Skipping-based handover algorithm for video distribution over ultra-dense VANET

Next-generation networks will pave the way for video distribution over vehicular Networks (VANETs), which will be composed of ultra-dense heterogeneous radio networks by considering existing communication infrastructures to achieve higher spectral efficiency and spectrum reuse rates. However, the increased number of cells makes mobility management schemes a challenging task for 5G VANET, since vehicles frequently switch among different networks, leading to unnecessary handovers, higher overhead, and ping-pong effect. In this sense, an inefficient handover algorithm delivers videos with poor Quality of Experience (QoE), caused by frequent and ping-pong handover that leads to high packets/video frames losses. In this article, we introduce a multi-criteria skipping-based handover algorithm for video distribution over ultra-dense 5G VANET, called Skip-HoVe. It considers a skipping mechanism coupled with mobility prediction, Quality of Service (QoS)- and QoE-aware decision, meaning the handovers are made more reliable and less frequently. Simulation results show the efficiency of Skip-HoVe to deliver videos with Mean Opinion Score (MOS) 30% better compared to state-of-the-art algorithms while maintaining a ping-pong rate around 2%.publishe

Conflicts treatment for ubiquitous collective and context-aware applications

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, which may lead to conflicts that occur during adaptation actions due to individual profiles divergences and/or environment resources incompatibility. In such situations it is interesting 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 novel methodology for conflicts detection and resolution that considers the trade-off between quality of services and resources consumption. A case study based on a collective tourist guide was implemented as a proof-of-study to the proposed methodology.Key words: context and awareness in collaborative systems, ubiquitous computing, adaptive collaborative environments

From movement purpose to perceptive spatial mobility prediction

A major limiting factor for prediction algorithms is the forecast of new or never before-visited locations. Conventional personal models utterly relying on personal location data perform poorly when it comes to discoveries of new regions. The reason is explained by the prediction relying only on previously visited/seen (or known) locations. As a side effect, locations that were never visited before (or explorations) by a user cause disturbance to known location's prediction. Besides, such explorations cannot be accurately predicted. We claim the tackling of such limitation first requires identifying the purpose of the next probable movement. In this context, we propose a novel framework for adjusting prediction resolution when probable explorations are going to happen. As recently demonstrated [3, 15], there exist regularities in returning and exploring visits. Moreover, the geographical occurrences of explorations are far from being random in a coarser-grained spatial resolution. Exploiting these properties, instead of directly predicting a user's next location, we design a two-step predictive framework. First, we infer an individual's next type of transition: (i) a return, i.e., a visit to a previously known location, or (ii) an exploration, i.e., a discovery of a new place. Next, we predict the next location or the next coarse-grained zone depending on the inferred type of movement. We conduct extensive experiments on three real-world GPS mobility traces. The results demonstrate substantial improvements in the accuracy of prediction by dint of fruitfully forecasting coarse-grained zones used for exploration activities. To the best of our knowledge, we are the first to propose a framework solely based on personal location data to tackle the prediction of visits to new places.Accepted manuscrip

Learning and distinguishing time series dynamics via ordinal patterns transition graphs

Strategies based on the extraction of measures from ordinal patterns transformation, such as probability distributions and transition graphs, have reached relevant advancements in distinguishing different time series dynamics. However, the reliability of such measures depends on the appropriate selection of parameters and the need for large time series. In this paper we present a method for the characterization of distinct time series behaviors based on the probability of self-transitions, a measure extracted from their transformation onto ordinal patterns transition graphs. We validate our method by investigating the main characteristics of periodic, random, and chaotic time series. By the application of learning strategies, we precisely classify different randomness levels in time series, reaching 100% in accuracy, and advances in performing the hard task of distinguishing random noises from chaotic time series, correctly distinguishing 96.61% of the cases. Furthermore, we show that this strategy is well suitable to be used by many applications, even for short time series, and does not depend on the selection of parameters.Fil: Borges, João B.. Universidade Federal de Minas Gerais; Brasil. Universidade Federal do Rio Grande do Norte; BrasilFil: Ramos, Heitor S.. Universidade Federal de Minas Gerais; BrasilFil: Mini, Raquel A.F.. Pontificia Universidade Catolica de Minas Gerais;Fil: Rosso, Osvaldo Aníbal. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidade Federal de Alagoas; Brasil. Instituto Universidad Escuela de Medicina del Hospital Italiano; ArgentinaFil: Frery, Alejandro C.. Universidade Federal de Alagoas; BrasilFil: Loureiro, Antonio A.F.. Universidade Federal de Minas Gerais; Brasi

Information Fusion for Data Dissemination in Self-Organizing Wireless Sensor

Data dissemination is a fundamental task in wireless sensor networks. Because of the radios range limitation and energy consumption constraints, sensor data is commonly disseminated in a multihop fashion (flat networks) through a tree topology. However, to the best of our knowledge none of the current solutions worry about the moment when the dissemination topology needs to be rebuilt. This work addresses such problem introducing the use of information fusion mechanisms, where the traffic is handled as a signal that is filtered and translated into evidences that indicate the likelihood of critical failures occurrence. These evidences are combined by a Dempster-Shafer engine to detect the need for a topology reconstruction. Our solution, called Diffuse, is evaluated through a set of simulations. We conclude that information fusion is a promising approach that can improve the performance of dissemination algorithms for wireless sensor networks by avoiding unnecessary traffic

A rate control video dissemination solution for extremely dynamic vehicular ad hoc networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Video dissemination to a group of vehicles is one of the many fundamental services envisioned for Vehicular Ad hoc Networks, especially as a building block for entertainment applications. For this purpose, in this paper we describe VoV, a video dissemination protocol that operates under extremely dynamic road traffic conditions. Contrary to most existing approaches that focus exclusively on always-connected networks and tackle the broadcast storm problem inherent to them, VoV is designed to operate under any kind of road traffic condition. We propose a new geographic-based broadcast suppression mechanism that gives a higher priority to rebroadcast to vehicles inside especial forwarding zones. Furthermore, vehicles store and carry received messages in a local buffer in order to forward them to vehicles that were not covered by the first dissemination process, probably as a result of collisions or intermittent disconnections. Finally, VoV employs a rate control mechanism that sets the pace at which messages must be transmitted according to the perceived network data traffic, thus avoiding channel overloading. Therefore, VoV adapts not only to the perceived road traffic condition, but also to the perceived channel quality. When compared to two related and well-accepted solutions ABSM and AID under Manhattan grid and real city scenarios, we show that, overall, our proposal is more efficient in terms of message delivery, delay and overhead. (C) 2015 Elsevier B.V. All rights reserved.Video dissemination to a group of vehicles is one of the many fundamental services envisioned for Vehicular Ad hoc Networks, especially as a building block for entertainment applications. For this purpose, in this paper we describe VoV, a video disseminat87318CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORFAPEMIG - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE MINAS GERAISFAPEAL - FUNDAÇÃO DE AMPARO À PESQUISA DO EConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)SEM INFORMAÇÃOSEM INFORMAÇÃOSEM INFORMAÇÃOSEM INFORMAÇÃ

Semi-Automatic Generation of Monitoring Applications for Wireless Networks

In this paper we present a new tool called BeanWatcher. This tool allows the semi-automatic generation of monitoring and management applications for wireless networks such as WLANs and WPANs. The architecture of the tool is based on a component model flexible enough to allow the creation of new components and the optimization of the components currently provided. BeanWatcher was designed to offer a development environment suitable for both expert and beginner users allowing them to choose the programming language that better fits the application requirements