An Evaluation of a Conservative Transmit Power Control Mechanism on an Indoor 802.11 Wireless Mesh Testbed

Power control techniques for IEEE 802.11 wireless networks have already gained considerable attention. Such techniques are particularly attractive because they can improve various aspects of wireless network operation such as interference mitigation, spatial reuse in dense wireless deployments, topology control, and link quality enhancement. In this paper we propose a novel delivery ration based Conservative Transmit Power Control (ConTPC) mechanism. Our implementation is conservative when it comes to deciding if the transmit power should be reduced for a given link. This is because we do not want poor quality wireless links to further reduce their quality and be overwhelmed by other links transmitting at maximum power. We have experimentally evaluated the benefit of the proposed power control scheme when compared with fixed power level systems. We show that our ConTPC mechanism can increase the throughput, however the magnitude of this enhancement largely depends on the topology of the wireless network

Using SWE Standards for Ubiquitous Environmental Sensing: A Performance Analysis

Although smartphone applications represent the most typical data consumer tool from the citizen perspective in environmental applications, they can also be used for in-situ data collection and production in varied scenarios, such as geological sciences and biodiversity. The use of standard protocols, such as SWE, to exchange information between smartphones and sensor infrastructures brings benefits such as interoperability and scalability, but their reliance on XML is a potential problem when large volumes of data are transferred, due to limited bandwidth and processing capabilities on mobile phones. In this article we present a performance analysis about the use of SWE standards in smartphone applications to consume and produce environmental sensor data, analysing to what extent the performance problems related to XML can be alleviated by using alternative uncompressed and compressed formats

Enterprise 2.0 em Portugal

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de InformaçãoConsiderado um conjunto de ferramentas e tecnologias colaborativas, a Web 2.0 é definida como uma nova plataforma de fácil acesso e utilização, que permite a partilha de informação entre pessoas e organizações, e onde o utilizador apresenta um novo papel, mais colaborativo, interactivo e importante, na passagem de conhecimento. Na literatura ainda parecem existir algumas dúvidas sobre o termo Web 2.0, se representa uma nova versão da Web ou se é apenas uma manobra de marketing para reposicionar um conjunto de funcionalidades que já existiam, mas que juntas apresentam outro valor. Ao nível organizacional, o conceito utilizado para a adopção e utilização de tecnologias e ferramentas Web 2.0 é Enterprise 2.0, tendo algumas empresas já percebido os benefícios associados à sua integração, outras ainda não.Devida à lacuna existente de estudos realizados em Portugal, e dada a importância que se tem vindo a dar em surveys e estudos de caso realizados ao nível mundial, não se poderia deixar de analisar a experiência portuguesa, com o objectivo de se perceber quais as ferramentas adoptadas, as razões dessa adopção e se existem benefícios. É ainda importante perceber em que fase se encontram na adopção de ferramentas Web 2.0, bem como incentivar outras empresas a entrar no mundo 2.0

Improving Multicast Communications Over Wireless Mesh Networks

In wireless mesh networks (WMNs) the traditional approach to shortest path tree based multicasting is to cater for the needs of the poorest performingnode i.e. the maximum permitted multicast line rate is limited to the lowest line rate used by the individual Child nodes on a branch. In general, this meansfixing the line rate to its minimum value and fixing the transmit power to its maximum permitted value. This simplistic approach of applying a single multicast rate for all nodes in the multicast group results in a sub-optimal trade-off between the mean network throughput and coverage area that does not allow for high bandwidth multimedia applications to be supported. By relaxing this constraint and allowing multiple line rates to be used, the mean network throughput can be improved. This thesis presents two methods that aim to increase the mean network throughput through the use of multiple line rates by the forwarding nodes. This is achieved by identifying the Child nodes responsible for reducing the multicast group rate. The first method identifies specific locations for the placement of relay nodes which allows for higher multicast branch line rates to be used. The second method uses a power control algorithm to tune the transmit power to allow for higher multicast branch line rates. The use of power control also helps to reduce the interference caused to neighbouring nodes.Through extensive computer simulation it can be shown that these two methods can lead to a four-fold gain in the mean network throughput undertypical WMN operating conditions compared with the single line rate case

Simulação de sistemas energéticos isolados: Ilha de Santiago

Mestrado em Engenharia MecânicaA ilha de Santiago é a maior ilha de Cabo Verde com cerca de 50% da população do país. Tem enfrentado, de uma forma contínua, sérios problemas com a falta de capacidade para suprir a procura de energia elétrica devido a questões técnicas, financeiras e estruturais. Este trabalho tem o objetivo principal de efetuar uma análise comparativa em termos económicos e ambientais entre duas hipóteses para a expansão do sistema de geração de eletricidade da ilha a médio-longo prazo (2030): um cenário que engloba a evolução do sistema sob o paradigma da produção centralizada de energia; e um outro cenário onde o aumento de capacidade instalada será efetuado apostando na descentralização dos sistemas de produção. Para facilitar o processo de planeamento energético existem diversas variedades de ferramentas e base de dados disponíveis para apoiar diferentes aspetos da análise energética que funcionam como sistema/ferramenta de apoio à decisão no planeamento energético (METAXIOTIS, 2009). Para uma melhor compreensão dessas ferramentas efetuou-se a caracterização e classificação dos conceitos subjacentes, das metodologias, dos dados necessários, dos âmbitos da aplicação e das capacidades analíticas bem como a caracterização e exemplificação dos diferentes softwares existentes. No desenvolvimento deste trabalho foram utilizados dois softwares/ferramentas de modelação energética, LEAP e HOMER. O primeiro serviu para criar o modelo energético da ilha de Santiago e efetuar a análise de cenários; o segundo foi usado para otimizar o sistema de microprodução numa casa típica da ilha, sendo esta informação depois importada para o LEAP. Do estudo concluiu-se que as energias renováveis têm um impacto fundamental no futuro sistema elétrico da ilha de Santiago, principalmente no que diz respeito a redução do custo da produção de eletricidade, dependência energética e impactos ambientais. Das duas hipóteses de expansão do sistema geração de geração de eletricidade analisadas, o sistema de geração descentralizada revelou ser a melhor opção. Em 2020, relativamente ao custo, com 50% de energias renováveis, poupa-se 620 milhões de euros com o benefício da redução de dependência do setor elétrico e possibilidade de acumular até 2030 85 milhões de euros em certificados de emissões de carbono.Santiago is the biggest island of Cape Verde with about half of country population. The island has been facing serious and continuous difficulties in overcoming the lack of resources to satisfy the electric power demand due to technical, financial and structural issues. The main objective of this work is to perform a medium long term (2030) economic and environmental analysis of two alternatives of Santiago Island electric system development: On the first scenario, increase of electric energy demand will be supplied with centralized energy production; and on the second scenario the electric energy demand will be supplied by distributed energy production. In order to facilitate the energy planning process there is a variety of tools and database available to sustain different aspects of the energetic analyses working as a decision support system (METAXIOTIS, 2009). It was done the characterization and classification of the underlying concepts, methodologies, required data, application scope and analytic capability for a better understanding of those tools as well as the characterization of the existing modeling tools. Two energy planning tools were used in this work, LEAP and HOMER. The first one was used to create Santiago Island energy model and for energy scenario analyses. The second one was used to optimize the micro production system in Santiago typical house. The optimization results are then imported into LEAP model. Analysis shows that the renewable energy plays a great role on the future of Santiago electric system, mainly at cost production, energy, energy security/dependency and environmental impacts. It was found that distributed energy generation is the best alternative. In 2020, with 50% of renewable energy penetration, it can be saved 620 million Euros with the benefit of reduction of electric sector dependency on fossil fuels. And there is an opportunity of CO2 certificate trade up to 85 million Euros in 2030

A Novel SNR Estimation Technique for OFDM Systems

Orthogonal Frequency Division Multiplexing (OFDM) systems have received a lot of attention because of their robust performance in frequency dispersive channels. Further performance improvement is achieved by employing more sophisticated receiver techniques that often require the knowledge of signal-to-noise ratio (SNR) - broadly defined as the ratio of the desired signal power to the unwanted noise power. For example, noise variance and, hence, signal to noise ratio (SNR) estimates of the received signal are very important for the channel quality control in communication systems. Similarly, in advanced communication systems, SNR estimation is used for adaptive algorithms for modulation, power control and coding. The objective of the work undertaken in this thesis is to design a front-end noise power estimator and, thence, SNR estimator. The proposed SNR estimator utilizes the OFDM preamble signal - the preamble used for synchronization. The estimation is achieved by auto correlating the preamble and it is deployed right at the front-end of the receiver. Noise power and, hence, signal power is estimated from the correlation results. The technique is also extended to obtaining noise power estimates of colored noise using wavelet-packet based filter bank analysis of the noise. In order to benchmark the proposed noise power and SNR estimation technique, a complete end-to-end fixed-broadband-wireless-access-system (IEEE 802.16d) simulation has been developed and the results are compared with other works reported in the literature. The simulations are conducted in both frequency non-dispersive and dispersive channels with real additive white Gaussian noise (A WGN) and also colored noise. It is observed that the proposed estimator gives better SNR estimates. The proposed estimator is also checked with WiMAX systems (IEEE802.\6d, 2004) using SUI multipath channels and with Wi-Fi systems (IEEE802.11 a) with indoor channel models. The estimator performs SNR estimation at front-end of the receiver unlike all other estimators which perform SNR estimation at back-end of the receiver. Furthermore, the proposed estimator has relatively low computational complexity; for it makes use of only one OFDM preamble signal to find the SNR estimates. The criteria of good SNR estimator are accuracy of estimates, low complexity and easy to implement. The results show that the proposed estimator fulfills these criteria successfully

ICE-B 2010:proceedings of the International Conference on e-Business

The International Conference on e-Business, ICE-B 2010, aims at bringing together researchers and practitioners who are interested in e-Business technology and its current applications. The mentioned technology relates not only to more low-level technological issues, such as technology platforms and web services, but also to some higher-level issues, such as context awareness and enterprise models, and also the peculiarities of different possible applications of such technology. These are all areas of theoretical and practical importance within the broad scope of e-Business, whose growing importance can be seen from the increasing interest of the IT research community. The areas of the current conference are: (i) e-Business applications; (ii) Enterprise engineering; (iii) Mobility; (iv) Business collaboration and e-Services; (v) Technology platforms. Contributions vary from research-driven to being more practical oriented, reflecting innovative results in the mentioned areas. ICE-B 2010 received 66 submissions, of which 9% were accepted as full papers. Additionally, 27% were presented as short papers and 17% as posters. All papers presented at the conference venue were included in the SciTePress Digital Library. Revised best papers are published by Springer-Verlag in a CCIS Series book

Analyzing Enterprise WiFi Session Data for Modeling Building Occupancy, Evacuation, and Energy Consumption

Buildings are the prime components of office complexes, university campuses, and city centers. They are expensive to build and expensive to operate. Building managers are under constant pressure to keep them efficient and safe. However, they are often stymied by lack of fine-grained data that can help them optimize occupancy levels so as to make most efficient use of space, evacuation patterns that can ensure safety in the event of emergencies, and energy usage behavior that can help reduce operating costs. While several modern buildings are increasingly being equipped with sensors for detecting people presence, movement patterns, and thermal conditions, such instrumentation can often be expensive and limited in scale. This thesis investigates the potential to use data generated by the pervasive WiFi infrastructure that is present in all buildings. Specifically, we evaluate the use of WiFi data to model room usage, anatomize emergency evacuations, and reduce energy excursion costs associated with evacuation events. We begin this thesis by surveying data-driven approaches for efficient building operation and management, while reviewing existing technologies for measuring occupancy using both existing and purpose-built sensing infrastructure. Central to this thesis is the data we have collected and analyzed on WiFi session logs from a dense wireless network consisting of nearly 5000 access points across 50 buildings in a large university campus over a period of 2 years. For our first contribution, we use this data to develop a machine learning-based method to estimate classroom occupancy in near real-time. The output of our method is compared to that from specialized people-counting sensors, and the symmetric Mean Absolute Percentage Error is no more than 13%. Our second contribution develops a systematic method to evaluate emergency evacuation events using building WiFi session data. Our systematic analysis of 43 planned and unplanned evacuation events across 14 buildings quantifies important measures such as evacuation speed, number of evacuees, and typicality of occupancy levels, demonstrating that WiFi data enables accurate and scalable evaluation of building evacuations, corroborating current manual records and revealing new insights. For our third and final contribution, we show that evacuations (particularly during summer) can result in HVAC power excursions of up to 150% above the agreed threshold, imposing heavy power tariffs. We develop a cooling strategy that allows the power cost to be traded off against thermal comfort of occupants post evacuation in a tunable manner. Application of our algorithm to typical building evacuation scenarios shows that the power excursion costs can be largely mitigated for as little as 5 minutes of delay in achieving ideal indoor temperatures. Taken together, our contributions equip building operators with tools and techniques to improve efficiency and safety by leveraging existing WiFi data with no additional infrastructure costs

On the detection of privacy and security anomalies

Data analytics over generated personal data has the potential to derive meaningful insights to enable clarity of trends and predictions, for instance, disease outbreak prediction as well as it allows for data-driven decision making for contemporary organisations. Predominantly, the collected personal data is managed, stored, and accessed using a Database Management System (DBMS) by insiders as employees of an organisation. One of the data security and privacy concerns is of insider threats, where legitimate users of the system abuse the access privileges they hold. Insider threats come in two flavours; one is an insider threat to data security (security attacks), and the other is an insider threat to data privacy (privacy attacks). The insider threat to data security means that an insider steals or leaks sensitive personal information. The insider threat to data privacy is when the insider maliciously access information resulting in the violation of an individual’s privacy, for instance, browsing through customers bank account balances or attempting to narrow down to re-identify an individual who has the highest salary. Much past work has been done on detecting security attacks by insiders using behavioural-based anomaly detection approaches. This dissertation looks at to what extent these kinds of techniques can be used to detect privacy attacks by insiders. The dissertation proposes approaches for modelling insider querying behaviour by considering sequence and frequency-based correlations in order to identify anomalous correlations between SQL queries in the querying behaviour of a malicious insider. A behavioural-based anomaly detection using an n-gram based approach is proposed that considers sequences of SQL queries to model querying behaviour. The results demonstrate the effectiveness of detecting malicious insiders accesses to the DBMS as anomalies, based on query correlations. This dissertation looks at the modelling of normative behaviour from a DBMS perspective and proposes a record/DBMS-oriented approach by considering frequency-based correlations to detect potentially malicious insiders accesses as anomalies. Additionally, the dissertation investigates modelling of malicious insider SQL querying behaviour as rare behaviour by considering sequence and frequency-based correlations using (frequent and rare) item-sets mining. This dissertation proposes the notion of ‘Privacy-Anomaly Detection’ and considers the question whether behavioural-based anomaly detection approaches can have a privacy semantic interpretation and whether the detected anomalies can be related to the conventional (formal) definitions of privacy semantics such as k-anonymity and the discrimination rate privacy metric. The dissertation considers privacy attacks (violations of formal privacy definition) based on a sequence of SQL queries (query correlations). It is shown that interactive querying settings are vulnerable to privacy attacks based on query correlation. Whether these types of privacy attacks can potentially manifest themselves as anomalies, specifically as privacy-anomalies, is investigated. One result is that privacy attacks (violation of formal privacy definition) can be detected as privacy-anomalies by applying behavioural-based anomaly detection using n-gram over the logs of interactive querying mechanisms