On the Dynamics of Human Proximity for Data Diffusion in Ad-Hoc Networks

We report on a data-driven investigation aimed at understanding the dynamics of message spreading in a real-world dynamical network of human proximity. We use data collected by means of a proximity-sensing network of wearable sensors that we deployed at three different social gatherings, simultaneously involving several hundred individuals. We simulate a message spreading process over the recorded proximity network, focusing on both the topological and the temporal properties. We show that by using an appropriate technique to deal with the temporal heterogeneity of proximity events, a universal statistical pattern emerges for the delivery times of messages, robust across all the data sets. Our results are useful to set constraints for generic processes of data dissemination, as well as to validate established models of human mobility and proximity that are frequently used to simulate realistic behaviors.Comment: A. Panisson et al., On the dynamics of human proximity for data diffusion in ad-hoc networks, Ad Hoc Netw. (2011

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

Fast community structure local uncovering by independent vertex-centred process

This paper addresses the task of community detection and proposes a local approach based on a distributed list building, where each vertex broadcasts basic information that only depends on its degree and that of its neighbours. A decentralised external process then unveils the community structure. The relevance of the proposed method is experimentally shown on both artificial and real data.Comment: 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Aug 2015, Paris, France. Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Minin

Towards Efficient File Sharing and Packet Routing in Mobile Opportunistic Networks

With the increasing popularity of portable digital devices (e.g., smartphones, laptops, and tablets), mobile opportunistic networks (MONs) [40, 90] consisting of portable devices have attracted much attention recently. MONs are also known as pocket switched networks (PSNs) [52]. MONs can be regarded as a special form of mobile ad hoc networks (MANETs) [7] or delay tolerant networks (DTNs) [35, 56]. In such networks, mobile nodes (devices) move continuously and meet opportunistically. Two mobile nodes can communicate with each other only when they are within the communication range of each other in a peer-to-peer (P2P) manner (i.e., without the need of infrastructures). Therefore, such a network structure can potentially provide file sharing or packet routing services among portable devices without the support of network infrastructures. On the other hand, mobile opportunistic networks often experience frequent network partition, and no end-to-end contemporaneous path can be ensured in the network. These distinctive properties make traditional file sharing or packet routing algorithms in Internet or mobile networks a formidable challenge in MONs. In summary, it is essential and important to achieve efficient file sharing and packet routing algorithms in MONs, which are the key for providing practical and novel services and applications over such networks. In this Dissertation, we develop several methods to resolve the aforementioned challenges. Firstly, we propose two methods to enhance file sharing efficiency in MONs by creating replicas and by leveraging social network properties, respectively. In the first method, we investigate how to create file replicas to optimize file availability for file sharing in MONs. We introduce a new concept of resource for file replication, which considers both node storage and meeting frequency with other nodes. We theoretically study the influence of resource allocation on the average file access delay and derive a resource allocation rule to minimize the average file access delay. We also propose a distributed file replication protocol to realize the deduced optimal file replication rule. In the second method, we leverage social network properties to improve the file searching efficiency in MONs. This method groups common-interest nodes that frequently meet with each other into a community. It takes advantage of node mobility by designating stable nodes, which have the most frequent contact with community members, as community coordinators for intra-community file request forwarding, and highly-mobile nodes that visit other communities frequently as community ambassadors for inter-community file request forwarding. Based on such a community structure, an interest-oriented file searching scheme is proposed to first search local community and then search the community that is most likely to contain the requested file, leading to highly efficient file sharing in MONs. Secondly, we propose two methods to realize efficient packet routing among mobile nodes and among different landmarks in MONs, respectively. The first method utilizes distributed social map to route packets to mobile nodes efficiently with a low-cost in MONs. Each node builds its own social map consisting of nodes it has met and their frequently encountered nodes in a distributed manner. Based on both encountering frequency and social closeness of two linked nodes in the social map, we decide the weight of each link to reflect the packet delivery ability between the two nodes. The social map enables more accurate forwarder selection through a broader view and reduces the cost on information exchange. The second method realizes high-throughput packet routing among different landmarks in MONs. It selects popular places that nodes visit frequently as landmarks and divides the entire MON area into sub-areas represented by landmarks. Nodes transiting between two landmarks relay packets between the two landmarks. The frequency of node transits between two landmarks is measured to represent the forwarding capacity between them, based on which routing tables are built on each landmark to guide packet routing. Finally, packets are routed landmark by landmark to reach their destination landmarks. Extensive analysis and real-trace based experiments are conducted to support the designs in this Dissertation and demonstrate the effectiveness of the proposed methods in comparison with the state-of-art methods. In the future, we plan to further enhance the file sharing and packet routing efficiency by considering more realistic scenarios or including more useful information. We will also investigate the security and privacy issues in the proposed methods