881 resultados para distributed computing


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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Denna avhandling handlar om metoder för att hitta begränsningar för det asymptotiska beteendet hos en förväntad uthoppstid från ett område omkring en xpunkt för processer som har normalfördelad störning. I huvudsak behandlas olika typer av autoregressiva processer. Fyra olika metoder används. En metod som använder principen för stora avvikelser samt en metod som jämför uthoppstiden med en återkomsttid ger övre begränsningar för den förväntade uthoppstiden. En martingalmetod och en metod för normalfördelade stokastiska variabler ger undre begränsningar. Metoderna har alla både förtjänster och nackdelar. Genom att kombinera de olika metoderna får man de bästa resultaten. Vi får fram gränsvärdet för det asymptotiska beteendet hos en uthoppstid för den multivariata autoregressiva processen, samt motsvarande gränsvärde för den univariata autoregressiva processen av ordning n.

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Smart phones became part and parcel of our life, where mobility provides a freedom of not being bounded by time and space. In addition, number of smartphones produced each year is skyrocketing. However, this also created discrepancies or fragmentation among devices and OSes, which in turn made an exceeding hard for developers to deliver hundreds of similar featured applications with various versions for the market consumption. This thesis is an attempt to investigate whether cloud based mobile development platforms can mitigate and eventually eliminate fragmentation challenges. During this research, we have selected and analyzed the most popular cloud based development platforms and tested integrated cloud features. This research showed that cloud based mobile development platforms may able to reduce mobile fragmentation and enable to utilize single codebase to deliver a mobile application for different platforms.

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Digital business ecosystems (DBE) are becoming an increasingly popular concept for modelling and building distributed systems in heterogeneous, decentralized and open environments. Information- and communication technology (ICT) enabled business solutions have created an opportunity for automated business relations and transactions. The deployment of ICT in business-to-business (B2B) integration seeks to improve competitiveness by establishing real-time information and offering better information visibility to business ecosystem actors. The products, components and raw material flows in supply chains are traditionally studied in logistics research. In this study, we expand the research to cover the processes parallel to the service and information flows as information logistics integration. In this thesis, we show how better integration and automation of information flows enhance the speed of processes and, thus, provide cost savings and other benefits for organizations. Investments in DBE are intended to add value through business automation and are key decisions in building up information logistics integration. Business solutions that build on automation are important sources of value in networks that promote and support business relations and transactions. Value is created through improved productivity and effectiveness when new, more efficient collaboration methods are discovered and integrated into DBE. Organizations, business networks and collaborations, even with competitors, form DBE in which information logistics integration has a significant role as a value driver. However, traditional economic and computing theories do not focus on digital business ecosystems as a separate form of organization, and they do not provide conceptual frameworks that can be used to explore digital business ecosystems as value drivers—combined internal management and external coordination mechanisms for information logistics integration are not the current practice of a company’s strategic process. In this thesis, we have developed and tested a framework to explore the digital business ecosystems developed and a coordination model for digital business ecosystem integration; moreover, we have analysed the value of information logistics integration. The research is based on a case study and on mixed methods, in which we use the Delphi method and Internetbased tools for idea generation and development. We conducted many interviews with key experts, which we recoded, transcribed and coded to find success factors. Qualitative analyses were based on a Monte Carlo simulation, which sought cost savings, and Real Option Valuation, which sought an optimal investment program for the ecosystem level. This study provides valuable knowledge regarding information logistics integration by utilizing a suitable business process information model for collaboration. An information model is based on the business process scenarios and on detailed transactions for the mapping and automation of product, service and information flows. The research results illustrate the current cap of understanding information logistics integration in a digital business ecosystem. Based on success factors, we were able to illustrate how specific coordination mechanisms related to network management and orchestration could be designed. We also pointed out the potential of information logistics integration in value creation. With the help of global standardization experts, we utilized the design of the core information model for B2B integration. We built this quantitative analysis by using the Monte Carlo-based simulation model and the Real Option Value model. This research covers relevant new research disciplines, such as information logistics integration and digital business ecosystems, in which the current literature needs to be improved. This research was executed by high-level experts and managers responsible for global business network B2B integration. However, the research was dominated by one industry domain, and therefore a more comprehensive exploration should be undertaken to cover a larger population of business sectors. Based on this research, the new quantitative survey could provide new possibilities to examine information logistics integration in digital business ecosystems. The value activities indicate that further studies should continue, especially with regard to the collaboration issues on integration, focusing on a user-centric approach. We should better understand how real-time information supports customer value creation by imbedding the information into the lifetime value of products and services. The aim of this research was to build competitive advantage through B2B integration to support a real-time economy. For practitioners, this research created several tools and concepts to improve value activities, information logistics integration design and management and orchestration models. Based on the results, the companies were able to better understand the formulation of the digital business ecosystem and the importance of joint efforts in collaboration. However, the challenge of incorporating this new knowledge into strategic processes in a multi-stakeholder environment remains. This challenge has been noted, and new projects have been established in pursuit of a real-time economy.

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Distributed storage systems are studied. The interest in such system has become relatively wide due to the increasing amount of information needed to be stored in data centers or different kinds of cloud systems. There are many kinds of solutions for storing the information into distributed devices regarding the needs of the system designer. This thesis studies the questions of designing such storage systems and also fundamental limits of such systems. Namely, the subjects of interest of this thesis include heterogeneous distributed storage systems, distributed storage systems with the exact repair property, and locally repairable codes. For distributed storage systems with either functional or exact repair, capacity results are proved. In the case of locally repairable codes, the minimum distance is studied. Constructions for exact-repairing codes between minimum bandwidth regeneration (MBR) and minimum storage regeneration (MSR) points are given. These codes exceed the time-sharing line of the extremal points in many cases. Other properties of exact-regenerating codes are also studied. For the heterogeneous setup, the main result is that the capacity of such systems is always smaller than or equal to the capacity of a homogeneous system with symmetric repair with average node size and average repair bandwidth. A randomized construction for a locally repairable code with good minimum distance is given. It is shown that a random linear code of certain natural type has a good minimum distance with high probability. Other properties of locally repairable codes are also studied.

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Smart home implementation in residential buildings promises to optimize energy usage and save significant amount of energy simply due to a better understanding of user's energy usage profile. Apart from the energy optimisation prospects of this technology, it also aims to guarantee occupants significant amount of comfort and remote control over home appliances both at home locations and at remote places. However, smart home investment just like any other kind of investment requires an adequate measurement and justification of the economic gains it could proffer before its realization. These economic gains could differ for different occupants due to their inherent behaviours and tendencies. Thus it is pertinent to investigate the various behaviours and tendencies of occupants in different domain of interests and to measure the value of the energy savings accrued by smart home implementations in these domains of interest in order to justify such economic gains. This thesis investigates two domains of interests (the rented apartment and owned apartment) for primarily two behavioural tendencies (Finland and Germany) obtained from observation and corroborated by conducted interviews to measure the payback time and Return on Investment (ROI) of their smart home implementations. Also, similar measures are obtained for identified Australian use case. The research finding reveals that building automation for the Finnish behavioural tendencies seems to proffers a better ROI and payback time for smart home implementations.

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The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

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Resilience is the property of a system to remain trustworthy despite changes. Changes of a different nature, whether due to failures of system components or varying operational conditions, significantly increase the complexity of system development. Therefore, advanced development technologies are required to build robust and flexible system architectures capable of adapting to such changes. Moreover, powerful quantitative techniques are needed to assess the impact of these changes on various system characteristics. Architectural flexibility is achieved by embedding into the system design the mechanisms for identifying changes and reacting on them. Hence a resilient system should have both advanced monitoring and error detection capabilities to recognise changes as well as sophisticated reconfiguration mechanisms to adapt to them. The aim of such reconfiguration is to ensure that the system stays operational, i.e., remains capable of achieving its goals. Design, verification and assessment of the system reconfiguration mechanisms is a challenging and error prone engineering task. In this thesis, we propose and validate a formal framework for development and assessment of resilient systems. Such a framework provides us with the means to specify and verify complex component interactions, model their cooperative behaviour in achieving system goals, and analyse the chosen reconfiguration strategies. Due to the variety of properties to be analysed, such a framework should have an integrated nature. To ensure the system functional correctness, it should rely on formal modelling and verification, while, to assess the impact of changes on such properties as performance and reliability, it should be combined with quantitative analysis. To ensure scalability of the proposed framework, we choose Event-B as the basis for reasoning about functional correctness. Event-B is a statebased formal approach that promotes the correct-by-construction development paradigm and formal verification by theorem proving. Event-B has a mature industrial-strength tool support { the Rodin platform. Proof-based verification as well as the reliance on abstraction and decomposition adopted in Event-B provides the designers with a powerful support for the development of complex systems. Moreover, the top-down system development by refinement allows the developers to explicitly express and verify critical system-level properties. Besides ensuring functional correctness, to achieve resilience we also need to analyse a number of non-functional characteristics, such as reliability and performance. Therefore, in this thesis we also demonstrate how formal development in Event-B can be combined with quantitative analysis. Namely, we experiment with integration of such techniques as probabilistic model checking in PRISM and discrete-event simulation in SimPy with formal development in Event-B. Such an integration allows us to assess how changes and di erent recon guration strategies a ect the overall system resilience. The approach proposed in this thesis is validated by a number of case studies from such areas as robotics, space, healthcare and cloud domain.

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Internet of Things (IoT) technologies are developing rapidly, and therefore there exist several standards of interconnection protocols and platforms. The existence of heterogeneous protocols and platforms has become a critical challenge for IoT system developers. To mitigate this challenge, few alliances and organizations have taken the initiative to build a framework that helps to integrate application silos. Some of these frameworks focus only on a specific domain like home automation. However, the resource constraints in the large proportion of connected devices make it difficult to build an interoperable system using such frameworks. Therefore, a general purpose, lightweight interoperability framework that can be used for a range of devices is required. To tackle the heterogeneous nature, this work introduces an embedded, distributed and lightweight service bus, Lightweight IoT Service bus Architecture (LISA), which fits inside the network stack of a small real-time operating system for constrained nodes. LISA provides a uniform application programming interface for an IoT system on a range of devices with variable resource constraints. It hides platform and protocol variations underneath it, thus facilitating interoperability in IoT implementations. LISA is inspired by the Network on Terminal Architecture, a service centric open architecture by Nokia Research Center. Unlike many other interoperability frameworks, LISA is designed specifically for resource constrained nodes and it provides essential features of a service bus for easy service oriented architecture implementation. The presented architecture utilizes an intermediate computing layer, a Fog layer, between the small nodes and the cloud, thereby facilitating the federation of constrained nodes into subnetworks. As a result of a modular and distributed design, the part of LISA running in the Fog layer handles the heavy lifting to assist the lightweight portion of LISA inside the resource constrained nodes. Furthermore, LISA introduces a new networking paradigm, Node Centric Networking, to route messages across protocol boundaries to facilitate interoperability. This thesis presents a concept implementation of the architecture and creates a foundation for future extension towards a comprehensive interoperability framework for IoT.

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Manufacturing industry has been always facing challenge to improve the production efficiency, product quality, innovation ability and struggling to adopt cost-effective manufacturing system. In recent years cloud computing is emerging as one of the major enablers for the manufacturing industry. Combining the emerged cloud computing and other advanced manufacturing technologies such as Internet of Things, service-oriented architecture (SOA), networked manufacturing (NM) and manufacturing grid (MGrid), with existing manufacturing models and enterprise information technologies, a new paradigm called cloud manufacturing is proposed by the recent literature. This study presents concepts and ideas of cloud computing and cloud manufacturing. The concept, architecture, core enabling technologies, and typical characteristics of cloud manufacturing are discussed, as well as the difference and relationship between cloud computing and cloud manufacturing. The research is based on mixed qualitative and quantitative methods, and a case study. The case is a prototype of cloud manufacturing solution, which is software platform cooperated by ATR Soft Oy and SW Company China office. This study tries to understand the practical impacts and challenges that are derived from cloud manufacturing. The main conclusion of this study is that cloud manufacturing is an approach to achieve the transformation from traditional production-oriented manufacturing to next generation service-oriented manufacturing. Many manufacturing enterprises are already using a form of cloud computing in their existing network infrastructure to increase flexibility of its supply chain, reduce resources consumption, the study finds out the shift from cloud computing to cloud manufacturing is feasible. Meanwhile, the study points out the related theory, methodology and application of cloud manufacturing system are far from maturity, it is still an open field where many new technologies need to be studied.

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Leveraging cloud services, companies and organizations can significantly improve their efficiency, as well as building novel business opportunities. Cloud computing offers various advantages to companies while having some risks for them too. Advantages offered by service providers are mostly about efficiency and reliability while risks of cloud computing are mostly about security problems. Problems with security of the cloud still demand significant attention in order to tackle the potential problems. Security problems in the cloud as security problems in any area of computing, can not be fully tackled. However creating novel and new solutions can be used by service providers to mitigate the potential threats to a large extent. Looking at the security problem from a very high perspective, there are two focus directions. Security problems that threaten service user’s security and privacy are at one side. On the other hand, security problems that threaten service provider’s security and privacy are on the other side. Both kinds of threats should mostly be detected and mitigated by service providers. Looking a bit closer to the problem, mitigating security problems that target providers can protect both service provider and the user. However, the focus of research community mostly is to provide solutions to protect cloud users. A significant research effort has been put in protecting cloud tenants against external attacks. However, attacks that are originated from elastic, on-demand and legitimate cloud resources should still be considered seriously. The cloud-based botnet or botcloud is one of the prevalent cases of cloud resource misuses. Unfortunately, some of the cloud’s essential characteristics enable criminals to form reliable and low cost botclouds in a short time. In this paper, we present a system that helps to detect distributed infected Virtual Machines (VMs) acting as elements of botclouds. Based on a set of botnet related system level symptoms, our system groups VMs. Grouping VMs helps to separate infected VMs from others and narrows down the target group under inspection. Our system takes advantages of Virtual Machine Introspection (VMI) and data mining techniques.

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The goal of this thesis is to define and validate a software engineering approach for the development of a distributed system for the modeling of composite materials, based on the analysis of various existing software development methods. We reviewed the main features of: (1) software engineering methodologies; (2) distributed system characteristics and their effect on software development; (3) composite materials modeling activities and the requirements for the software development. Using the design science as a research methodology, the distributed system for creating models of composite materials is created and evaluated. Empirical experiments which we conducted showed good convergence of modeled and real processes. During the study, we paid attention to the matter of complexity and importance of distributed system and a deep understanding of modern software engineering methods and tools.

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Liberalization of electricity markets has resulted in a competed Nordic electricity market, in which electricity retailers play a key role as electricity suppliers, market intermediaries, and service providers. Although these roles may remain unchanged in the near future, the retailers’ operation may change fundamentally as a result of the emerging smart grid environment. Especially the increasing amount of distributed energy resources (DER), and improving opportunities for their control, are reshaping the operating environment of the retailers. This requires that the retailers’ operation models are developed to match the operating environment, in which the active use of DER plays a major role. Electricity retailers have a clientele, and they operate actively in the electricity markets, which makes them a natural market party to offer new services for end-users aiming at an efficient and market-based use of DER. From the retailer’s point of view, the active use of DER can provide means to adapt the operation to meet the challenges posed by the smart grid environment, and to pursue the ultimate objective of the retailer, which is to maximize the profit of operation. This doctoral dissertation introduces a methodology for the comprehensive use of DER in an electricity retailer’s short-term profit optimization that covers operation in a variety of marketplaces including day-ahead, intra-day, and reserve markets. The analysis results provide data of the key profit-making opportunities and the risks associated with different types of DER use. Therefore, the methodology may serve as an efficient tool for an experienced operator in the planning of the optimal market-based DER use. The key contributions of this doctoral dissertation lie in the analysis and development of the model that allows the retailer to benefit from profit-making opportunities brought by the use of DER in different marketplaces, but also to manage the major risks involved in the active use of DER. In addition, the dissertation introduces an analysis of the economic potential of DER control actions in different marketplaces including the day-ahead Elspot market, balancing power market, and the hourly market of Frequency Containment Reserve for Disturbances (FCR-D).

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Variations in different types of genomes have been found to be responsible for a large degree of physical diversity such as appearance and susceptibility to disease. Identification of genomic variations is difficult and can be facilitated through computational analysis of DNA sequences. Newly available technologies are able to sequence billions of DNA base pairs relatively quickly. These sequences can be used to identify variations within their specific genome but must be mapped to a reference sequence first. In order to align these sequences to a reference sequence, we require mapping algorithms that make use of approximate string matching and string indexing methods. To date, few mapping algorithms have been tailored to handle the massive amounts of output generated by newly available sequencing technologies. In otrder to handle this large amount of data, we modified the popular mapping software BWA to run in parallel using OpenMPI. Parallel BWA matches the efficiency of multithreaded BWA functions while providing efficient parallelism for BWA functions that do not currently support multithreading. Parallel BWA shows significant wall time speedup in comparison to multithreaded BWA on high-performance computing clusters, and will thus facilitate the analysis of genome sequencing data.

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Tesis (Maestría en Ciencias con Orientación en Matemáticas) UANL, 2013.