Thais R. M. Braga Silva

Vehicular Networks: A New Challenge for Content-Delivery-Based Applications

A significant number of promising applications for vehicular ad hoc networks (VANETs) are becoming a reality. Most of these applications require a variety of heterogenous content to be delivered to vehicles and to their on-board users. However, the task of content delivery in such dynamic and large-scale networks is easier said than done. In this article, we propose a classification of content delivery solutions applied to VANETs while highlighting their new characteristics and describing their underlying architectural design. First, the two fundamental building blocks that are part of an entire content delivery system are identified: replica allocation and content delivery. The related solutions are then classified according to their architectural definition. Within each category, solutions are described based on the techniques and strategies that have been adopted. As result, we present an in-depth discussion on the architecture, techniques, and strategies adopted by studies in the literature that tackle problems related to vehicular content delivery networks.

A conflict resolution methodology for collective ubiquitous context-aware applications

The context-aware computing is a research field that defines systems capable of adapting their behavior according to any relevant information about entities (e.g.,people, places and objects) of interest. The ubiquitous computing is closely related to the use of contexts, since it aims to provide personalized, transparent and on-demand services. Ubiquitous systems are frequently shared among multiple users, once they are designed to be embedded into everyday objects and environments such as houses, cars and offices. In scenarios where more than one user shares the same ubiquitous context-aware application, conflicts may occur during adaptation actions due to individual profiles divergences and/or environment resources incompatibility. In such situations it is interesting to use computer supported collaborative work techniques in order to detect and solve those conflicts, considering what is better for the group but also being fair enough with each individual demand, whenever possible. This work presents the important concepts on the collective ubiquitous context-aware applications field. Furthermore, it proposes a new methodology for conflicts detection and resolution that considers the trade-off between quality of services and resources consumption.

Solving collective conflicts in a disaster emergency attendance application

The context-aware computing is a research field that defines systems capable of adapting their behavior according to any relevant information about entities (e.g., people, places and objects) of interest. Ubiquitous systems are closely related to the use of contexts and are frequently shared among multiple users, once they are designed to be embedded into everyday environments such as houses, cars, and offices. In scenarios where more than one user shares the same ubiquitous context-aware application, conflicts may occur during adaptation actions due to individual profile divergences and/or environment resource incompatibility. In such situations it is interesting to use some mechanism to detect and solve those conflicts, considering what is better for the group but also being fair enough with each individual demand, whenever possible. This work presents the important concepts in the collective ubiquitous context-aware applications field through a disaster emergency attendance application. Furthermore, the proposal of a methodology for conflict detection and resolution is described. The obtained simulation results showed how this methodology can maintain the application working properly while solving the collective conflicts, managing resource consumption and providing an interesting user satisfaction average.

ODCRep: Origin–Destination-Based Content Replication for Vehicular Networks

The evolution of vehicular network applications, from simple alert message exchange to more elaborate and sophisticated systems, boosts the need for content delivery solutions. A useful technique, in this case, is content replication, in which strategically selected vehicles replicate content and help in the delivery process. However, content replication is particularly challenging in vehicular networks, due to their special characteristics, such as highly dynamic topology, diverse density, and large-scale scenarios. Although there has been progress in routing and dissemination solutions for vehicular networks, few studies have concentrated on the content replication problem. To address this issue, we propose an origin-destination-based content replication (ODCRep) solution that focuses on balancing the number of replicas across the application area. Differently from existing solutions, ODCRep relies only on the origin-destination information and uses computationally efficient algorithms. Results from exhaustive simulations show that ODCRep can achieve high coverage, yet can also consume fewer resources than existing solutions.

A novel macroscopic mobility model for vehicular networks

Researchers face a great challenge when evaluating large-scale vehicular ad hoc network solutions. Since it is not feasible to perform real experiments in this case, and there are no large-scale testbeds available, simulation is the most frequently used evaluation technique, which requires a realistic mobility model to provide accurate results. However, building large-scale realistic vehicular mobility models is a difficult task and many important characteristics have been neglected, particularly macroscopic ones. In this work, a realistic vehicular mobility trace is characterized and macroscopic features are inferred. Based on this characterization, we propose and validate a macroscopic mobility model that provides more realistic characteristics to the vehicular network evaluation process. The obtained results contribute to the research community by providing a more realistic macroscopic model that complements many vehicular mobility generators available in the literature.

On the Improvement of Vehicular Macroscopic Mobility Models

Evaluating large scale vehicular networks solutions is a great challenge once real experiments are not feasible yet and there are no large scale testbeds available. Thus, the most used evaluation technique is simulation, which requires a realistic mobility model to provide accurate results. However, building large scale realistic vehicular mobility models is a hard task and many important characteristics have been neglected, like the origin-destination (O-D) macroscopic one. In this work it is proposed a trace-based O-D macroscopic model inferred by the adoption of statistical techniques in order to characterize a validated traffic model. This work contributes to the research community by providing a more realistic O-D macroscopic model, which can be considered a complement for many traffic generators available in literature.

Improving Information Dissemination in Vehicular Networks by Selecting Appropriate Disseminators

Information dissemination applications (e.g. weather, news, advertisements, traffic, and so on) are among the most promising ones for vehicular networks. However, disseminating information to all vehicles in vehicular networks is not a trivial task because of their specific characteristics like high dynamic topology and different density values along time and space. The proposals found in literature focused on improved flooding schemes that, in realistic scenarios, may cause unnecessary overhead and redundant data. This work addresses the dissemination to all vehicles problem by assuming that some vehicles are more appropriate to be good disseminators than others. This hypothesis was validated through a large-scale urban mobility scenario and two heuristics were proposed to select the appropriate disseminators. Results showed that the proposed heuristics were able to achieve high coverage (more than 97% of vehicles) with low redundant data.

Content replication and delivery in vehicular networks

Vehicular Ad-Hoc Network (VANET) applications usually require some kind of content to be delivered to vehicles. However, this task is easier said than done because of the VANETs specific characteristics, such as highly dynamic topology, short intermittent contacts, different density scenarios, and large-scale, to name a few. Thus, one concept that seems to be of great help is that of Content Delivery Network (CDN), in which strategically nodes are selected to act as servers and to help on the delivery process. Some researchers have started working on the application of such concept to VANET scenarios. In this paper, we present the state-of-the-art survey on the vehicular content delivery network (VCDN) field by presenting and discussing the main related studies found in the literature.

Discovering Mobile Application Usage Patterns from a Large-Scale Dataset

The discovering of patterns regarding how, when, and where users interact with mobile applications reveals important insights for mobile service providers. In this work, we exploit for the first time a real and large-scale dataset representing the records of mobile application usage of 5,342 users during 2014. The data was collected by a software agent, installed at the users’ smartphones, which monitors detailed usage of applications. First, we look for general patterns of how users access some of the most popular mobile applications in terms of frequency, duration, diversity, and data traffic. Next, we mine the dataset looking for temporal patterns in terms of when and how often accesses occur. Finally, we exploit the location of each access to detect users’ points of interest and location-based communities. Based on the results, we derive a model to generate synthetic datasets of mobile application usage and evaluate solutions to predict the next application to be launched. We also discuss a series of implications of the findings regarding telecommunication services, mobile advertisements, and smart cities. This is the first time this dataset is used, and we also make it publicly available for other researchers.

CReMe: a Dynamic and Flexible Conflict Resolution Methodology for Competitive Ambient Systems

Abstract Ambient Systems are available to their users all the time and everywhere. Most of them can be viewed as collective applications, i.e., shared by two or more users, which may lead to competition for resources and personal needs, generating conflicts of interests. The goal of this work is to present CReMe, a dynamic and flexible methodology to detect and solve conflicts for ambient systems. Two distinct case studies were evaluated to demonstrate CReMes characteristics. The results showed that it was possible to accomplish a tradeoff between computational resources consumption and users’ satisfaction.