Special section on Mobile Opportunistic Networking

It is a great pleasure to introduce this special section of the journal focusing on Mobile Opportunistic Networking. This emerging networking paradigm represents an important evolution of the self-organizing networking concept to provide effective communications in a pervasive computing environment. The huge proliferation of mobile devices with wireless networking capabilities makes it possible to foresee a pervasive networking environment in which users’ mobile devices will spontaneously network together and build self-organizing wireless networks for enabling users interaction and content exchange. In these scenarios, due to users’ mobility, the network will be intrinsically disconnected. Enabling device communications in such an intermittently connected world requires a departure from the legacy end-to-end model, where a complete path between sender and receiver must be established prior to transmission. In the legacymodel, nodes’mobility is seen as a problem tomask in order to provide stable end-to-end communication paths. Instead, opportunistic networks see nodes’ mobility as a communication opportunity when complete paths do not connect the source-destination pairs. Mobile opportunistic networks operate according to the store-carry-and-forward paradigm; node movements are exploited to bridge disconnections and bring data closer to the intended destination. In these networks, each contact among devices represents an opportunity for exchanging messages and finding good next hops towards the eventual destinations. An end-to-end path between the sender and the receiver may never exist and still mobile opportunistic networks are able to find a path for delivering the messages. Opportunistic networks thus encompass the scope of delay or disruption tolerant networks (DTN). This special section presents the extended versions of four selected papers originally presented at the ACM MobiOpp 2010 workshop. The first paper of this section ‘‘Connectivity in Time-Graphs’’ by Utku Gunay Acer, Petros Drineas, and Alhussein A. Abouzeid, investigates the relationship between some structural properties of the time-graphs that represent the connectivity in opportunistic networks, and performance figures such as the expected hitting time and the diffusion time. The paper takes an original direction by using 3-mode adjacency tensors to model time-graphs, and relate their structure to the network connectivity. The next two papers focus on routing scheme in opportunistic networks. In ‘‘Impact of Source Counter on Routing Performance in Resource Constrained DTNs’’, Xiaolan Zhang, Honggang Zhang, and Yu Gu study, by analysis and simulation, the performance of multi-hop multi-copy routing schemes in opportunistic networks. In particular they develop analytic models for the analysis of two-hop single-copy scheme and two-hop k-copy scheme for data delivery in opportunistic networks. In the next paper, entitled ‘‘Message Ferries as Generalized Dominating Sets in Intermittently Connected Mobile Networks’’, Bahadir K. Polat, Pushkar Sachdeva, Mostafa H. Ammar, and EllenW. Zegura investigate routing in opportunistic networks using the message ferries approach. A message ferry is a mobile node in charge of storing and carrying data between sources and destinations. Message ferries may need to relay data to each other to achieve connectivity between all nodes. In this paper the authors provide a formalism to characterize intrinsic message ferrying capabilities. Specifically, they show that the use of message ferries is the mobile generalization of the dominating set problem, and then they define the concept of a connected message ferry dominating set to achieve data delivery with certain performance bounds. Finally, the fourth paper, ‘‘From Encounters to Plausible Mobility’’ by John Whitbeck et al., presents a fast heuristic algorithm, inspired by dynamic force-based graph drawing, capable of inferring a plausible movement from any contact trace. In the paper the algorithm is evaluated on both synthetic and real-life contact traces. Results reveal that the quality of the inferredmobility is directly linked to the precision of themeasured contact trace, and the simple addition of appropriate anticipation forces between nodes leads to an accurate inferred mobility. This selection of papers, by addressing relevant theoretical and practical research issues, represents a very important contribution to the opportunistic networking literature, and Iwould like to thank the authors of these papers for contributing their high quality works. I take this opportunity to thanks the paper reviewers, who significantly contributed to the quality of this special section.