D2D Data Offloading in Vehicular Environments with Optimal Delivery Time Selection

Within the framework of a Device-to-Device (D2D) data offloading system for cellular networks, we propose a Content Delivery Management System (CDMS) in which the instant for transmitting a content to a requesting node, through a D2D communication, is selected to minimize the energy consumption required for transmission. The proposed system is particularly fit to highly dynamic scenarios, such as vehicular networks, where the network topology changes at a rate which is comparable with the order of magnitude of the delay tolerance. We present an analytical framework able to predict the system performance, in terms of energy consumption, using tools from the theory of point processes, validating it through simulations, and provide a thorough performance evaluation of the proposed CDMS, in terms of energy consumption and spectrum use. Our performance analysis compares the energy consumption and spectrum use obtained with the proposed scheme with the performance of two benchmark systems. The first one is a plain classic cellular scheme, the second is a D2D data offloading scheme (that we proposed in previous works) in which the D2D transmissions are performed as soon as there is a device with the required content within the maximum D2D transmission range..

Special Section on Autonomic and Opportunistic Communications

It is our great pleasure to introduce this Special Section of the Journal, focused on Autonomic and Opportunistic Communications. We strongly believe autonomic and opportunistic properties will be a key feature of the Future Mobile Internet. The huge proliferation of mobile devices with wireless networking capabilities makes it possible to foresee a Future Internet environment in which users\u27 mobile devices will spontaneously network together and build self-organizing wireless networks for enabling users interaction and content exchange. This will be a natural enabler for the take off of User Generated Content and other user-centred networking models in the area of pervasive mobile networks

Egocentric online social networks: Analysis of key features and prediction of tie strength in Facebook

The widespread use of online social networks, such as Facebook and Twitter, is generating a growing amount of accessible data concerning social relationships. The aim of this work is twofold. First, we present a detailed analysis of a real Facebook data set aimed at characterising the properties of human social relationships in online environments. We find that certain properties of online social networks appear to be similar to those found ?offline? (i.e., on human social networks maintained without the use of social networking sites). Our experimental results indicate that on Facebook there is a limited number of social relationships an individual can actively maintain and this number is close to the well-known Dunbar?s number (150) found in offline social networks. Second, we also present a number of linear models that predict tie strength (the key figure to quantitatively represent the importance of social relationships) from a reduced set of observable Facebook variables. Specifically, we are able to predict with good accuracy (i.e., higher than 80%) the strength of social ties by exploiting only four variables describing different aspects of users interaction on Facebook. We find that the recency of contact between individuals ? used in other studies as the unique estimator of tie strength ? has the highest relevance in the prediction of tie strength. Nevertheless, using it in combination with other observable quantities, such as indices about the social similarity between people, can lead to more accurate prediction

SPoT: Representing the Social, Spatial, and Temporal Dimensions of Human Mobility with a Unifying Framework

Modeling human mobility is crucial in the analysis and simulation of opportunistic networks, where contacts are exploited as opportunities for peer-topeer message forwarding. The current approach with human mobility modeling has been based on continuously modifying models, trying to embed in them the mobility properties (e.g., visiting patterns to locations or specific distributions of inter-contact times) as they came up from trace analysis. As a consequence, with these models it is difficult, if not impossible, to modify the features of mobility or to control the exact shape of mobility metrics (e.g., modifying the distribution of inter-contact times). For these reasons, in this paper we propose a mobility framework rather than a mobility model, with the explicit goal of providing a exible and controllable tool for modeling mathematically and generating simulatively different possible features of human mobility. Our framework, named SPoT, is able to incorporate the three dimensions - spatial, social, and temporal - of human mobility. The way SPoT does it is by mapping the different social communities of the network into different locations, whose members visit with a configurable temporal pattern. In order to characterize the temporal patterns of user visits to locations and the relative positioning of locations based on their shared users, we analyze the traces of real user movements extracted from three location-based online social networks (Gowalla, Foursquare, and Altergeo). We observe that a Bernoulli process effectively approximates user visits to locations in the majority of cases and that locations that share many common users visiting them frequently tend to be located close to each other. In addition, we use these traces to test the exibility of the framework, and we show that SPoT is able to accurately reproduce the mobility behavior observed in traces. Finally, relying on the Bernoulli assumption for arrival processes, we provide a throughout mathematical analysis of the controllability of the framework, deriving the conditions under which heavy-tailed and exponentially-tailed aggregate inter-contact times (often observed in real traces) emerge

Intercontact times in opportunistic networks and their impact on forwarding convergence

The increasing popularity of some new mobile technologies (smartphones for example) has opened new interesting scenarios in communications because of the possibility of a device to communicate with another one without using the wireless (or wired) network interfaces but taking advantages of the mobility of all the devices. In this direction, one of the most important evolution of Mobile ad hoc networks are opportunistic networks, that are self-organizing networks where there are not any guarantee of two devices to be linked with complete multi-hop path in any time. What a node has to do to deliver a certain message, is to nd a space-time multi-hop path, that is portions of path that can carry on the message during the time until it reaches the destination. We can see an example in Figure 1: the source S has to deliver a message to the destination D; the message can arrive at D at time t3, even if in [t1,t3] S and D are not directly linked. As nodes do not have any knowledges of the network topology, but only of the destination the massage have to arrive to, this way of delivering needs at any time to make some decisions, that are to whom has to be sent message and how many copies has to be sent

The stability region of the delay in Pareto opportunistic networks

The intermeeting time, i.e., the time between two consecutive contacts between a pair of nodes, plays a fundamental role in the delay of messages in opportunistic networks. A desirable property of message delay is that its expectation is finite, so that the performance of the system can be predicted. Unfortunately, when intermeeting times feature a Pareto distribution, this property does not always hold. In this paper, assuming heterogeneous mobility and Pareto intermeeting times, we provide a detailed analysis of the conditions for the expectation of message delay to be finite (i.e., to converge) when social-oblivious or social-aware forwarding schemes are used. More specifically, we consider different classes of social-oblivious and social-aware schemes, based on the number of hops allowed and the number of copies generated. Our main finding is that, in terms of convergence, allowing more than two hops may provide advantages only in the social-aware case. At the same time, we show that using a multi-copy scheme can in general improve the convergence of the expected delay. We also compare social-oblivious and social-aware strategies from the convergence standpoint and we prove that, depending on the mobility scenario considered, social-aware schemes may achieve convergence while social-oblivious cannot, and vice versa. Finally, we apply the derived convergence conditions to three popular contact data sets available in the literature (Cambridge, Infocom, and RollerNet), assessing the convergence of each class of forwarding protocols in these three cases

Design and Performance Evaluation of Data Dissemination Systems for Opportunistic Networks Based on Cognitive Heuristics

It is often argued that the Future Internet will be a very large scale content-centric network. Scalability issues will stem even more from the amount of content nodes will gen- erate, share and consume. In order to let users become aware and retrieve the content they really need, these nodes will be required to swiftly react to stimuli and assert the rele- vance of discovered data under uncertainty and only partial information. The human brain performs the task of infor- mation ltering and selection using the so-called cognitive heuristics, i.e. simple, rapid, low-resource demanding, yet very eective schemes that can be modeled using a func- tional approach. In this paper we propose a solution based on one such heuristics, namely the recognition heuristic, for dealing with data dissemination in opportunistic networks. We show how to implement an algorithm that exploits the environmental information in order to implement an eec- tive dissemination of data based on the recognition heuristic, and provide a performance evaluation of such a solution via simulation

The stability region of the delay in Pareto opportunistic networks

The intermeeting time, i.e., the time between two consecutive contacts between a pair of nodes, plays a fundamental role in the delay of messages in opportunistic networks. A desirable property of message delay is that its expectation is finite, so that the performance of the system can be predicted. Unfortunately, when intermeeting times feature a Pareto distribution, this property does not always hold. In this paper, assuming heterogeneous mobility and Pareto intermeeting times, we provide a detailed analysis of the conditions for the expectation of message delay to be finite (i.e., to converge) when social-oblivious or social-aware forwarding schemes are used. More specifically, we consider different classes of social-oblivious and social-aware schemes, based on the number of hops allowed and the number of copies generated. Our main finding is that, in terms of convergence, allowing more than two hops may provide advantages only in the social-aware case. At the same time, we show that using a multi-copy scheme can in general improve the convergence of the expected delay. Finally, we compare social-oblivious and social-aware strategies from the convergence standpoint and we prove that, depending on the mobility scenario considered, social-aware schemes may achieve convergence while social-oblivious cannot, and vice versa