nikodin.ristanovic

Abstract—Data dissemination is useful for many applications

3G networks are currently overloaded, due to the increasing popularity of various applications for smartphones. Offloading mobile data traffic through opportunistic communications is a promising solution to partially solve this problem, because there is almost no monetary cost for it. We propose to exploit opportunistic communications to facilitate information dissemination in the emerging Mobile Social Networks (MoSoNets) and thus reduce the amount of mobile data traffic. As a case study, we investigate the target-set selection problem for information delivery. In particular, we study how to select the target set with only k users, such that we can minimize the mobile data traffic over cellular networks. We propose three algorithms, called Greedy, Heuristic, and Random, for this problem and evaluate their performance through an extensive trace-driven simulation study. Our simulation results verify the efficiency of these algorithms for both synthetic and real-world mobility traces. For example, the Heuristic algorithm can offload mobile data traffic by up to 73.66 % for a real-world mobility trace. Moreover, to investigate the feasibility of opportunistic communications for mobile phones, we implement a proof-of-concept prototype, called Opp-Off, on Nokia N900 smartphones, which utilizes their Bluetooth interface for device/service discovery and content transfer. Index Terms Mobile data offloading, target-set selection, opportunistic communications, mobile social networks, implementation, trace-driven simulation. 2 I.

to optimize global performance in Delay Tolerant Networks (DTNs). These methods rely on simple local node operations and consensus algorithms to average neighbours ’ information. Existing results for convergence to optimal solutions can only be applied to DTNs in the case of synchronous operation of the nodes and memory-less random meeting processes. In this paper we address both these issues. First, we prove convergence to the optimal solution for a more general class of mobility models. Second, we show that, under asynchronous operations, a direct application of the original sub-gradient method would lead to suboptimal solutions and we propose some adjustments to solve this problem. Further, at the end of the paper, we illustrate a possible DTN application to demonstrate the validity of this optimization approach. IndexTerms—delaytolerantnetworks,distributedoptimization, consensus, sub-gradient method I.

Abstract—Opportunistic ad-hoc communication enables portable devices such as smartphones to effectively exchange information, taking advantage of their mobility and locality. The nature of human interaction makes information dissemination using such networks challenging. We use three different experimental traces to study fundamental properties of human interactions. We break our traces down in multiple areas and classify mobile users in each area according to their social behavior: Socials are devices that show up frequently or periodically, while Vagabonds represent the rest of the population. We find that in most cases the majority of the population consists of Vagabonds. We evaluate the relative role of these two groups of users in data dissemination. Surprisingly, we observe that under certain circumstances, which appear to be common in real life situations, the effectiveness of dissemination predominantly depends on the number of users in each class rather than their social behavior, contradicting some of the previous observations. We validate and extend the findings of our experimental study through a mathematical analysis. I.

Delay Tolerant Networks (DTNs) have evolved from Mobile Ad Hoc Networks (MANET). It is a network, where contemporaneous connectivity among all nodes doesn‟t exist. This leads to the problem of how to route a packet from one node to another, in such a network. This problem becomes more complex, when the node mobility also is considered. The researchers have attempted to address this issue for over a decade. They have found that communication is possible in such a challenged network. The design of routing protocol for such networks is an important issue. This work surveys the literature and classifies the various routing approaches.

Abstract. We study and characterize social-aware forwarding protocols in opportunistic networks and we derive bounds on the expected message delivery time for two different routing protocols, which are representatives of social-oblivious and social-aware forwarding. In particular, we consider a recently introduced stateless, social-aware forwarding protocol using interest similarity between individuals, and the well-known BinarySW protocol, which is optimal within a certain class of stateless, social-oblivious forwarding protocols. We compare both from the theoretical and experimental point of view the asymptotic performance of Interest-Based (IB) forwarding and BinarySW under two mobility scenarios, modeling situations in which pairwise meeting rates between nodes are either independent of or correlated to the similarity of their interests. 1

Abstract—Opportunistic mobile networks are a promising way to offload infrastructure networks, or provide communication in case of insufficient or non-existent infrastructure coverage. Understanding of the mobility process that drives such networks is crucial for design, analysis, and configuration. Generally, this mobility process is modeled on a plain playground where devices can move freely; both in case of simulation, and analysis of real-world traces. Graph-based playgrounds provide more realistic models but their impact on mobility is insufficiently understood. We provide a methodology to analyze the impact of the underlying graph on inter-contact time using methods from spectral graph theory. We gather the inter-contact times that both a random and a social mobility model exhibit on synthetic grid-based graphs and real-world city maps through simulations and perform fitting to a model for inter-contact time distribution. We then analyze correlations between parameters of these distributions and the spectral gap of a graph. Our main finding is that the graph structure has strong impact on intercontact time distribution in both random and social mobility on grid-based graphs. For real-world city graphs a social mobility model determines inter-contact time independently of the graph structure, whereas the graph structure has strong impact on inter-contact times for a random mobility process. I.

Abstract—Node mobility and end-to-end disconnections in Disruption Tolerant Networks (DTNs) greatly impair the effectiveness of data forwarding. Although social-based approaches can address the problem, most existing solutions only focus on forwarding data to a single destination. In this paper, we study multicast with single and multiple data items in DTNs from a social network perspective, develop analytical models for multicast relay selection, and furthermore investigate the essential difference between multicast and unicast in DTNs. The proposed approach selects relays according to their capabilities, measured by social-based metrics, for forwarding data to the destinations. The design of social-based metrics exploits social network concepts such as node centrality and social community, and the selected relays ensure achieving the required data delivery ratio within the given time constraint. Extensive tracedriven simulations show that the proposed approach has similar data delivery ratio and delay to that of Epidemic routing, but significantly reduces data forwarding cost, measured by the number of relays used. Index Terms—Multicast, Disruption Tolerant Network, social network, centrality, community.

Abstract—As content that users access on their mobile devices becomes bulkier, opportunistic networking is becoming a potential complement to centralised and infrastructure based downloads. We study how users share items of mutual interest with each other with a simple model based on a ‘networked urn process’. We investigate the effect of different content sharing policies upon a multi-category set of items. We find that the process of sharing mutual interests inherently disproportionately reinforces category replication disparity, i.e., the most popular categories become proportionally even more numerous. These findings uncover a major hurdle in the creation of automatic opportunistic file sharing between users. Even if users altruistically sacrifice battery power and network resources to share content not relevant to them, overall, the system may not be able to fairly distribute items that belong to niche categories. I.