broadcast. The relationship between the signal strength and the mobility parameters on one, and the relative location on the other side can be analytically formulated in an ideal case. The limitations of a realistic scenario complicate this relationship, making it very difficult to formulate analytically. An empirical approach is thus used. The angle and the distance estimates are individually computed, together forming a two-dimensional location estimate. The performance of the algorithm was analysed in detail using simulation, showing a median estimate error of under 10m, and its application was tested through design and evaluation of a distributed sensing coverage algorithm, showing RNL location estimates can provide 90% of the coverage achievable with true locations being known

A Hybrid Optimized Weighted Minimum Spanning Tree for the Shortest Intrapath Selection in Wireless Sensor Network

Wireless sensor network (WSN) consists of sensor nodes that need energy efficient routing techniques as they have limited battery power, computing, and storage resources. WSN routing protocols should enable reliable multihop communication with energy constraints. Clustering is an effective way to reduce overheads and when this is aided by effective resource allocation, it results in reduced energy consumption. In this work, a novel hybrid evolutionary algorithm called Bee Algorithm-Simulated Annealing Weighted Minimal Spanning Tree (BASA-WMST) routing is proposed in which randomly deployed sensor nodes are split into the best possible number of independent clusters with cluster head and optimal route. The former gathers data from sensors belonging to the cluster, forwarding them to the sink. The shortest intrapath selection for the cluster is selected using Weighted Minimum Spanning Tree (WMST). The proposed algorithm computes the distance-based Minimum Spanning Tree (MST) of the weighted graph for the multihop network. The weights are dynamically changed based on the energy level of each sensor during route selection and optimized using the proposed bee algorithm simulated annealing algorithm

Architecture and Methods for Innovative Heterogeneous Wireless Sensor Network Applications

Nowadays wireless sensor netwoks (WSN) technology, wireless communications and digital electronics have made it realistic to produce a large scale miniaturized devices integrating sensing, processing and communication capabilities. The focus of this paper is to present an innovative mobile platform for heterogeneous sensor networks, combined with adaptive methods to optimize the communication architecture for novel potential applications in multimedia and entertainment. In fact, in the near future, some of the applications foreseen for WSNs will employ multi-platform systems with a high number of different devices, which may be completely different in nature, size, computational and energy capabilities, etc. Nowadays, in addition, data collection could be performed by UAV platforms which can be a sink for ground sensors layer, acting essentially as a mobile gateway. In order to maximize the system performances and the network lifespan, the authors propose a recently developed hybrid technique based on evolutionary algorithms. The goal of this procedure is to optimize the communication energy consumption in WSN by selecting the optimal multi-hop routing schemes, with a suitable hybridization of different routing criteria. The proposed approach can be potentially extended and applied to ongoing research projects focused on UAV-based sensing with WSN augmentation and real-time processing for immersive media experiences

Design and evaluation of wireless dense networks : application to in-flight entertainment systems

Le réseau sans fil est l'un des domaines de réseautage les plus prometteurs avec des caractéristiques uniques qui peuvent fournir la connectivité dans les situations où il est difficile d'utiliser un réseau filaire, ou lorsque la mobilité des nœuds est nécessaire. Cependant, le milieu de travail impose généralement diverses contraintes, où les appareils sans fil font face à différents défis lors du partage des moyens de communication. De plus, le problème s'aggrave avec l'augmentation du nombre de nœuds. Différentes solutions ont été introduites pour faire face aux réseaux très denses. D'autre part, un nœud avec une densité très faible peut créer un problème de connectivité et peut conduire à l'optension de nœuds isolés et non connectes au réseau. La densité d'un réseau est définit en fonction du nombre de nœuds voisins directs au sein de la portée de transmission du nœud. Cependant, nous croyons que ces métriques ne sont pas suffisants et nous proposons une nouvelle mesure qui considère le nombre de voisins directs et la performance du réseau. Ainsi, la réponse du réseau, respectant l'augmentation du nombre de nœuds, est considérée lors du choix du niveau de la densité. Nous avons défini deux termes: l'auto-organisation et l'auto-configuration, qui sont généralement utilisés de façon interchangeable dans la littérature en mettant en relief la différence entre eux. Nous estimons qu'une définition claire de la terminologie peut éliminer beaucoup d'ambiguïté et aider à présenter les concepts de recherche plus clairement. Certaines applications, telles que Ies systèmes "In-Flight Entertainment (IFE)" qui se trouvent à l'intérieur des cabines d'avions, peuveut être considérées comme des systèmes sans fil de haute densité, même si peu de nœuds sont relativement présents. Pour résoudre ce problème, nous proposons une architecture hétérogène de différentes technologies à fin de surmonter les contraintes spécifiques de l'intérieur de la cabine. Chaque technologie vise à résoudre une partie du problème. Nous avons réalisé diverses expérimentations et simulations pour montrer la faisabilité de l'architecture proposée. Nous avons introduit un nouveau protocole d'auto-organisation qui utilise des antennes intelligentes pour aider certains composants du système IFE; à savoir les unités d'affichage et leurs systèmes de commande, à s'identifier les uns les autres sans aucune configuration préliminaire. Le protocole a été conçu et vérifié en utilisant le langage UML, puis, un module de NS2 a été créé pour tester les différents scénarios.Wireless networking is one of the most challenging networking domains with unique features that can provide connectivity in situations where it is difficult to use wired networking, or when ! node mobility is required. However, the working environment us! ually im poses various constrains, where wireless devices face various challenges when sharing the communication media. Furthermore, the problem becomes worse when the number of nodes increase. Different solutions were introduced to cope with highly dense networks. On the other hand, a very low density can create a poor connectivity problem and may lead to have isolated nodes with no connection to the network. It is common to define network density according to the number of direct neighboring nodes within the node transmission range. However, we believe that such metric is not enough. Thus, we propose a new metric that encompasses the number of direct neighbors and the network performance. In this way, the network response, due to the increasing number of nodes, is considered when deciding the density level. Moreover, we defined two terms, self-organization and self-configuration, which are usually used interchangeably in the literature through highlighting the difference ! between them. We believe that having a clear definition for terminology can eliminate a lot of ambiguity and help to present the research concepts more clearly. Some applications, such as In-Flight Entertainment (IFE) systems inside the aircraft cabin, can be considered as wirelessly high dense even if relatively few nodes are present. To solve this problem, we propose a heterogeneous architecture of different technologies to overcome the inherited constrains inside the cabin. Each technology aims at solving a part of the problem. We held various experimentation and simulations to show the feasibility of the proposed architecture