Antonio A. F. Loureiro

Network partition-aware geographical data dissemination

Vehicular Ad hoc Networks (VANETs) have attracted the attention of the research community recently as they have opened up a myriad of on the road applications and increased their potential by providing accident-free and intelligent transport systems. The envisaged applications, as well as some inherent VANET characteristics make data dissemination an essential service and a challenging task in these networks. The existing solutions for data dissemination do not effectively address broadcast storm and network partition problems when considered together. To tackle these problems, we propose a novel GEographical Data Dissemination of Alert Information and Aware of Network Partition (GEDDAI-NP), which eliminates the broadcast storm and maximizes data dissemination capabilities across network partitions with short delays and low overhead. The simulation results show that the data dissemination performed by GEDDAI-NP provides better efficiency than other algorithms, outperforming them in different scenarios in all the evaluations carried out.

A framework based on small world features to design HSNs topologies with QoS

In this work we propose a framework based on the small world features to design Heterogeneous Sensor Network (HSN) topologies with QoS. The framework creates three different topologies and each topology has its goals related to the latency and energy consumption during data communication. We also propose a routing algorithm that uses the created topologies in order to provide QoS in HSN. Simulation results showed that the three topologies can provide different levels of QoS that can be used in many sensor network applications. We also compare our framework to the literature topology to provide QoS in HSN and our framework presents better tradeoff between energy consumption and latency during data communication.

On The Use Data Reduction Algorithms for Real-Time Wireless Sensor Networks

This work presents the design of real-time applications for wireless sensor networks (WSNs) by using an algorithm based on data stream to process the sensor data. The proposed algorithm is based on sampling techniques applied to data histograms created from original data streams acquired by sensor nodes. As a result, the algorithm provides a sample of log n items to represent the original data stream of n elements. In this work, we show how to use the data reduction algorithm in real-time WSN design.

TCP-ETX: A cross layer path metric for TCP optimization in wireless networks

Transmission Control Protocol (TCP) suffers degradation in wireless networks because, among other factors, low quality links tend to interrup a TCP connection. Most of the routing protocols use the number of hops as path metric without considering the link condition. Expected Transmission Count (ETX) calculates the estimated number of transmissions to successfully transmit a packet, but it fails to calculate the correct number of transmissions for a TCP segment. In addition, the overhead of ETX is very high because it needs to probe all destinations to calculate the link loss probability. In this paper, we propose a novel cross layer path metric, TCP-ETX, which calculates the accurate number of transmissions for TCP segments and minimizes the protocol overhead. To evaluate our proposal, we conduct simulations and compare our solution to existing protocols, which shows that our protocol can offer a significant improvement on the TCP performance.

Pervasive forwarding mechanism for mobile social networks

Abstract In recent years, we have witnessed an increase in the popularity of mobile wireless devices and networks, with greater attention devoted to feasibility of opportunistic computing, sensing, and communication. In Mobile Social Networks (MSNs), communication is provided by spatial proximity and social links between peers, where personal devices carried by users communicate directly in a device-to-device mode. On one hand, human mobility provides encounters between peers and opportunities for communication without additional infrastructure; on the other hand, it introduces intermittent connections, network partitions, and long delay, requiring sophisticated message-forwarding mechanisms to improve network performance. Therefore, socially-inspired approaches which consider network structure and personal user features have been proposed to cope with these challenges. However, many studies disregard adaptive policies of message forwarding capable of dealing with variations of these features. In this paper, we investigated message dissemination in MSNs considering external factors such as temperature and seasonal calendar as environmental features capable of model users’preferences and encounters. We evaluated the time of day, the day of the week, and environmental variables such as weather and geographic position as important factors to the collective behavior and spatiotemporal characteristics of urban scenarios. This paper presents an analysis of real data from weather and human mobility, which depict distinct social interactions and spatial features characterized by changes in thermal conditions. Thus, we propose a socially-aware forwarding mechanism that is adaptable to the seasonality of personal preferences. Our experiments indicated that pervasive data can provide useful information towards the design of the next generation of human-centered Opportunistic Networks.

Towards TCP optimization in wireless networks by a frame based cross layer routing metric

With the rapid development of wireless networks, the solution for degradation of Transmission Control Protocol (TCP) over wireless networks becomes more and more significant because of the software reusability. In order to improve the performance of TCP protocol, several studies have been proposed in different directions. Some of them attempt to find a suitable path for TCP transmission. Expected Transmission Count (ETX) is one of the most famous routing metrics to select a path with the least expected transmissions. However, ETX does not consider the Automatic Repeat Request (ARQ) mechanism in TCP, which generates extra transmissions. By modifying the ETX, we proposed a Frame-based TCP-ETX (FTCP-ETX), which calculates the expected frame transmissions for a TCP segment transmission. To evaluate our proposal, we conducted simulations by comparing FTCP-ETX, ETX and DSDV. Simulation results reveal that our routing metric improves TCP performance by selecting a better path.

Conflict Resolution in 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 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 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.