Routing in Opportunistic Networks

Abstract

Opportunistic networking is employed in scenarios where end-to-end communication paths between nodes cannot be assumed due to continuously changing network topology. In these networks, data is routed in a "store-carry-forward" fashion by exploiting the transient communication opportunities that arise when mobile nodes equipped with short-range wireless interfaces come within each other's transmission range. Designing efficient routing schemes for opportunistic networks is challenging as they face a trade-off between delivery performance and resource consumption. In this thesis, we propose a novel opportunistic routing algorithm that addresses this trade-off by incorporating information about the node contact pattern in the network. Aggregating contact events into a weighted graph enables us to detect communities and learn about the neighbourhoods of nodes. This information is utilized by our algorithm to assess the usefulness of every forwarding opportunity that arises. Performance evaluation of the proposed algorithm shows that it is capable of achieving good delivery performance while consuming significantly fewer resources in comparison to the existing opportunistic routing algorithms.ii Sommaire Le réseautage opportuniste est utilisé dans les scénarios où l'existence de routes de communication entre agents ne peut pasêtre présumé dûà l'altération constante de la topologie du réseau. Dans ces réseaux, l'information est acheminée grâceà une procédure de "sauvegarde-report" qui exploite les opportunités de communication transitoires qui ont lieu lorsque des agentséquippés d'interface sans-filà petite portée entrent dans leurs périmètres de portée respectifs.Établir des plans de communication efficaces dans le contexte de réseaux opportunistes est un défi puisque ceux-ci font faceà un compromis entre performance de livraison et consommation de ressources. Dans cette thèse, nous proposons un algorithme de routage opportuniste original qui addresse ce compromis en incorporant l'information liée aux contacts entre noeuds du réseau. Assembler lesévènements de contacts dans un graphe pondéré nous permet de détecter les communautés et d'apprendre le voisinage de chaque noeud. Cette information est utilisée par notre algorithme afin d'évaluer l'utilité de chaque opportunité de communication qui se présente. Une analyse de la performance de l'algorithme proposé montre qu'il est capable d'atteindre une bonne performance de livraison tout en consommant significativement moins de ressources lorsque comparé aux algorithmes de routage opportuniste actuels.iii

Dynamic Rendezvous Based Routing Algorithm on Sparse Opportunistic Network Environment

“…An OppNet routing is designed to address an extreme network environment where the source and destination node might never be fully connected at the same time. The OppNet routing can be used in several recent applications such as Social Mobile Network, Disaster Recovery Networks, Military Tactical Network, and Movable Sensor Networks as described in the recent books [31–33]. Social Mobile Network [34–37]: the OppNet nodes are represented by mobile application utilizing available nearby communication channels to relay the messages toward the destination. Disaster Recovery Networks [38–41]: when a stable infrastructure is destroyed by a natural disaster, the mobile agents are utilized to exchange the messages between victims, first responders, or rescue teams without long range wireless transmission. Military Tactical Network [42–44]: the OppNet nodes are represented by soldiers equipped with communication devices to communicate with each other and mobile command post to facilitate the data exchange in the operational area. Movable Sensor Networks [45–47]: the data collection is done utilizing stationary sensor node and movable sensor node.…”

Selfish node detection algorithm based on fuzzy game theory in mobile social networks

“…In addition, fear of malicious data from unknown nodes and unwillingness to help other community nodes leads to selfish behavior. These nNodes are not actually selfish, but do not participate in the routing process [9]. In general, selfishness is a vital problem for the networks that their operation depends on the responsibilities and accuracy of the nodes.…”