Bootstrapping opportunistic networks using social roles

Opportunistic routing protocols can enable message delivery in disconnected networks of mobile devices. To conserve energy in mobile environments, such routing protocols must minimise unnecessary message-forwarding. This paper presents an opportunistic routing protocol that leverages social role information. We compute node roles from a social network graph to identify nodes with similar contact relationships, and use these roles to determine routing decisions. By using pre-existing social network information, such as online social network friends, to determine roles, we show that our protocol can bootstrap a new opportunistic network without the delay incurred by encounter-history-based routing protocols such as SimbetTS. Simulations with four real-world datasets show improved performance over SimbetTS, with performance approaching Epidemic routing in some scenarios.Postprin

Towards Adaptable and Adaptive Policy-Free Middleware

We believe that to fully support adaptive distributed applications, middleware must itself be adaptable, adaptive and policy-free. In this paper we present a new language-independent adaptable and adaptive policy framework suitable for integration in a wide variety of middleware systems. This framework facilitates the construction of adaptive distributed applications. The framework addresses adaptability through its ability to represent a wide range of specific middleware policies. Adaptiveness is supported by a rich contextual model, through which an application programmer may control precisely how policies should be selected for any particular interaction with the middleware. A contextual pattern mechanism facilitates the succinct expression of both coarse- and fine-grain policy contexts. Policies may be specified and altered dynamically, and may themselves take account of dynamic conditions. The framework contains no hard-wired policies; instead, all policies can be configured.Comment: Submitted to Dependable and Adaptive Distributed Systems Track, ACM SAC 200

Opportunistic data collection through delegation

We consider a collection system where collectors move around gathering information generated by data producers. In such a system, data may remain uncollected when the number of collectors is insufficient to cover the whole population of producers. Motivated by the observation that node encounters are sufficient to build a connected relationship graph, we propose to take advantage of the inherent interactions among nodes and transform some producers into delegates. With such an approach, collectors only need to meet delegates that, in turn, are responsible for gathering data from a subset of standard producers. We achieve this goal through two contributions. First, we investigate several delegation strategies based on the relative importance of nodes in their social interactions (i.e., the node centrality). Second, by considering a prediction strategy that estimates the likelihood of two nodes meeting each other, we investigate how the delegation strategies perform on predicted traces. We evaluate the delegation strategies both in terms of coverage and size of the delegation existing real mobility data sets. We observe that delegation strategies that rely on localized information perform as well as the ones that consider a complete view of the topology.Nous considérons un système de collecte où les collectionneurs se déplacent et collectent les informations générées par les producteurs de données. Dans un tel système, les données peuvent ne pas être collectées lorsque le nombre de collectionneurs est insuffisant pour couvrir l'ensemble de la population des producteurs. Motivé par le fait que les rencontres de nœuds sont suffisants pour construire un graphe connecté, nous proposons de profiter des interactions inhérentes entre les nœuds et transformer certains producteurs en délégués. Avec une telle approche, les collectionneurs ont seulement besoin de rencontrer les délégués que, à leur tour, sont responsables de la collecte de données d'un sous-ensemble des producteurs. Nous atteignons cet objectif grâce à deux contributions. Tout d'abord, nous étudions plusieurs stratégies de délégation basée sur l'importance relative des nœuds dans leurs interactions sociales (par exemple, la centralité du nœud). Deuxièmement, en considérant une stratégie de prédiction qui donne les estimations de la probabilité d'une rencontre de deux nœuds, nous étudions les stratégies de délégation avec les traces prédit. Nous évaluons les stratégies de délégation à la fois en termes de couverture et de la taille du groupe de délégation en utilisant des traces de mobilité réelles. Nous n'observons que les stratégies de délégation qui se basent sur des informations localisées fournis aussi des bons résultats comparés aux résultats considérant une vue complète de la topologie

Bootstrapping opportunistic networks using social roles

Opportunistic routing protocols can enable message delivery in disconnected networks of mobile devices. To conserve energy in mobile environments, such routing protocols must minimise unnecessary message-forwarding. This paper presents an opportunistic routing protocol that leverages social role information. We compute node roles from a social network graph to identify nodes with similar contact relationships, and use these roles to determine routing decisions. By using pre-existing social network information, such as online social network friends, to determine roles, we show that our protocol can bootstrap a new opportunistic network without the delay incurred by encounter-history-based routing protocols such as SimbetTS. Simulations with four real-world datasets show improved performance over SimbetTS, with performance approaching Epidemic routing in some scenarios.Postprin

Using self-reported social networks to improve opportunistic networking

Opportunistic networks provide an ad hoc communication medium without the need for an infrastructure network, by leveraging human encounters and mobile devices. Routing protocols in opportunistic networks frequently rely upon encounter histories to build up meaningful data to use for informed routing decisions. This thesis shows that it is possible to use pre-existing social-network information to improve existing opportunistic routing protocols, and that these self-reported social networks have a particular benefit when used to bootstrap an opportunistic routing protocol. Frequently, opportunistic routing protocols require users to relay messages on behalf of one another: an act that incurs a cost to the relaying node. Nodes may wish to avoid this forwarding cost by not relaying messages. Opportunistic networks need to incentivise participation and discourage the selfish behaviour. This thesis further presents an incentive mechanism that uses self-reported social networks to construct and maintain reputation and trust relationships between participants, and demonstrates its superior performance over existing incentive mechanisms