Arlindo F. da Conceição

Is IEEE 802.11 ready for VoIP

In this paper, we empirically explore voice communication over IEEE 802.11 networks (VoWiFi). The objective is to understand the limitations of the current WiFi network for VoWiFi deployment. Our experiment finds two major problems of VoWiFi: unstable and excessively long handoffs and unpredictable occurrence of bursts. We also discuss several other minor factors that could hinder VoWiFi deployment, such as network capacity, fairness, and interference susceptibility. Finally, we describe the scenarios where VoWiFi could be used. We conclude that VoWiFi is feasible if used moderately, with low mobility and good signal strength

Acc-Motif: accelerated network motif detection

Network motif algorithms have been a topic of research mainly after the 2002-seminal paper from Milo et al. [1], which provided motifs as a way to uncover the basic building blocks of most networks. Motifs have been mainly applied in Bioinformatics, regarding gene regulation networks. Motif detection is based on induced subgraph counting. This paper proposes an algorithm to count subgraphs of size k + 2 based on the set of induced subgraphs of size k. The general technique was applied to detect 3, 4 and 5-sized motifs in directed graphs. Such algorithms have time complexity O(a(G)m), O(m2) and O(nm2), respectively, where a(G) is the arboricity of G(V, E). The computational experiments in public data sets show that the proposed technique was one order of magnitude faster than Kavosh and FANMOD. When compared to NetMODE, acc-Motif had a slightly improved performance.

Accelerated Motif Detection Using Combinatorial Techniques

Network motif algorithms have been a topic of research mainly after the 2002-seminal paper from Milo et al, that provided motifs as a way to uncover the basic building blocks of most networks. This article proposes new algorithms to exactly count isomorphic pattern motifs of size 3 and 4 in directed graphs. The algorithms are accelerated by combinatorial techniques. Let G(V, E) be a directed graph with m=|E|. We describe an O(m√m) time complexity algorithm to count isomorphic patterns of size 3. To counting isomorphic patterns of size 4, we propose an O(m2) algorithm. The new algorithms were implemented and compared with Fanmod motif detection tool. The experiments show that our algorithms are expressively faster than Fanmod. We also let our tool to detect motifs, the ACC-MOTIF, available in the Internet.

Voice transmission over IEEE 802.11 networks: main issues and restrictions

This work analyzes the voice communication over IEEE 802.11 networks (VoWiFi). It empirically characterizes the transmission problems of VoWiFi and describes scenarios where it could be used over the existing network technologies. The two major problems found were: the excessively long handoffs and the occurrence of bursts. We conclude that is feasible to use VoWiFi if, during a voice call, mobility is kept low, signal strength is high enough and the network capacity is not exceeded.Este trabalho faz uma avaliação da comunicação de voz sobre redes IEEE 802.11 (VoWiFi). Para isto, caracteriza empiricamente os problemas de transmissão e aponta cen´rios em que a implantação de VoWiFi é vi´vel utilizando-se as tecnologias atualmente disponĩveis. Os dois principais problemas encontrados foram: a longa duração das migrações (handoffs) e a ocorrência de tr´fegos em rajada. Concluĩmos que, com as tecnologias atuais, a utilização de VoWiFi é vi´vel desde que, durante uma chamada, a mobilidade seja baixa, a qualidade do sinal seja suficientemente alta e que a capacidade de transmissão da rede não seja excedida.

A framework for building language interpreters

This work presents an Object-Oriented framework for the implementation of language interpreters in an educational context. We use this framework to implement different programming language paradigms, including interpreters for the Functional, Object-Oriented and Logic paradigms. This framework focuses its structure on aiding the comprehension of the similarities and differences between the implementation of different paradigms.

Empowering Mobile Users: Create Your Own Mobile Application for Data Collection in the Cloud

This paper presents a cloud infrastructure that allows users to create mobile applications to collect and visualize data. The system offers simple and intuitive interfaces to create Apps, without the need for any programming skill to develop them. The platform allows the collection of conventional data, such as numbers and text, and also non-conventional data, such as multimedia files, location information, barcodes, etc. The collected data can be shared among users on a social network, allowing Apps to extract intelligence from the collected data. The system is based on free software and can be accessed at the following address: http://maritaca.unifesp.br .

Pytos: A Framework for Mobile Computation Offloading in Python

Cloud-based offloading may improve mobile application performance and reduce energy consumption by migrating mobile code execution to the cloud. Nevertheless, it is not always the best bet, because of the high WAN delay. This article presents Pytos, a framework for Python, that allows code migration to the network edge (cloudlet), mitigating latency limitations. Pytos provides a transparent offloading mechanism to end users, hence the system discovers available cloudlets in the network automatically. To developers, Pytos provides a simple programming model at method-level granularity. Empirical evaluation showed that Pytos may improve performance and energy consumption up to 20 times.

Pipeline architecture for mobile data analysis

This paper presents a cloud architecture that allows collecting and analyzing mobile data. The system offers simple and intuitive interfaces to create mobile applications (Apps), without the need for any programming skill to develop them. The platform allows the collection of conventional data, such as numbers and text, and also non-conventional data, such as multimedia files, location information, and barcodes. The collected data can be shared among users on a social network. In addition, we propose a pipeline architecture to data analyzing.