Mobile devices integrating wireless short-range communication technologies make possible new applications for spontaneous communication, interaction and collaboration. An interesting approach is to use collaboration to facilitate communication when mobile devices are not able to establish direct communication paths. Opportunistic networks, formed when mobile devices communicate with each other while users are in close proximity, can help applications still exchange data in such cases. In opportunistic networks routes are built dynamically, as each mobile device acts according to the store-carry-and-forward paradigm. Thus, contacts between mobile devices are seen as opportunities to move data towards destination. In such networks data dissemination is done using forwarding and is usually based on a publish subscribe model. Opportunistic data dissemination also raises questions concerning user privacy and incentives. Such problems are addressed dierently by various opportunistic data dissemination techniques. In this we analyze existing relevant work in the area of data dissemination in opportunistic networks. We present the categories of a proposed taxonomy that capture the capabilities of data dissemination techniques used in such networks. Moreover, we survey relevant data dissemination techniques and analyze them using the proposed taxonomy. In this we analyze existing work in the area of data dissemination in opportunistic networks. We analyze dif- ferent collaboration-based communication solutions, em- phasizing their capabilities to opportunistically dissemi- nate data. We present the advantages and disadvantages of the analyzed solutions. Furthermore, we propose the categories of a taxonomy that captures the capabilities of data dissemination techniques used in opportunistic net- works. Using the categories of the proposed taxonomy, we also present a critical analysis of four opportunistic data dissemination solutions. To our knowledge, a classication of data dissemination techniques has never been previously proposed.
Several papers exclusively treat the problem of data dissemination in opportunistic networks. The Epidemic approach is presented in @cite_5 . In @cite_10 , a dissemination technique based on publish subscribe communication and communities is described, while @cite_11 and @cite_6 propose a wireless ad hoc podcasting system based on opportunistic networks. A multicast distribution method is presented in @cite_3 , while ContentPlace, a system that exploits dynamically learned information about users' social relationships to decide where to place data objects in order to optimize content availability, is presented in @cite_0 . These methods are further analyzed in Section 4. To compare them we apply the categories of the proposed taxonomy. The obtained analysis highlights their advantages and disadvantages and further differentiates between their capabilities.
@cite_3 @cite_6 @cite_0 @cite_5 @cite_10 @cite_11
2111269948 2045295122 2112263843 1572481965 1997405607
This paper presents a publish subscribe-based multicast distribution infrastructure for DTN-based opportunistic networking environments. The distribution approach is designed to combine an effective distribution of content to interested nodes in the presence of resource constraints, mobility and unstable connectivity. By considering local resource constraints such as limited storage space and limited available bandwidth at opportunistic contacts as well as knowledge about interest for content in the network environment, nodes make local decisions about resource utilization and DTN bundle prioritization. Without further coordination, this approach uses the overall available network resources more effectively compared to other approaches such as epidemic forwarding. We have implemented this approach and have performed a series of measurements in mobile opportunistic networking scenarios under different configurations. Podcasting has become a very popular and successful Internet service in a short time. This success illustrates the interest for participatory broadcasting, in its actual form however, podcasting is only available with fixed infrastructure support to retrieve publicized episodes. We aim at releasing this limitation and present herein our podcasting system architecture together with a prototype implementation based on opportunistic wireless networking that allows us to extend podcasting to ad hoc domains. In this paper we present and evaluate ContentPlace, a data dissemination system for opportunistic networks, i.e., mobile networks in which stable simultaneous multi-hop paths between communication endpoints cannot be provided. We consider a scenario in which users both produce and consume data objects. ContentPlace takes care of moving and replicating data objects in the network such that interested users receive them despite possible long disconnections, partitions, etc. Thanks to ContentPlace, data producers and consumers are completely decoupled, and might be never connected to the network at the same point in time. The key feature of ContentPlace is learning and exploiting information about the social behaviour of the users to drive the data dissemination process. This allows ContentPlace to be more efficient both in terms of data delivery and in terms of resource usage with respect to reference alternative solutions. The performance of ContentPlace is thoroughly investigated both through simulation and analytical models. Mobile ad hoc routing protocols allow nodes with wireless adaptors to communicate with one another without any pre-existing network infrastructure. Existing ad hoc routing protocols, while robust to rapidly changing network topology, assume the presence of a connected path from source to destination. Given power limitations, the advent of short-range wireless networks, and the wide physical conditions over which ad hoc networks must be deployed, in some scenarios it is likely that this assumption is invalid. In this work, we develop techniques to deliver messages in the case where there is never a connected path from source to destination or when a network partition exists at the time a message is originated. To this end, we introduce Epidemic Routing, where random pair-wise exchanges of messages among mobile hosts ensure eventual message delivery. The goals of Epidemic Routing are to: i) maximize message delivery rate, ii) minimize message latency, and iii) minimize the total resources consumed in message delivery. Through an implementation in the Monarch simulator, we show that Epidemic Routing achieves eventual delivery of 100 of messages with reasonable aggregate resource consumption in a number of interesting scenarios. The emergence of Delay Tolerant Networks (DTNs) has culminated in a new generation of wireless networking. We focus on a type of human-to-human communication in DTNs, where human behaviour exhibits the characteristics of networks by forming a community. We show the characteristics of such networks from extensive study of real-world human connectivity traces. We exploit distributed community detection from the trace and propose a Socio-Aware Overlay over detected communities for publish subscribe communication. Centrality nodes have the best visibility to the other nodes in the network. We create an overlay with such centrality nodes from communities. Distributed community detection operates when nodes (i.e. devices) are in contact by gossipping, and subscription propagation is performed along with this operation. We validate our message dissemination algorithms for publish subscribe with connectivity traces.