Attribute Based Encryption for Secure Data Access in Cloud

Cloud computing is a progressive computing worldview, which empowers adaptable, on-request, and ease use of Information Technology assets. However, the information transmitted to some cloud servers, and various protection concerns are arising out of it. Different plans given the property-based encryption have been proposed to secure the Cloud Storage. In any case, most work spotlights on the information substance security and the get to control, while less consideration towards the benefit control and the character protection. In this paper, a semi-anonymous benefit control conspires AnonyControl to address the information protection, as well as the client character security in existing access control plans. AnonyControl decentralizes the central authority to restrain the character spillage and accordingly accomplishes semi-anonymity. Furthermore, it likewise sums up the document get to control to the benefit control, by which advantages of all operations on the cloud information managed in a fine-grained way. Along these lines, display the AnonyControl-F, which ultimately keeps the character spillage and accomplish the full secrecy. Our security assessment demonstrates that both AnonyControl and AnonyControl-F are secure under the decisional bilinear Diffie-Hellman presumption, and our execution assessment shows the attainability of our plans. Index Terms: Anonymity, multi-authority, attribute-based encryption

Energy Measurements of High Performance Computing Systems: From Instrumentation to Analysis

Energy efficiency is a major criterion for computing in general and High Performance Computing in particular. When optimizing for energy efficiency, it is essential to measure the underlying metric: energy consumption. To fully leverage energy measurements, their quality needs to be well-understood. To that end, this thesis provides a rigorous evaluation of various energy measurement techniques. I demonstrate how the deliberate selection of instrumentation points, sensors, and analog processing schemes can enhance the temporal and spatial resolution while preserving a well-known accuracy. Further, I evaluate a scalable energy measurement solution for production HPC systems and address its shortcomings. Such high-resolution and large-scale measurements present challenges regarding the management of large volumes of generated metric data. I address these challenges with a scalable infrastructure for collecting, storing, and analyzing metric data. With this infrastructure, I also introduce a novel persistent storage scheme for metric time series data, which allows efficient queries for aggregate timelines. To ensure that it satisfies the demanding requirements for scalable power measurements, I conduct an extensive performance evaluation and describe a productive deployment of the infrastructure. Finally, I describe different approaches and practical examples of analyses based on energy measurement data. In particular, I focus on the combination of energy measurements and application performance traces. However, interweaving fine-grained power recordings and application events requires accurately synchronized timestamps on both sides. To overcome this obstacle, I develop a resilient and automated technique for time synchronization, which utilizes crosscorrelation of a specifically influenced power measurement signal. Ultimately, this careful combination of sophisticated energy measurements and application performance traces yields a detailed insight into application and system energy efficiency at full-scale HPC systems and down to millisecond-range regions.:1 Introduction 2 Background and Related Work 2.1 Basic Concepts of Energy Measurements 2.1.1 Basics of Metrology 2.1.2 Measuring Voltage, Current, and Power 2.1.3 Measurement Signal Conditioning and Analog-to-Digital Conversion 2.2 Power Measurements for Computing Systems 2.2.1 Measuring Compute Nodes using External Power Meters 2.2.2 Custom Solutions for Measuring Compute Node Power 2.2.3 Measurement Solutions of System Integrators 2.2.4 CPU Energy Counters 2.2.5 Using Models to Determine Energy Consumption 2.3 Processing of Power Measurement Data 2.3.1 Time Series Databases 2.3.2 Data Center Monitoring Systems 2.4 Influences on the Energy Consumption of Computing Systems 2.4.1 Processor Power Consumption Breakdown 2.4.2 Energy-Efficient Hardware Configuration 2.5 HPC Performance and Energy Analysis 2.5.1 Performance Analysis Techniques 2.5.2 HPC Performance Analysis Tools 2.5.3 Combining Application and Power Measurements 2.6 Conclusion 3 Evaluating and Improving Energy Measurements 3.1 Description of the Systems Under Test 3.2 Instrumentation Points and Measurement Sensors 3.2.1 Analog Measurement at Voltage Regulators 3.2.2 Instrumentation with Hall Effect Transducers 3.2.3 Modular Instrumentation of DC Consumers 3.2.4 Optimal Wiring for Shunt-Based Measurements 3.2.5 Node-Level Instrumentation for HPC Systems 3.3 Analog Signal Conditioning and Analog-to-Digital Conversion 3.3.1 Signal Amplification 3.3.2 Analog Filtering and Analog-To-Digital Conversion 3.3.3 Integrated Solutions for High-Resolution Measurement 3.4 Accuracy Evaluation and Calibration 3.4.1 Synthetic Workloads for Evaluating Power Measurements 3.4.2 Improving and Evaluating the Accuracy of a Single-Node Measuring System 3.4.3 Absolute Accuracy Evaluation of a Many-Node Measuring System 3.5 Evaluating Temporal Granularity and Energy Correctness 3.5.1 Measurement Signal Bandwidth at Different Instrumentation Points 3.5.2 Retaining Energy Correctness During Digital Processing 3.6 Evaluating CPU Energy Counters 3.6.1 Energy Readouts with RAPL 3.6.2 Methodology 3.6.3 RAPL on Intel Sandy Bridge-EP 3.6.4 RAPL on Intel Haswell-EP and Skylake-SP 3.7 Conclusion 4 A Scalable Infrastructure for Processing Power Measurement Data 4.1 Requirements for Power Measurement Data Processing 4.2 Concepts and Implementation of Measurement Data Management 4.2.1 Message-Based Communication between Agents 4.2.2 Protocols 4.2.3 Application Programming Interfaces 4.2.4 Efficient Metric Time Series Storage and Retrieval 4.2.5 Hierarchical Timeline Aggregation 4.3 Performance Evaluation 4.3.1 Benchmark Hardware Specifications 4.3.2 Throughput in Symmetric Configuration with Replication 4.3.3 Throughput with Many Data Sources and Single Consumers 4.3.4 Temporary Storage in Message Queues 4.3.5 Persistent Metric Time Series Request Performance 4.3.6 Performance Comparison with Contemporary Time Series Storage Solutions 4.3.7 Practical Usage of MetricQ 4.4 Conclusion 5 Energy Efficiency Analysis 5.1 General Energy Efficiency Analysis Scenarios 5.1.1 Live Visualization of Power Measurements 5.1.2 Visualization of Long-Term Measurements 5.1.3 Integration in Application Performance Traces 5.1.4 Graphical Analysis of Application Power Traces 5.2 Correlating Power Measurements with Application Events 5.2.1 Challenges for Time Synchronization of Power Measurements 5.2.2 Reliable Automatic Time Synchronization with Correlation Sequences 5.2.3 Creating a Correlation Signal on a Power Measurement Channel 5.2.4 Processing the Correlation Signal and Measured Power Values 5.2.5 Common Oversampling of the Correlation Signals at Different Rates 5.2.6 Evaluation of Correlation and Time Synchronization 5.3 Use Cases for Application Power Traces 5.3.1 Analyzing Complex Power Anomalies 5.3.2 Quantifying C-State Transitions 5.3.3 Measuring the Dynamic Power Consumption of HPC Applications 5.4 Conclusion 6 Summary and Outloo

A distributed analysis and monitoring framework for the compact Muon solenoid experiment and a pedestrian simulation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The design of a parallel and distributed computing system is a very complicated task. It requires a detailed understanding of the design issues and of the theoretical and practical aspects of their solutions. Firstly, this thesis discusses in detail the major concepts and components required to make parallel and distributed computing a reality. A multithreaded and distributed framework capable of analysing the simulation data produced by a pedestrian simulation software was developed. Secondly, this thesis discusses the origins and fundamentals of Grid computing and the motivations for its use in High Energy Physics. Access to the data produced by the Large Hadron Collider (LHC) has to be provided for more than five thousand scientists all over the world. Users who run analysis jobs on the Grid do not necessarily have expertise in Grid computing. Simple, userfriendly and reliable monitoring of the analysis jobs is one of the key components of the operations of the distributed analysis; reliable monitoring is one of the crucial components of the Worldwide LHC Computing Grid for providing the functionality and performance that is required by the LHC experiments. The CMS Dashboard Task Monitoring and the CMS Dashboard Job Summary monitoring applications were developed to serve the needs of the CMS community

IMPROVING REVISITATION IN LONG DOCUMENTS WITH TWO-LEVEL ARTIFICIAL-LANDMARK SCROLLBARS

Revisitation – returning to previously-visited locations in a document – is commonly done in the digital world. While linear navigation controls provide a spatial representation of the document and allow effective navigation in short documents, they are not effective in long documents, particularly for revisitation. Bookmarks, search and history dialogs, and “read wear” (visual marks left as the user interacts with the document) can all assist revisitation; however, for long documents all of these tools are limited in terms of effort, clutter, and interpretability. Inspired by visual cues such as coloured edges and “thumb indents” in hardcopy books, recent work has proposed artificial landmarks to help users build up natural spatial memory for the locations in a document; in long documents, however, this technique is also limited because of the number of pages each landmark represents. To address this problem, this thesis proposes a Double-Scrollbar design that uses two columns of artificial landmarks that can provide greater specificity for spatial memory and revisitation in long documents. We developed three versions of landmark-augmented Double-Scrollbar, using icons, letters, and digits as landmarks. To assess the performance and usability of the Double-Scrollbar design, two studies were conducted with 21 participants, each visiting and revisiting pages of a long document using each of the new designs, as well as a single-column design and a standard scrollbar. Results showed that two levels of icon landmarks were significantly better for assisting revisitation, and were preferred by participants. The two-level artificial-landmark scrollbar is a new way of improving revisitation in long documents by assisting the formation of more precise spatial memories about document locations

Energy-efficient mobile Web computing

Next-generation Web services will be primarily accessed through mobile devices. However, mobile devices are low-performance and stringently energy-constrained. In my dissertation, I propose the design of a high-performance and energy-efficient mobile Web computing substrate. It is a hardware/software co-designed system that delivers satisfactory user quality-of-service (QoS) experience on a mobile energy budget. The key insight is that the traditional interfaces between different Web stacks need to be enhanced with new abstractions that express user QoS experience and that expose architectural-level complexities. On the basis of the enhanced interfaces, I propose synergistic cross-layer optimizations across the processor architecture, Web runtime, programming language, and application layers to maximize the whole system efficiency. The contributions made in this dissertation will likely have a long-term impact because the target application domain, the Web, is becoming a universal mobile development platform, and because our solutions target the fundamental computation layers of the Web domain.Electrical and Computer Engineerin

A Generic method for assembling software product line components

Software product lines (SPL) facilitate the industrialization of software development. The main goal is to create a set of reusable software components for the rapid production of a software systems family. Many authors propose different approaches to implement and assemble the reusable components of an SPL. However, the construction and assembly of these components continue to be a complex and time-consuming process. This thesis analyzes the advantages and disadvantages of the current approaches to implement and assemble the reusable components of an SPL. Taking advantage of these elements and with the goal of developing a generic method (which can be applied to several software components developed in different software languages), we develop Fragment-oriented programming (FragOP), a framework to design, implement and reuse SPL domain components. FragOP is based on: (i) domain components, (ii) domain files, (iii) fragmentation points, (iv) fragments, (v) customization points, and (vi) customization files. FragOP was implemented in an open-source tool called VariaMos, and we also carried out three evaluations: (i) we created a clothing stores SPL, derived five different products, and discussed the results. (ii) We developed a discussion about the comparison between FragOP and other approaches. And (iii) we designed and executed a usability test of VariaMos to support the FragOP approach. The results show preliminary evidence that the use of FragOP reduces the manual intervention when assembling SPL domain components and it can be used as a generic method for assembling assets and SPL components developed in different software languages.Las líneas de productos de software (LPS) promueven la industrialización del desarrollo de software mediante la definición y ensamblaje de componentes reutilizables de software. Actualmente existen diferentes propuestas para implementar y ensamblar estos componentes. Sin embargo, su construcción y ensamblaje continúa siendo un proceso complejo y que requiere mucho tiempo. Esta tesis analiza las ventajas y desventajas de las diferentes estrategias actuales para implementación y ensamblaje de componentes de LPS. Con base en esto y con el objetivo de desarrollar un método genérico (el cual se pueda aplicar a múltiples componentes de software desarrollados en diferentes lenguajes), esta tesis desarrolla la programación orientada a fragmentos (FragOP), la cual define un marco de trabajo para diseñar, implementar y reutilizar componentes de dominio de LPS. FragOP se basa en: (i) componentes de dominio, (ii) archivos de dominio, (iii) puntos de fragmentación, (iv) fragmentos, (v) puntos de personalización, y (vi) archivos de personalización. Además, se realizó una implementación de FragOP en una herramienta llamada VariaMos, y se llevaron a cabo tres evaluaciones: (i) se creó una LPS de tiendas de ropa, se derivaron cinco productos y se discutieron los resultados. (ii) Se realizó una discusión acerca de la comparación de FragOP y otras propuestas actuales. Y (iii) se diseñó una prueba de usabilidad acerca del soporte de VariaMos para FragOP. Los resultados muestran evidencia preliminar de que el uso de FragOP reduce la intervención manual cuando se ensamblan componentes, y que FragOP puede usarse como un método genérico para el ensamblaje de componentes.Doctorad

Optimal use of computing equipment in an automated industrial inspection context

This thesis deals with automatic defect detection. The objective was to develop the techniques required by a small manufacturing business to make cost-efficient use of inspection technology. In our work on inspection techniques we discuss image acquisition and the choice between custom and general-purpose processing hardware. We examine the classes of general-purpose computer available and study popular operating systems in detail. We highlight the advantages of a hybrid system interconnected via a local area network and develop a sophisticated suite of image-processing software based on it. We quantitatively study the performance of elements of the TCP/IP networking protocol suite and comment on appropriate protocol selection for parallel distributed applications. We implement our own distributed application based on these findings. In our work on inspection algorithms we investigate the potential uses of iterated function series and Fourier transform operators when preprocessing images of defects in aluminium plate acquired using a linescan camera. We employ a multi-layer perceptron neural network trained by backpropagation as a classifier. We examine the effect on the training process of the number of nodes in the hidden layer and the ability of the network to identify faults in images of aluminium plate. We investigate techniques for introducing positional independence into the network's behaviour. We analyse the pattern of weights induced in the network after training in order to gain insight into the logic of its internal representation. We conclude that the backpropagation training process is sufficiently computationally intensive so as to present a real barrier to further development in practical neural network techniques and seek ways to achieve a speed-up. Weconsider the training process as a search problem and arrive at a process involving multiple, parallel search "vectors" and aspects of genetic algorithms. We implement the system as the mentioned distributed application and comment on its performance