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About

I am a post-doc researcher at HASLab, INESC TEC, working on Security in Computer Communications. Previously, I received my PhD in Informatics from University of Minho, Portugal, in 2016, MSc in Network Engineering and Communication Services from the same university in 2011 and BS from University Federal of Sergipe, Brazil, in 2008. My research interests include traffic measurements, classification and characterization, network security and wireless sensor networks. 

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Publications

2018

Qualification offer in EGOV competencies in PALOP-TL

Authors
Silva, JMC; Ramos, LFM; Fonte, V;

Publication
ACM International Conference Proceeding Series

Abstract
Information and Communications Technologies (ICT) have been successfully used in order to promote and pursue the goals of UN's 2030 Agenda for Sustainable Development. Meeting these goals, however, require significant efforts on public policy development, adequate planning and implementation, as well as qualified human resources working at every level of government, public administration and institutions. This paper presents a first quantitative analysis originated from Electronic Government-related training sessions that took place on all five Portuguese Speaking African Countries, and in Timor-Leste along 2017. The results focus on (i) the availability of higher education institutions offering courses related to EGOV on each of those countries; (ii) the qualification of the professionals attending those sessions; and (iii) how availability of local higher education courses translates into qualifications of local professionals serving at public administration level. This paper also discusses some perceptions gathered from the field, both from participants and lecturer teams, framing additional challenges that EGOV-related courses must take into account in those particular settings. It concludes by pointing out some of the works already taking place, which provides a deeper understanding of the workforce competencies in EGOV for each of those countries. © 2018 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

2017

Exploring SDN to deploy flexible sampling-based network monitoring

Authors
da Silva, CP; Lima, SR; Silva, JM;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
In recent years we witnessed the arrival of new trends, such as server virtualization and cloud services, an increasing number of mobile devices and online contents, leading the networking industry to deliberate about how traditional network architectures can be adapted or even deciding if a new perspective for them should be taken. SDN (Software-Defined Networking) emerged under this framing, opening a road for new developments due to the centralized logic control and view of the network, the decoupling of data and control planes, and the abstraction of the underlying network infrastructure from the applications. Although firstly oriented to packet switching, network measurements have also emerged as one promising field for SDN, as its flexibility enables programmable measurements, allowing a SDN controller to manage measurement tasks concurrently at multiple spatial and temporal scales. In this context, this paper is focused on exploring the SDN architecture and components for supporting the flexible selection and configuration of network monitoring tasks that rely on the use of traffic sampling. The aim is to take advantage of the integrated view of SDN controllers to apply and configure appropriate sampling techniques in network measurement points according to the requirements of specific measurement tasks. Through SDN, flexible and service-oriented configuration of network monitoring can be achieved, allowing also to improve the trade-off between accuracy and overhead of the monitoring process. In this way, this study, examining relevant SDN elements and solutions for deploying this monitoring paradigm, provides useful insights to enhance the programmability and efficiency of sampling-based network monitoring. © 2017, Springer International Publishing AG.

2017

LiteSense: An adaptive sensing scheme for WSNs

Authors
Silva, JMC; Bispo, KA; Carvalho, P; Lima, SR;

Publication
Proceedings - IEEE Symposium on Computers and Communications

Abstract
Adaptability and energy-efficient sensing are essential properties to sustain the easy deployment and lifetime of WSNs. These properties assume a stronger role in autonomous sensing environments where the application objectives or the parameters under measurement vary, and human intervention is not viable. In this context, this paper proposes LiteSense, a self-adaptive sampling scheme for WSNs, which aims at capturing accurately the behavior of the physical parameters of interest in each WSN context yet reducing the overhead in terms of sensing events and, consequently, the energy consumption. For this purpose, a set of low-complexity rules auto-regulates the sensing frequency depending on the observed parameter variation. Resorting to real environmental datasets, we provide statistical results showing the ability of LiteSense in reducing sensing activity and power consumption, while keeping the estimation accuracy of sensing events. © 2017 IEEE.

2017

Inside packet sampling techniques: exploring modularity to enhance network measurements

Authors
Silva, JMC; Carvalho, P; Lima, SR;

Publication
International Journal of Communication Systems

Abstract
Traffic sampling is viewed as a prominent strategy contributing to lightweight and scalable network measurements. Although multiple sampling techniques have been proposed and used to assist network engineering tasks, these techniques tend to address a single measurement purpose, without detailing the network overhead and computational costs involved. The lack of a modular approach when defining the components of traffic sampling techniques also makes difficult their analysis. Providing a modular view of sampling techniques and classifying their characteristics is, therefore, an important step to enlarge the sampling scope, improve the efficiency of measurement systems, and sustain forthcoming research in the area. Thus, this paper defines a taxonomy of traffic sampling techniques resorting to a comprehensive analysis of the inner components of existing proposals. After identifying granularity, selection scheme, and selection trigger as the main components differentiating sampling proposals, the study goes deeper on characterizing these components, including insights into their computational weight. Following this taxonomy, a general-purpose architecture is established to sustain the development of flexible sampling-based measurement systems. Traveling inside packet sampling techniques, this paper contributes to a clearer positioning and comparison of existing proposals, providing a road map to assist further research and deployments in the area. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

2017

A Modular Traffic Sampling Architecture: Bringing Versatility and Efficiency to Massive Traffic Analysis

Authors
Silva, JMC; Carvalho, P; Lima, SR;

Publication
Journal of Network and Systems Management

Abstract
The massive traffic volumes and heterogeneity of services in today’s networks urge for flexible, yet simple measurement solutions to assist network management tasks, without impairing network performance. To turn treatable tasks requiring traffic analysis, sampling the traffic has become mandatory, triggering substantial research in the area. Despite that, there is still a lack of an encompassing solution able to support the flexible deployment of sampling techniques in production networks, adequate to diverse traffic scenarios and measurement activities. In this context, this article proposes a modular traffic sampling architecture able to foster the flexible design and deployment of efficient measurement strategies. The architecture is composed of three layers—management plane, control plane and data plane—covering key components to achieve versatile and lightweight measurements in diverse traffic scenarios and measurement activities. Each component of the architecture is described considering the different strategies, technologies and protocols that compose the several stages of a measurement process. Following the proposed architecture, a sampling framework prototype has been developed, providing a fair environment to assess and compare sampling techniques under distinct measurement scenarios, evaluating their performance in balancing computational burden and accuracy. The results have demonstrated the relevance and applicability of the proposed architecture, revealing that a modular and configurable approach to sampling is a step forward for improving sampling scope and efficiency. © 2017 Springer Science+Business Media New York