Enabling Design of Middleware for Massive Scale IOT-based Systems

Recently, the Internet of Things (IoT) technology has rapidly advanced to the stage where it is feasible to discover, locate and identify various smart sensors and devices based on the context, situation, characteristics, and relevancy to query for their data or control actions. Taking things a step further when developing Large Scale Applications requires that two serious issues be overcome. The first issue is to find a solution for data sensing and collection from a massive number of various ubiquitous devices when converging these into the next generation networks. The second important issue is to deal with the “Big Data” that arrive from a very large number of sources. This research emphasizes the need for finding a solution for a large scale data aggregation and delivery. The paper introduces biomimetic design methods for data aggregation in the context of large scale IoT-based systems

Hierarchical Routing in Low-Power Wireless Networks

Steen, M.R. van [Promotor

Design and prototyping of a network-enabled low-cost low-power seismic sensor monitoring system

Esta tese explora recentes desenvolvimentos em tecnologias de informação, comunicações e sensores no campo da sismologia. A tese aborda o potencial das redes de monitorização sísmica de elevada densidade na melhoria da resolução da actividade sísmica observada e, consequentemente, na melhor compreensão dos processos físicos que estão na base da ocorrência de terramotos. A tese argumenta que a tecnologia de sistemas de microelectromecânica (MEMS), usada na produção de acelerómetros de pequena dimensão, tem aplicabilidade e elevado potencial no domínio da sismologia. Acelerómetros MEMS já facilitaram a instalação de redes sísmicas de elevada densidade com superior resolução espacial pela Universidade da Califórnia (Rede Sísmica Comunitária) e pela Universidade de Évora (Rede Sísmica de Sensores do Alentejo), esta última ainda em fase de instalação. Neste contexto, a tese descreve o trabalho conduzido no desenho e desenvolvimento de sistemas de sensores baseados em acelerómetros MEMS. Este trabalho inclui a conceptualização de componentes de arquitectura usados para a implementação de quatro protótipos. Adicionalmente, foram também desenvolvidos os componentes necessários para a operação e gestão da rede de sensores, que inclui servidores dedicados a operar software especificamente desenvolvido neste trabalho. A tese descreve também a instalação e avaliação de protótipos, usando como base de comparação uma estação sísmica de elevado desempenho, recorrendo inclusivamente à actividade sísmica resultante de dois eventos sísmicos. A tese conclui que a arquitectura conceptualizada para o sistema sensor e para a rede de sensores demonstrou ser eficaz. Adicionalmente, embora a tecnologia MEMS seja promissora, ainda exibe limitações que limitam a sua aplicabilidade no domínio da sismologia, especificamente na observação de eventos sísmicos moderados e fortes. Conclui-se também que a instalação de acelerómetros MEMS em conjunto com sismómetros pode trazer benefícios na observação de actividade sísmica. Espera-se também que futuras gerações de acelerómetros MEMS possam ter uma adoção generalizada na sismologia; ABSTRACT: This thesis exploits advances in information technologies, communications and sensor systems to the field of seismology. It addresses the potential for high-density networks for seismic monitoring aiming to improve the resolution of the recorded seismic activity and, consequently, to improve the understanding of the physical processes that cause earthquakes, as well as to gather more detailed seismic characterisation of studied regions. It argues that microelectromechanical systems (MEMS) technology, used to produce small size accelerometers, has a potential application in seismology. Indeed, MEMS accelerometers have enabled the deployment of high-density seismic networks capable of monitoring seismic activity with high spatial resolution, such as CalTech's Community Seismic Network (CSN) and University of Évora’s SSN-Alentejo, currently in the deployment phase. In this context, this thesis describes the work conducted to design and develop low-cost seismic sensor systems, based on low-cost MEMS accelerometers. This work includes the conceptualisation of the architectural components that were implemented in four prototypes. Moreover, server-side components, necessary to operate and manage the sensor network, as well as to provide visualisation tools for users, are also developed and presented. This work also describes the field deployment and evaluation of selected prototypes, using a high-performance seismic station as the reference sensor for comparison, based on generated signals and two recorded seismic events. It is concluded that the herein conceptualised architecture for the high-dense network and sensor prototypes has been demonstrated to be effective. Moreover, albeit promising, MEMS accelerometers still exhibit performance limitations constraining their application in seismology addressing moderate and strong motion. In addition, MEMS accelerometers characteristics complement seismometers, thus installing MEMS accelerometers with seismometers, may provide additional insights concerning seismic activity and seismology in general. It is also expected that next generation MEMS accelerometers will be capable to compete with traditional seismometers, becoming the de facto technology in seismology

TOA Estimation of Chirp Signal in Dense Multipath Environment for Low-Cost Acoustic Ranging

In this paper, a novel time of arrival (TOA) estimation method is proposed based on an iterative cleaning process to extract the first path signal. The purpose is to address the challenge in dense multipath indoor environments that the power of the first path component is normally smaller than other multipath components, where the traditional match filtering (MF)-based TOA estimator causes huge errors. Along with parameter estimation, the proposed process is trying to detect and extract the first path component by eliminating the strongest multipath component using a band-elimination filter in fractional Fourier domain at each iterative procedure. To further improve the stability, a slack threshold and a strict threshold are introduced. Six simple and easily calculated termination criteria are proposed to monitor the iterative process. When the iterative 'cleaning' process is done, the outputs include the enhanced first path component and its estimated parameters. Based on these outputs, an optimal reference signal for the MF estimator can be constructed, and a more accurate TOA estimation can be conveniently obtained. The results from numerical simulations and experimental investigations verified that, for acoustic chirp signal TOA estimation, the accuracy of the proposed method is superior to those obtained by the conventional MF estimators

Web-based monitoring of gas emissions from landfill sites using autonomous sensing platforms

Executive Summary Numerous initiatives that are policy driven by national, European and global agencies target the preservation of our environment, human society’s health and our ecology. Ireland’s EPA 2020 Vision outlines a mandate to prepare for the unavoidable impact of climate change, the reduction of greenhouse gas (GHG) emissions, the control of air-emissions standards, the sustainable use of resources and the holding to account of those who flout environmental laws. These strategies are echoed in the Europe 2020: Resource-efficient Europe Flagship Initiative, which also advocates the creation of new opportunities for economic growth and greater innovation. The promotion of research and technical development is central to each of these strategies – specifically the achievement of accurate environmental monitoring technologies that will inform policy-makers and effect change. This is described in the EPA Strategic Plan 2013–2015 as the provision of ‘high quality, targeted and timely environmental data, information and assessment to inform decision making at all levels’. Specific to landfills, the Environmental Protection Agency’s (EPA) Focus on Landfilling in Ireland stipulates the management of landfill gas to eliminate environmental harm and public nuisance, to promote energy generation where possible and to avoid liabilities in site closure and aftercare. It was in this context that the EPA STRIVE programme granted funding for this research project on developing autonomous sensor platforms for the real-time monitoring of gases generated in landfill facilities. Managing landfill gas is one of the crucial operations in a landfill facility, where gases (primarily methane [CH4] and carbon dioxide [CO2] generated from the decomposition of biodegradable waste) are extracted and combusted in a flare or preferably an engine (as biogas fuel). These gases, classified as greenhouse gases (GHGs), also pose localised hazards due to fire risk and asphyxiation, and are indicative of odorous nuisance compounds. Gas-monitoring on site is conducted to (i) ensure against gas migration into the local environment and to (ii) maintain the thorough gas extraction and optimum composition for combustion. This is becoming more relevant because of the numerous landfill closures brought by Europe-wide changes in waste-management policy. Even for landfills no longer actively receiving waste, substantial gas generation remains ongoing for years and even decades. Despite diminished financial resources and reduced manpower, management of this gas must be maintained. Traditionally, monitoring involves taking manual measurements using expensive handheld equipment and requiring laborious travel over difficult and expansive terrain. Consequently, it is conducted relatively infrequently – typically once a month. These issues can be addressed by adopting distributed continuous monitoring systems. These low-cost remotely deployable sensor platforms offer a valuable complementary service to operators and the EPA. They enable easier adherence to their licence criteria, the prevention of expensive remediation measures and the potential boost in revenue from increasing energy production through the use of biogas. Challenges arise in terms of achieving a long-term monitoring performance in a harsh environment while maintaining accuracy, reliability and cost-effectiveness. To meet these challenges, this project developed cost- effective autonomous sensor platforms to allow long- term continuous monitoring of gas composition (methane and carbon dioxide) and extraction pressure. The project’s work represents one of the only developments of autonomous sensor technology in this space; the few other market alternatives tend to be expensive or difficult to implement for remotely deployable continuous monitoring. Beyond the development of a platform technology, the challenge was to apply this technology to the adverse environmental conditions. The project delivered a total of 14 autonomous sensor platforms in deployments involving Irish landfill sites, a Scottish landfill site and a Brazilian wastewater treatment plant. The analysis and interpretation of acquired data, coupled with local meteorological data and on-site operational data, provided the translation from raw environmental data to meaningful conclusions that could inform decision-making. This report presents a number of case studies to illustrate this. Characteristics of site gas dynamics could be identified; for example, it was possible to show if excessive gas concentrations in a perimeter well could be resolved by increasing the flare extraction rate for a particular well. Furthermore, the potential for quantifying methane generation potential at distributed locations within the landfill was identified in addition to diagnosing the effectiveness of the extraction network – hence aiding in field-balancing and landfill gas utilisation. The extensive wealth of data enabled by this platform technology will help better-informed decision-making and improve operational practices in managing gas emissions. In landfills, this signifies alleviating gas migration with perimeter monitoring and enhancing flare/ engine operation by evaluating gas quality at distributed locations within the gas field. While landfilling is becoming outmoded as a waste-management process, the need for continuous monitoring will be relevant for many years to come. Indeed, a number of existing facilities are considering retrofitting engines because of the significant potential for additional landfill gas utilisation being identified by Sustainable Energy Authority Ireland in 2010. Furthermore, the technology’s low-cost and autonomous nature would benefit the hundreds of historical and legacy landfills if any were deemed to be problematic in terms of their environmental impact. Beyond landfills, this work pertains to other applications within the waste sector, as demonstrated by measuring emissions from wastewater treatment plant lagoons. With some further development, this technology could apply to efforts in dealing with climate change (e.g. in evaluating GHG inventories), where applications include managed peatlands (one case study is presented in this report and future efforts could also be targeted at carbon sinks/storage) and agriculture (Ireland’s greatest contributor to GHGs). Further scope could also be pursued in air-quality monitoring, particularly relevant at present with 2013 being dubbed the ‘Year of Air’ by European leaders. Throughout this project, the commercial prospect of this technology was affirmed with positive feedback from landfill operators, environmental regulators and private consultancies. Continual technical developments and refinements in mechanical/electronic design delivered a platform with expanded functionality and reduced price-point, thus becoming more viable for scaled-up deployments and commercial feasibility. Ultimately, this innovative development shows good promise as a high-potential commercial venture, with this work continuing under Enterprise Ireland’s Commercialisation Fund

Secure Data Management and Transmission Infrastructure for the Future Smart Grid

Power grid has played a crucial role since its inception in the Industrial Age. It has evolved from a wide network supplying energy for incorporated multiple areas to the largest cyber-physical system. Its security and reliability are crucial to any country’s economy and stability [1]. With the emergence of the new technologies and the growing pressure of the global warming, the aging power grid can no longer meet the requirements of the modern industry, which leads to the proposal of ‘smart grid’. In smart grid, both electricity and control information communicate in a massively distributed power network. It is essential for smart grid to deliver real-time data by communication network. By using smart meter, AMI can measure energy consumption, monitor loads, collect data and forward information to collectors. Smart grid is an intelligent network consists of many technologies in not only power but also information, telecommunications and control. The most famous structure of smart grid is the three-layer structure. It divides smart grid into three different layers, each layer has its own duty. All these three layers work together, providing us a smart grid that monitor and optimize the operations of all functional units from power generation to all the end-customers [2]. To enhance the security level of future smart grid, deploying a high secure level data transmission scheme on critical nodes is an effective and practical approach. A critical node is a communication node in a cyber-physical network which can be developed to meet certain requirements. It also has firewalls and capability of intrusion detection, so it is useful for a time-critical network system, in other words, it is suitable for future smart grid. The deployment of such a scheme can be tricky regarding to different network topologies. A simple and general way is to install it on every node in the network, that is to say all nodes in this network are critical nodes, but this way takes time, energy and money. Obviously, it is not the best way to do so. Thus, we propose a multi-objective evolutionary algorithm for the searching of critical nodes. A new scheme should be proposed for smart grid. Also, an optimal planning in power grid for embedding large system can effectively ensure every power station and substation to operate safely and detect anomalies in time. Using such a new method is a reliable method to meet increasing security challenges. The evolutionary frame helps in getting optimum without calculating the gradient of the objective function. In the meanwhile, a means of decomposition is useful for exploring solutions evenly in decision space. Furthermore, constraints handling technologies can place critical nodes on optimal locations so as to enhance system security even with several constraints of limited resources and/or hardware. The high-quality experimental results have validated the efficiency and applicability of the proposed approach. It has good reason to believe that the new algorithm has a promising space over the real-world multi-objective optimization problems extracted from power grid security domain. In this thesis, a cloud-based information infrastructure is proposed to deal with the big data storage and computation problems for the future smart grid, some challenges and limitations are addressed, and a new secure data management and transmission strategy regarding increasing security challenges of future smart grid are given as well

Secure Data Management and Transmission Infrastructure for the Future Smart Grid

Power grid has played a crucial role since its inception in the Industrial Age. It has evolved from a wide network supplying energy for incorporated multiple areas to the largest cyber-physical system. Its security and reliability are crucial to any country’s economy and stability [1]. With the emergence of the new technologies and the growing pressure of the global warming, the aging power grid can no longer meet the requirements of the modern industry, which leads to the proposal of ‘smart grid’. In smart grid, both electricity and control information communicate in a massively distributed power network. It is essential for smart grid to deliver real-time data by communication network. By using smart meter, AMI can measure energy consumption, monitor loads, collect data and forward information to collectors. Smart grid is an intelligent network consists of many technologies in not only power but also information, telecommunications and control. The most famous structure of smart grid is the three-layer structure. It divides smart grid into three different layers, each layer has its own duty. All these three layers work together, providing us a smart grid that monitor and optimize the operations of all functional units from power generation to all the end-customers [2]. To enhance the security level of future smart grid, deploying a high secure level data transmission scheme on critical nodes is an effective and practical approach. A critical node is a communication node in a cyber-physical network which can be developed to meet certain requirements. It also has firewalls and capability of intrusion detection, so it is useful for a time-critical network system, in other words, it is suitable for future smart grid. The deployment of such a scheme can be tricky regarding to different network topologies. A simple and general way is to install it on every node in the network, that is to say all nodes in this network are critical nodes, but this way takes time, energy and money. Obviously, it is not the best way to do so. Thus, we propose a multi-objective evolutionary algorithm for the searching of critical nodes. A new scheme should be proposed for smart grid. Also, an optimal planning in power grid for embedding large system can effectively ensure every power station and substation to operate safely and detect anomalies in time. Using such a new method is a reliable method to meet increasing security challenges. The evolutionary frame helps in getting optimum without calculating the gradient of the objective function. In the meanwhile, a means of decomposition is useful for exploring solutions evenly in decision space. Furthermore, constraints handling technologies can place critical nodes on optimal locations so as to enhance system security even with several constraints of limited resources and/or hardware. The high-quality experimental results have validated the efficiency and applicability of the proposed approach. It has good reason to believe that the new algorithm has a promising space over the real-world multi-objective optimization problems extracted from power grid security domain. In this thesis, a cloud-based information infrastructure is proposed to deal with the big data storage and computation problems for the future smart grid, some challenges and limitations are addressed, and a new secure data management and transmission strategy regarding increasing security challenges of future smart grid are given as well

A survey on MAC-based physical layer security over wireless sensor network

Physical layer security for wireless sensor networks (WSNs) is a laborious and highly critical issue in the world. Wireless sensor networks have great importance in civil and military fields or applications. Security of data/information through wireless medium remains a challenge. The data that we transmit wirelessly has increased the speed of transmission rate. In physical layer security, the data transfer between source and destination is not confidential, and thus the user has privacy issues, which is why improving the security of wireless sensor networks is a prime concern. The loss of physical security causes a great threat to a network. We have various techniques to resolve these issues, such as interference, noise, fading in the communications, etc. In this paper we have surveyed the different parameters of a security design model to highlight the vulnerabilities. Further we have discussed the various attacks on different layers of the TCP/IP model along with their mitigation techniques. We also elaborated on the applications of WSNs in healthcare, military information integration, oil and gas. Finally, we have proposed a solution to enhance the security of WSNs by adopting the alpha method and handshake mechanism with encryption and decryption