A layer 2 multipath fabric using a centralized controller

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Evaluation and optimization of a session-based middleware for data management

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A distributed platform for the volunteer execution of workflows on a local area network

Thesis submitted in fulfilment of the requirements for the Degree of Master of Science in Computer Science

The implementation of an Enterprise Geographical Information System to support Cadastre and Expropriation activities.

The processes of mobilization of land for infrastructures of public and private domain are developed according to proper legal frameworks and systematically confronted with the impoverished national situation as regards the cadastral identification and regularization, which leads to big inefficiencies, sometimes with very negative impact to the overall effectiveness. This project report describes Ferbritas Cadastre Information System (FBSIC) project and tools, which in conjunction with other applications, allow managing the entire life-cycle of Land Acquisition and Cadastre, including support to field activities with the integration of information collected in the field, the development of multi-criteria analysis information, monitoring all information in the exploration stage, and the automated generation of outputs. The benefits are evident at the level of operational efficiency, including tools that enable process integration and standardization of procedures, facilitate analysis and quality control and maximize performance in the acquisition, maintenance and management of registration information and expropriation (expropriation projects). Therefore, the implemented system achieves levels of robustness, comprehensiveness, openness, scalability and reliability suitable for a structural platform. The resultant solution, FBSIC, is a fit-for-purpose cadastre information system rooted in the field of railway infrastructures. FBSIC integrating nature of allows: to accomplish present needs and scale to meet future services; to collect, maintain, manage and share all information in one common platform, and transform it into knowledge; to relate with other platforms; to increase accuracy and productivity of business processes related with land property management.

Novel Cryopreservation Strategies for Cell‐Therapies and Pre‐Clinical Research

The expanding need for complex biologics for therapeutic applications, in‐vitro pharmacology and toxicology studies and fundamental research demands the production of banks of well‐characterized and safety‐tested stocks of a large number of cell/tissue samples. This implies the development of effective cryopreservation methodologies that can cope with process scalability and automation and must reflect the biological and physical properties of the cells as these can be significantly altered by the process.

Botnet cluster identification

Botnets are a group of computers infected with a specific sub-set of a malware family and controlled by one individual, called botmaster. This kind of networks are used not only, but also for virtual extorsion, spam campaigns and identity theft. They implement different types of evasion techniques that make it harder for one to group and detect botnet traffic. This thesis introduces one methodology, called CONDENSER, that outputs clusters through a self-organizing map and that identify domain names generated by an unknown pseudo-random seed that is known by the botnet herder(s). Aditionally DNS Crawler is proposed, this system saves historic DNS data for fast-flux and double fastflux detection, and is used to identify live C&Cs IPs used by real botnets. A program, called CHEWER, was developed to automate the calculation of the SVM parameters and features that better perform against the available domain names associated with DGAs. CONDENSER and DNS Crawler were developed with scalability in mind so the detection of fast-flux and double fast-flux networks become faster. We used a SVM for the DGA classififer, selecting a total of 11 attributes and achieving a Precision of 77,9% and a F-Measure of 83,2%. The feature selection method identified the 3 most significant attributes of the total set of attributes. For clustering, a Self-Organizing Map was used on a total of 81 attributes. The conclusions of this thesis were accepted in Botconf through a submited article. Botconf is known conferênce for research, mitigation and discovery of botnets tailled for the industry, where is presented current work and research. This conference is known for having security and anti-virus companies, law enforcement agencies and researchers.

AGNI: an API for the control of automomous service robots

With the continuum growth of Internet connected devices, the scalability of the protocols used for communication between them is facing a new set of challenges. In robotics these communications protocols are an essential element, and must be able to accomplish with the desired communication. In a context of a multi-­‐‑agent platform, the main types of Internet communication protocols used in robotics, mission planning and task allocation problems will be revised. It will be defined how to represent a message and how to cope with their transport between devices in a distributed environment, reviewing all the layers of the messaging process. A review of the ROS platform is also presented with the intent of integrating the already existing communication protocols with the ServRobot, a mobile autonomous robot, and the DVA, a distributed autonomous surveillance system. This is done with the objective of assigning missions to ServRobot in a security context.

Development of 3D in vitro models for prediction of hepatic metabolism and toxicity

The development of human cell models that recapitulate hepatic functionality allows the study of metabolic pathways involved in toxicity and disease. The increased biological relevance, cost-effectiveness and high-throughput of cell models can contribute to increase the efficiency of drug development in the pharmaceutical industry. Recapitulation of liver functionality in vitro requires the development of advanced culture strategies to mimic in vivo complexity, such as 3D culture, co-cultures or biomaterials. However, complex 3D models are typically associated with poor robustness, limited scalability and compatibility with screening methods. In this work, several strategies were used to develop highly functional and reproducible spheroid-based in vitro models of human hepatocytes and HepaRG cells using stirred culture systems. In chapter 2, the isolation of human hepatocytes from resected liver tissue was implemented and a liver tissue perfusion method was optimized towards the improvement of hepatocyte isolation and aggregation efficiency, resulting in an isolation protocol compatible with 3D culture. In chapter 3, human hepatocytes were co-cultivated with mesenchymal stem cells (MSC) and the phenotype of both cell types was characterized, showing that MSC acquire a supportive stromal function and hepatocytes retain differentiated hepatic functions, stability of drug metabolism enzymes and higher viability in co-cultures. In chapter 4, a 3D alginate microencapsulation strategy for the differentiation of HepaRG cells was evaluated and compared with the standard 2D DMSO-dependent differentiation, yielding higher differentiation efficiency, comparable levels of drug metabolism activity and significantly improved biosynthetic activity. The work developed in this thesis provides novel strategies for 3D culture of human hepatic cell models, which are reproducible, scalable and compatible with screening platforms. The phenotypic and functional characterization of the in vitro systems performed contributes to the state of the art of human hepatic cell models and can be applied to the improvement of pre-clinical drug development efficiency of the process, model disease and ultimately, development of cell-based therapeutic strategies for liver failure.

Scaling In-Memory databases on multicores

Current computer systems have evolved from featuring only a single processing unit and limited RAM, in the order of kilobytes or few megabytes, to include several multicore processors, o↵ering in the order of several tens of concurrent execution contexts, and have main memory in the order of several tens to hundreds of gigabytes. This allows to keep all data of many applications in the main memory, leading to the development of inmemory databases. Compared to disk-backed databases, in-memory databases (IMDBs) are expected to provide better performance by incurring in less I/O overhead. In this dissertation, we present a scalability study of two general purpose IMDBs on multicore systems. The results show that current general purpose IMDBs do not scale on multicores, due to contention among threads running concurrent transactions. In this work, we explore di↵erent direction to overcome the scalability issues of IMDBs in multicores, while enforcing strong isolation semantics. First, we present a solution that requires no modification to either database systems or to the applications, called MacroDB. MacroDB replicates the database among several engines, using a master-slave replication scheme, where update transactions execute on the master, while read-only transactions execute on slaves. This reduces contention, allowing MacroDB to o↵er scalable performance under read-only workloads, while updateintensive workloads su↵er from performance loss, when compared to the standalone engine. Second, we delve into the database engine and identify the concurrency control mechanism used by the storage sub-component as a scalability bottleneck. We then propose a new locking scheme that allows the removal of such mechanisms from the storage sub-component. This modification o↵ers performance improvement under all workloads, when compared to the standalone engine, while scalability is limited to read-only workloads. Next we addressed the scalability limitations for update-intensive workloads, and propose the reduction of locking granularity from the table level to the attribute level. This further improved performance for intensive and moderate update workloads, at a slight cost for read-only workloads. Scalability is limited to intensive-read and read-only workloads. Finally, we investigate the impact applications have on the performance of database systems, by studying how operation order inside transactions influences the database performance. We then propose a Read before Write (RbW) interaction pattern, under which transaction perform all read operations before executing write operations. The RbW pattern allowed TPC-C to achieve scalable performance on our modified engine for all workloads. Additionally, the RbW pattern allowed our modified engine to achieve scalable performance on multicores, almost up to the total number of cores, while enforcing strong isolation.

The quantified-Self and wearable technologies in the workplace: implications and challenges for their implementations

Introduction of technologies in the workplace have led to a dramatic change. These changes have come with an increased capacity to gather data about one’s working performance (i.e. productivity), as well as the capacity to track one’s personal responses (i.e. emotional, physiological, etc.) to this changing workplace environment. This movement of self-monitoring or self-sensing using diverse types of wearable sensors combined with the use of computing has been identified as the Quantified-Self. Miniaturization of sensors, reduction in cost and a non-stop increase in the computer power capacity has led to a panacea of wearables and sensors to track and analyze all types of information. Utilized in the personal sphere to track information, a looming question remains, should employers use the information from the Quantified-Self to track their employees’ performance or well-being in the workplace and will this benefit employees? The aim of the present work is to layout the implications and challenges associated with the use of Quantified-Self information in the workplace. The Quantified-Self movement has enabled people to understand their personal life better by tracking multiple information and signals; such an approach could allow companies to gather knowledge on what drives productivity for their business and/or well-being of their employees. A discussion about the implications of this approach will cover 1) Monitoring health and well-being, 2) Oversight and safety, and 3) Mentoring and training. Challenges will address the question of 1) Privacy and Acceptability, 2) Scalability and 3) Creativity. Even though many questions remain regarding their use in the workplace, wearable technologies and Quantified-Self data in the workplace represent an exciting opportunity for the industry and health and safety practitioners who will be using them.

Parallel improved Schnorr-Euchner enumeration SE++ for the CVP and SVP

The Closest Vector Problem (CVP) and the Shortest Vector Problem (SVP) are prime problems in lattice-based cryptanalysis, since they underpin the security of many lattice-based cryptosystems. Despite the importance of these problems, there are only a few CVP-solvers publicly available, and their scalability was never studied. This paper presents a scalable implementation of an enumeration-based CVP-solver for multi-cores, which can be easily adapted to solve the SVP. In particular, it achieves super-linear speedups in some instances on up to 8 cores and almost linear speedups on 16 cores when solving the CVP on a 50-dimensional lattice. Our results show that enumeration-based CVP-solvers can be parallelized as effectively as enumeration-based solvers for the SVP, based on a comparison with a state of the art SVP-solver. In addition, we show that we can optimize the SVP variant of our solver in such a way that it becomes 35%-60% faster than the fastest enumeration-based SVP-solver to date.

Development of magnetoelectric CoFe2O4/poly(vinylidene fluoride) microspheres

Magnetoelectric microspheres based on piezoelectric poly(vinylidene fluoride) (PVDF) and magnetrostrictive CoFe2O4 (CFO), a novel morphology for polymer-based ME material, have been developed by an electrospray process. The CFO nanoparticles content in the (3-7 μm diameter) microspheres reaches values up to 27 wt.%, despite their concentration in the starting solution reaching values up to 70 wt.%. Additionally, the inclusion of magnetostrictive nanoparticles into the polymer spheres has no relevant effect on the piezoelectric β-phase content (≈60%), crystallinity (40%) and the onset degradation temperature (460º-465ºC) of the polymer matrix. The multiferroic microspeheres show a maximum piezoelectric reponse |d33|≈30 pC.N-1, leading to a magnetoelectric response of Δ|d33|≈5 pC.N-1 obtained when a 220 mT DC magnetic field was applied. It is also shown that the interface between CFO nanoparticles and PVDF (from 0 to 55%) has a strong influence on the ME response of the microspheres. The simplicity and the scalability of the processing method suggest a large application potential of this novel magnetoelectric geometry in areas such as tissue engineering, sensors and actuators.

A hybrid MAC Scheme to improve the transmission performance in body sensor networks

Wireless body sensor networks (WBSNs) constitute a key technology for closing the loop between patients and healthcare providers, as WBSNs provide sensing ability, as well as mobility and portability, essential characteristics for wide acceptance of wireless healthcare technology. However, one important and difficult aspect of WBSNs is to provide data transmissions with quality of service, among other factors due to the antennas being small size and placed close to the body. Such transmissions cannot be fully provided without the assumption of a MAC protocol that solves the problems of the medium sharing. A vast number of MAC protocols conceived for wireless networks are based on random or scheduled schemes. This paper studies firstly the suitability of two MAC protocols, one using CSMA and the other TDMA, to transmit directly to the base station the signals collected continuously from multiple sensor nodes placed on the human body. Tests in a real scenario show that the beaconed TDMA MAC protocol presents an average packet loss ratio lower than CSMA. However, the average packet loss ratio is above 1.0 %. To improve this performance, which is of vital importance in areas such as e-health and ambient assisted living, a hybrid TDMA/CSMA scheme is proposed and tested in a real scenario with two WBSNs and four sensor nodes per WBSN. An average packet loss ratio lower than 0.2 % was obtained with the hybrid scheme. To achieve this significant improvement, the hybrid scheme uses a lightweight algorithm to control dynamically the start of the superframes. Scalability and traffic rate variation tests show that this strategy allows approximately ten WBSNs operating simultaneously without significant performance degradation.

ADSNARK: Nearly practical and privacy-preserving proofs on authenticated data

We study the problem of privacy-preserving proofs on authenticated data, where a party receives data from a trusted source and is requested to prove computations over the data to third parties in a correct and private way, i.e., the third party learns no information on the data but is still assured that the claimed proof is valid. Our work particularly focuses on the challenging requirement that the third party should be able to verify the validity with respect to the specific data authenticated by the source — even without having access to that source. This problem is motivated by various scenarios emerging from several application areas such as wearable computing, smart metering, or general business-to-business interactions. Furthermore, these applications also demand any meaningful solution to satisfy additional properties related to usability and scalability. In this paper, we formalize the above three-party model, discuss concrete application scenarios, and then we design, build, and evaluate ADSNARK, a nearly practical system for proving arbitrary computations over authenticated data in a privacy-preserving manner. ADSNARK improves significantly over state-of-the-art solutions for this model. For instance, compared to corresponding solutions based on Pinocchio (Oakland’13), ADSNARK achieves up to 25× improvement in proof-computation time and a 20× reduction in prover storage space.

Verificación Formal de Sistemas basada Formal Software Verification based on Automated Analysisen Análisis Automático.

Identificación y caracterización del problema. Uno de los problemas más importantes asociados con la construcción de software es la corrección del mismo. En busca de proveer garantías del correcto funcionamiento del software, han surgido una variedad de técnicas de desarrollo con sólidas bases matemáticas y lógicas conocidas como métodos formales. Debido a su naturaleza, la aplicación de métodos formales requiere gran experiencia y conocimientos, sobre todo en lo concerniente a matemáticas y lógica, por lo cual su aplicación resulta costosa en la práctica. Esto ha provocado que su principal aplicación se limite a sistemas críticos, es decir, sistemas cuyo mal funcionamiento puede causar daños de magnitud, aunque los beneficios que sus técnicas proveen son relevantes a todo tipo de software. Poder trasladar los beneficios de los métodos formales a contextos de desarrollo de software más amplios que los sistemas críticos tendría un alto impacto en la productividad en tales contextos. Hipótesis. Contar con herramientas de análisis automático es un elemento de gran importancia. Ejemplos de esto son varias herramientas potentes de análisis basadas en métodos formales, cuya aplicación apunta directamente a código fuente. En la amplia mayoría de estas herramientas, la brecha entre las nociones a las cuales están acostumbrados los desarrolladores y aquellas necesarias para la aplicación de estas herramientas de análisis formal sigue siendo demasiado amplia. Muchas herramientas utilizan lenguajes de aserciones que escapan a los conocimientos y las costumbres usuales de los desarrolladores. Además, en muchos casos la salida brindada por la herramienta de análisis requiere cierto manejo del método formal subyacente. Este problema puede aliviarse mediante la producción de herramientas adecuadas. Otro problema intrínseco a las técnicas automáticas de análisis es cómo se comportan las mismas a medida que el tamaño y complejidad de los elementos a analizar crece (escalabilidad). Esta limitación es ampliamente conocida y es considerada crítica en la aplicabilidad de métodos formales de análisis en la práctica. Una forma de atacar este problema es el aprovechamiento de información y características de dominios específicos de aplicación. Planteo de objetivos. Este proyecto apunta a la construcción de herramientas de análisis formal para contribuir a la calidad, en cuanto a su corrección funcional, de especificaciones, modelos o código, en el contexto del desarrollo de software. Más precisamente, se busca, por un lado, identificar ambientes específicos en los cuales ciertas técnicas de análisis automático, como el análisis basado en SMT o SAT solving, o el model checking, puedan llevarse a niveles de escalabilidad superiores a los conocidos para estas técnicas en ámbitos generales. Se intentará implementar las adaptaciones a las técnicas elegidas en herramientas que permitan su uso a desarrolladores familiarizados con el contexto de aplicación, pero no necesariamente conocedores de los métodos o técnicas subyacentes. Materiales y métodos a utilizar. Los materiales a emplear serán bibliografía relevante al área y equipamiento informático. Métodos. Se emplearán los métodos propios de la matemática discreta, la lógica y la ingeniería de software. Resultados esperados. Uno de los resultados esperados del proyecto es la individualización de ámbitos específicos de aplicación de métodos formales de análisis. Se espera que como resultado del desarrollo del proyecto surjan herramientas de análisis cuyo nivel de usabilidad sea adecuado para su aplicación por parte de desarrolladores sin formación específica en los métodos formales utilizados. Importancia del proyecto. El principal impacto de este proyecto será la contribución a la aplicación práctica de técnicas formales de análisis en diferentes etapas del desarrollo de software, con la finalidad de incrementar su calidad y confiabilidad. A crucial factor for software quality is correcteness. Traditionally, formal approaches to software development concentrate on functional correctness, and tackle this problem basically by being based on well defined notations founded on solid mathematical grounds. This makes formal methods better suited for analysis, due to their precise semantics, but they are usually more complex, and require familiarity and experience with the manipulation of mathematical definitions. So, their acceptance by software engineers is rather restricted, and formal methods applications have been confined to critical systems. Nevertheless, it is obvious that the advantages that formal methods provide apply to any kind of software system. It is accepted that appropriate software tool support for formal analysis is essential, if one seeks providing support for software development based on formal methods. Indeed, some of the relatively recent sucesses of formal methods are accompanied by good quality tools that automate powerful analysis mechanisms, and are even integrated in widely used development environments. Still, most of these tools either concentrate on code analysis, and in many cases are still far from being simple enough to be employed by software engineers without experience in formal methods. Another important problem for the adoption of tool support for formal methods is scalability. Automated software analysis is intrinsically complex, and thus techniques do not scale well in the general case. In this project, we will attempt to identify particular modelling, design, specification or coding activities in software development processes where to apply automated formal analysis techniques. By focusing in very specific application domains, we expect to find characteristics that might be exploited to increase the scalability of the corresponding analyses, compared to the general case.