財政部於2006年底建置完成的電子發票整合服務平台，提供不同產業間之買賣雙方一個具有公信力的交易稽核平台。企業在此可利用電子發票向銀行進行貸款，完成融資服務，由於貸款跨越企業與銀行，而各個不同組織間，其流程中會有金、商流共同所需之資訊，但是彼此所需的資訊格式的不同，讓整個流程無法一氣喝成。 本研究提出一個以雲端運算為基礎的服務導向架構電子發票加值平台，透過此平台企業可將原本的發票融資，轉換成利用電子發票進行線上融資，再透過XML-based訊息轉換器將企業端電子發票XML格式轉換為處理帳務之XBRL格式，以及銀行端之金流訊息FXML格式，並利用雲端運算服務作為資料儲存與呈現的基礎，而服務導向架構提供了完成此跨組織金、商流活動所需的平台一個良好架構。 在電子發票加值平台中，處理電子發票加值服務時會運用發票上的金流與商流資訊，基於安全性的考量，所以不能將資料都儲存於雲端運算的資源中，本研究的資料中心利用分散式資料儲存方式，將機密的資料儲存於企業端，減少企業使用服務的疑慮，並透過分散式資料擷取/儲存機制對不同的資料庫存取服務所需之資料，讓企業可以更放心且便利的使用服務。 / Ministry of Finance, R.O.C builds a reliable E-Invoice platform in 2006, to provide buyers and sellers a credible audit platform. Through E-Invoice platform, companies could complete loan service. Because loan service crosses the banks and enterprises, they will need the same information in loan process. However the information to each other is different formats, so that the whole process can not complete straight through. This study proposed a Service-oriented architecture E-Invoice value-added platform which based on cloud computing services. Through this platform, companies can change invoice loan service into E-Invoice on-line loan service. In this platform, they not only can use a XML-based message converter to convert business XML format to financial information XBRL format and cash flow information FXML format but also can use cloud computing services to store and present data. However Service-oriented architecture can provide this cross-organizational activity a suitable architecture. In E-Invoice value-added platform, E-Invoice on-line loan service will handle the information of cash flow and business flow, but based on security considerations, we can not stored all the data in the cloud. However this study use decentralized data center to store confidential information in the enterprise client to solve this problem and use some mechanism to extract/store data from different data center. Therefore Companies can reduce their concerns of using services and use services conveniently.

During this project NoSQL technologies for Hotel IT have been evaluated. It has been determined that among NoSQL technologies, document database fits the best this use-case. Couchbase and MongoDB, the two main documents stores have been evaluated, their similarities and differences have been highlighted. This reveals that document-oriented features were more developed in MongoDB than Couchbase, this has a direct impact on search of reservations functionality. However Couchbase offers a better way to replicate data across two remote data centers. As one of the goals was to provide a powerful search functionality, it has been decided to use MongoDB as a database for this project. A proof of concept has been developed, it enables to search reservations by property code, guest name, check-in date and check-out date using a REST/JSON interface and confirms that MongoDB could work for storing hotel reservations in terms of functionality. Then different experiments have been conducted on this system such as throughput and response time using specific hotel reservation search query and data set. The results we got reached our targets. We also performed a scalability test, using MongoDB sharding functionalities to distribute data across several machines (shards) using different strategies (shard keys) so as to provide configuration recommendations. Our main finding was that it was not necessary to always distribute the database. Then if "sharding" is needed, distributing the data according to the property code will make the database go faster, because queries will be sent directly to the good machine(s) in the cluster and thus avoid "scatter-gather" query. Finally some search optimizations have been proposed, and in particular how an advanced search by names could be implemented with MongoDB. / <p>This thesis is submitted in the framework of a double degree between Compiègne University Of Technology (UTC) and Linköping University (LiU)</p>

L'expansion des services en ligne, l'avènement du big data, favorisé par l'internet des objets et les terminaux mobiles, a entraîné une croissance exponentielle du nombre de centres de données qui fournissent des divers services de cloud computing. Par conséquent, la topologie du centre de données est considérée comme un facteur d'influence sur la performance du centre de données. En effet, les topologies des centres de données devraient offrir une latence faible, une longueur de chemin moyenne réduite avec une bande passante élevée. Ces exigences augmentent la consommation énergétique dans les centres de données. Dans cette dissertation, différentes solutions ont été proposées pour surmonter ces problèmes. Tout d'abord, nous proposons une nouvelle topologie appelée LCT (Linked Cluster Topology) qui augmente le nombre de nœuds, améliore la connexion réseau et optimise le routage des données pour avoir une faible latence réseau. Une nouvelle topologie appelée VacoNet (Variable connexion Network) a été également présentée. VacoNet offre un nouveau algorithme qui définit le exact nombre de port par commutateur pour connecter le nombre de serveurs requis tout en réduisant l'énergie consommée et les matériaux inutilisés (câbles, commutateurs). En outre, nous _étudions une nouvelle technique pour optimiser la consumation d'énergie aux centres de données. Cette technique peut périodiquement estimer la matrice de trafic et gérer l'_état des ports de serveurs tout en maintenant le centre de données entièrement connecté. La technique proposée prend en considération le trafic réseau dans la décision de gestion des ports. / Data centers (DC) are being built around the world to provide various cloud computing services. One of the fundamental challenges of existing DC is to design a network that interconnects massive number of nodes (servers)1 while reducing DC' cost and energy consumption. Several solutions have been proposed (e.g. FatTree, DCell and BCube), but they either scale too fast (i.e., double exponentially) or too slow. Effcient DC topologies should incorporate high scalability, low latency, low Average Path Length (APL), high Aggregated Bottleneck Throughput (ABT) and low cost and energy consumption. Therefore, in this dissertation, different solutions have been proposed to overcome these problems. First, we propose a novel DC topology called LCT (Linked Cluster Topology) as a new solution for building scalable and cost effective DC networking infrastructures. The proposed topology reduces the number of redundant connections between clusters of nodes, while increasing the numbers of nodes without affecting the network bisection bandwidth. Furthermore, in order to reduce the DCs cost and energy consumption, we propose first a new static energy saving topology called VacoNet (Variable Connection Network) that connects the needed number of servers while reducing the unused materials (cables, switches). Also, we propose a new approach that exploits the correlation in time of internode communication and some topological features to maximize energy saving without too much impacting the average path length.

Atualmente, o processamento de dados é uma operação vital para os negócios de qualquer companhia, indústria ou prestador de serviços. Entretanto, os servidores em operação, dissipam energia térmica, aquecendo o ambiente, podendo ocasionar problemas operacionais, como funcionamento inadequado, paradas operacionais e até incêndios. Por isso, é necessário um sistema de condicionamento de ar para controlar de temperatura e umidade ambiental, entretanto o consumo de energia elétrica deste sistema aumenta o custo operacional da instalação, sendo necessário minimizá-lo. Baseado neste fato, esta tese avalia a aplicação de 2 tipos de sistemas de resfriamento solar, absorção térmica solar e fotovoltaico, para reduzir o consumo do tradicional sistema elétrico com unidades de resfriamento elétricas operadas por compressão de vapor, apresentando economias, disponibilidade diária e vantagens em uma sala de missão crítica localiza genericamente, em São Paulo, Abu Dhabi, Los Angeles e Nova York. Além disto, analisa a contribuição de sistemas de resfriamento natural e seus efeitos sobre carga e consumo. As densidades de carga propostas foram de 0,5 kW?m-², 1,0 kW?m-², 2,0 kW?m-², 4,0 kW?m-² e 8,0 kW/m. Os índices locais de irradiação e temperaturas anuais baseiam-se nos dados apresentados no banco de dados da ASHRAE para as localidades. Os resultados, válidos para um ano típico e são comparados com (1) Sala de missão crítica acionada por um sistema convencional, (2) combinação de métodos de resfriamento solar, (3) combinação de técnicas solares e resfriamento natural. Por meio de estimativas anuais, calculando as contribuições dos métodos de resfriamento solar e natural, concluiu- maioria dos casos o método de absorção solar apresenta maiores vantagens de economia de energia e retorno de investimento que o método fotovoltaico, especialmente quando associado ao resfriamento natural indireto. Ao final, conclui-se que a utilização de resfriamento solar, pode atingir a 50% de economia na conta de energia e um TIR de 25%. Quando associado a sistemas de resfriamento natural, a economia pode atingir valores de 68% de economia e um TIR de 134%. Para tal deverá ser observado a carga aplicada, o valor de investimento e a curva característica da unidade de resfriamento que irá complementar a carga. / Nowadays, data processing is a fundamental operation for modern business such as banks, technology companies, and factories, among others. However, computers dissipate non-negligible amounts of heat and as the operating temperature increases, these machines cannot operate properly or, under extreme conditions, can come to a stop by overheating. Consequently, it is necessary air conditioning systems to keep the proper operating temperature as well as the room temperature itself. On the other hand, a data center air conditioning system drains a large amount of electrical energy in the installation. Based on this, this thesis evaluates two types of solar cooling system, an absorption thermal system, and a photovoltaic system, to support the traditional electric chiller system showing the energy saving, advantage over conventional cooling and day availability for this system. In addition, it analyzed free cooling system contribution and his effects on consumption. A case study is analyzed in a generic data center located in the city of São Paulo, Abu Dhabi, Los Angeles, and New York. At first, the electrical power density simulated by the computers is 0.5 kW/m², 1.0 kW/m² 2.0 kW/m², 4.0 kW/m² and 8 kW/m², that would occur in half loads or in high loads computer installations. Local solar irradiation and temperature indexes are based on the ASHRAE database. The results are valid for a typical year and are compared to (1) a conventional data center; (2) the event combination of solar cooling; (3) the event combination of solar cooling and free cooling. In conclusion, the energy savings, payback and internal rate of return for 10 years are presented. In the main cases, the solar absorption takes advantage than photovoltaic cooling, However, It must be observed the load replicated and the influence on the work curve of the chiller and the beginning investment. In conclusion, the solar cooling, especially solar absorption can achieve great advantage to installation, resulting in 50% on savings in the electric bill a return internal rate for 10 years of 25%. When it is associated with free cooling this savings can achieve 68% and return rate of 134%.

Atualmente, o processamento de dados é uma operação vital para os negócios de qualquer companhia, indústria ou prestador de serviços. Entretanto, os servidores em operação, dissipam energia térmica, aquecendo o ambiente, podendo ocasionar problemas operacionais, como funcionamento inadequado, paradas operacionais e até incêndios. Por isso, é necessário um sistema de condicionamento de ar para controlar de temperatura e umidade ambiental, entretanto o consumo de energia elétrica deste sistema aumenta o custo operacional da instalação, sendo necessário minimizá-lo. Baseado neste fato, esta tese avalia a aplicação de 2 tipos de sistemas de resfriamento solar, absorção térmica solar e fotovoltaico, para reduzir o consumo do tradicional sistema elétrico com unidades de resfriamento elétricas operadas por compressão de vapor, apresentando economias, disponibilidade diária e vantagens em uma sala de missão crítica localiza genericamente, em São Paulo, Abu Dhabi, Los Angeles e Nova York. Além disto, analisa a contribuição de sistemas de resfriamento natural e seus efeitos sobre carga e consumo. As densidades de carga propostas foram de 0,5 kW?m-², 1,0 kW?m-², 2,0 kW?m-², 4,0 kW?m-² e 8,0 kW/m. Os índices locais de irradiação e temperaturas anuais baseiam-se nos dados apresentados no banco de dados da ASHRAE para as localidades. Os resultados, válidos para um ano típico e são comparados com (1) Sala de missão crítica acionada por um sistema convencional, (2) combinação de métodos de resfriamento solar, (3) combinação de técnicas solares e resfriamento natural. Por meio de estimativas anuais, calculando as contribuições dos métodos de resfriamento solar e natural, concluiu- maioria dos casos o método de absorção solar apresenta maiores vantagens de economia de energia e retorno de investimento que o método fotovoltaico, especialmente quando associado ao resfriamento natural indireto. Ao final, conclui-se que a utilização de resfriamento solar, pode atingir a 50% de economia na conta de energia e um TIR de 25%. Quando associado a sistemas de resfriamento natural, a economia pode atingir valores de 68% de economia e um TIR de 134%. Para tal deverá ser observado a carga aplicada, o valor de investimento e a curva característica da unidade de resfriamento que irá complementar a carga. / Nowadays, data processing is a fundamental operation for modern business such as banks, technology companies, and factories, among others. However, computers dissipate non-negligible amounts of heat and as the operating temperature increases, these machines cannot operate properly or, under extreme conditions, can come to a stop by overheating. Consequently, it is necessary air conditioning systems to keep the proper operating temperature as well as the room temperature itself. On the other hand, a data center air conditioning system drains a large amount of electrical energy in the installation. Based on this, this thesis evaluates two types of solar cooling system, an absorption thermal system, and a photovoltaic system, to support the traditional electric chiller system showing the energy saving, advantage over conventional cooling and day availability for this system. In addition, it analyzed free cooling system contribution and his effects on consumption. A case study is analyzed in a generic data center located in the city of São Paulo, Abu Dhabi, Los Angeles, and New York. At first, the electrical power density simulated by the computers is 0.5 kW/m², 1.0 kW/m² 2.0 kW/m², 4.0 kW/m² and 8 kW/m², that would occur in half loads or in high loads computer installations. Local solar irradiation and temperature indexes are based on the ASHRAE database. The results are valid for a typical year and are compared to (1) a conventional data center; (2) the event combination of solar cooling; (3) the event combination of solar cooling and free cooling. In conclusion, the energy savings, payback and internal rate of return for 10 years are presented. In the main cases, the solar absorption takes advantage than photovoltaic cooling, However, It must be observed the load replicated and the influence on the work curve of the chiller and the beginning investment. In conclusion, the solar cooling, especially solar absorption can achieve great advantage to installation, resulting in 50% on savings in the electric bill a return internal rate for 10 years of 25%. When it is associated with free cooling this savings can achieve 68% and return rate of 134%.

Submitted by Erika Demachki (erikademachki@gmail.com) on 2015-02-05T19:59:39Z No. of bitstreams: 2 Dissertação - Pedro Henrique Pires de Castro - 2014.pdf: 1908182 bytes, checksum: edac87bddd8346a2bcce5d9b5f00301d (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Erika Demachki (erikademachki@gmail.com) on 2015-02-05T20:00:48Z (GMT) No. of bitstreams: 2 Dissertação - Pedro Henrique Pires de Castro - 2014.pdf: 1908182 bytes, checksum: edac87bddd8346a2bcce5d9b5f00301d (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2015-02-05T20:00:48Z (GMT). No. of bitstreams: 2 Dissertação - Pedro Henrique Pires de Castro - 2014.pdf: 1908182 bytes, checksum: edac87bddd8346a2bcce5d9b5f00301d (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2014-08-04 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Cloud computing is being consolidated as a new distributed systems paradigm, offering computing resources in a virtualized way and with unprecedented levels of flexibility, reliability, and scalability. Unfortunately, the benefits of cloud computing come at a high cost with regard to energy, mainly because of one of its core enablers, the data center. There are a number of proposals that seek to enhance energy efficiency in data centers. However, most of them focus only on the energy consumed by CPU and ignore the remaining hardware, e.g., RAM. In this work, we show the considerable impact that RAM can have on total energy consumption, particularly in servers with large amounts of this memory. We also propose three new approaches for dynamic consolidation of virtual machines (VMs) that take into account both CPU and RAM usage. We have implemented and evaluated our proposals in the CloudSim simulator using real-world traces and compared the results with state-of-the-art solutions. By adopting a wider view of the system, our proposals are able to reduce not only energy consumption but also the number of SLA violations, i.e., they provide a better service at a lower cost. / A computação em nuvem tem levado os sistemas distribuídos a um novo patamar, oferecendo recursos computacionais de forma virtualizada, flexível, robusta e escalar. Essas vantagens, no entanto, surgem juntamente com um alto consumo de energia nos centros de dados, ambientes que podem ter até centenas de milhares de servidores. Existem muitas propostas para alcançar eficiência energética em centros de dados para computação em nuvem. Entretanto, muitas propostas consideram apenas o consumo proveniente do uso de CPU e ignoram os demais componentes de hardware, e.g., RAM. Neste trabalho, mostramos o impacto considerável que RAM pode ter sobre o consumo total de energia, principalmente em servidores com grandes quantidades dessa memória. Também propomos três novas abordagens para consolidação dinâmica de máquinas virtuais, levando em conta tanto o consumo de CPU quanto de RAM. Nossas propostas foram implementadas e avaliadas no simulador CloudSim utilizando cargas de trabalho do mundo real. Os resultados foram comparados com soluções do estado-da-arte. Pela adoção de uma visão mais ampla do sistema, nossas propostas não apenas são capazes de reduzir o consumo de energia como também reduzem violações de SLA, i.e., proveem um serviço melhor a um custo mais baixo.

Lättnadsregeln i 11 kap. 15 § LSE ger möjlighet till avdrag för den el som förbrukats i datorhallar. Datorhallsdefintionen avgränsar skattelättnaden till att enbart gälla vissa datacenter enligt 1 kap. 14 § LSE. Skattelättnaderna innebär ett driftstöd, vilket regleras inom statsstödsreglerna. Generellt är statsstöd förbjudet, men Sverige har använt sig av gruppundantaget GBER för att kunna ge stöd till vissa datorhallar med motivationen att det faller in under GBER:s avsnitt för miljöskydd. Dagens utformning av stödmottagar-formuleringen enligt LSE kopplat till skattelättnadsregeln i 11 kap. 15 § LSE uppfyller inte syftet enligt förarbetena rörande skattelättnaderna för datorhallar. Enligt förarbetena framgår det tydligt att syftet är att även colocation-datorhallar är minst lika konkurrensutsatta och elintensiva som andra datorhallar, och därför bör anses lika berättigade till statsstöd som företagsspecifika datorhallar. I 1 kap. 11b § p. 4 framgår dock att stödmottagaren är elförbrukaren, vilket i colocation-sammanhang med största sannolikhet bör ses som colocation-företagens kunder, inte colocation-företagen själva. Detta skiljer sig gentemot de företagsspecifika datorhallarna, vilka förbrukar elen själva i de egna datorhallarna. SKV:s ställningstagande, vilket tolkar begreppet ”förbrukare av el” som ”den som äger utrustningen som elen förbrukas i”, får anses innebära en korrekt tolkning av lagen, så som den nu är utformad. Detta medför att det krävs en lagändring av vem som är stödmottagare i datorhallssammanhang för att syftena med förarbetet ska kunna uppnås. Omformuleringen kan lämpligen ske genom att begreppet stödmottagare, byts från ”förbrukaren av el” till något som tar sikte på själva datorhallen. I nuläget utgår statsstöd till sådana bolag, oavsett verksamhet, som hyr plats för sina servrar hos colocation-datorhallar som uppnår de tekniska kraven på bl.a. installerad effekt för att räknas som datorhall vars elförbrukning ger rätt till stöd. Det skulle möjligen kunna anses att ett så brett spann av stödmottagare inte stämmer överens med vad Sverige angett till kommissionen vid underrättelserna om statsstöd enligt GBER. Eftersom datorhallarna ger många fördelar för Sverige i form av exempelvis inkomster till statskassan och arbetstillfällen, så är det viktigt att Sverige upprätthåller konkurrenskraftiga förutsättningar för att attrahera fler datorhallsföretag. En del av att upprätthålla konkurrenskraften är att ha konkurrenskraftiga regler, däribland konkurrenskraftig prissättning på elen. Jag finner tre lösningar på stödmottagar-problematiken för colocation-företag. Antingen så får man ansöka om stöd istället för att använda sig av gruppundantaget, för att på så vis känna sig säkrare på att stödet blir korrekt utformat, eller separera colocation-regeln från LSE för att komma bort från stödmottagar-problematiken. Det tredje alternativet, vilket jag anser lättast, är att formulera ett tillägg i LSE, gällande vem som anses vara stödmottagare i datorhallssammanhang, exempelvis kopplat till vem som anses vara ägaren till infrastrukturen i datorhallarna. Finlands motsvarighet till vår lättnadsregel slipper uppdelningsproblematiken mellan företagsspecifika datorhallar och colocation-datorhallar, då de ser datorhallsföretagen som skattskyldiga, och då tillämpar en lägre skattesats för elen som datorhallarna förbrukar. LSE skiljer sig dock på flera sätt från den finska lagen. Detta gör att även om inspiration kan inhämtas kring hur fokus bör flyttas för stödmottagar-rollen i datorhallssammanhang till att inbegripa själva datorhallen snarare än elförbrukaren, så är det inte möjligt att kopiera den finska utformningen rakt av heller.

The complex turbulent flow regimes encountered in many thermal-fluid engineering applications have proven resistant to the effective application of systematic design because of the computational expense of model evaluation and the inherent variability of turbulent systems. In this thesis the integration of the Proper Orthogonal Decomposition (POD) for reduced order modeling of turbulent convection with the application of robust design principles is proposed as a practical design approach. The POD has been used successfully to create low dimensional steady state flow models within a prescribed range of parameters. The underlying foundation of robust design is to determine superior solutions to design problems by minimizing the effects of variation on system performance, without eliminating their causes. The integration of these constructs utilizing the compromise Decision Support Problem (DSP) results in an efficient, effective robust design approach for complex turbulent convective systems. The efficacy of the approach is illustrated through application to the configuration of data center server cabinets. Data centers are computing infrastructures that house large quantities of data processing equipment. The data processing equipment is stored in 2 m high enclosures known as cabinets. The demand for increased computational performance has led to very high power density cabinet design, with a single cabinet dissipating up to 20 kW. The computer servers are cooled by turbulent convection and have unsteady heat generation and cooling air flows, yielding substantial inherent variability, yet require some of the most stringent operational requirements of any engineering system. Through variation of the power load distribution and flow parameters, such as the rate of cooling air supplied, thermally efficient configurations that are insensitive to variations in operating conditions are determined. This robust design approach is applied to three common data center server cabinet designs, in increasing levels of modeling detail and complexity. Results of the application of this approach to the example problems studied show that the resulting thermally efficient configurations are capable of dissipating up to a 50% greater heat load and 15% decrease in the temperature variability using the same cooling infrastructure. These results are validated rigorously, including comparison of detailed CFD simulations with experimentally gathered temperature data of a mock server cabinet. Finally, with the approach validated, augmentations to the approach are considered for multi-scale design, extending approaches domain of applicability.

Data centers are computing infrastructure facilities that house arrays of electronic racks containing high power dissipation data processing and storage equipment whose temperature must be maintained within allowable limits. In this research, the sustainable and reliable operations of the electronic equipment in data centers are shown to be possible through the Open Engineering Systems paradigm. A design approach is developed to bring adaptability and robustness, two main features of open systems, in multi-scale convective systems such as data centers. The presented approach is centered on the integration of three constructs: a) Proper Orthogonal Decomposition (POD) based multi-scale modeling, b) compromise Decision Support Problem (cDSP), and c) robust design to overcome the challenges in thermal-fluid modeling, having multiple objectives, and inherent variability management, respectively. Two new POD based reduced order thermal modeling methods are presented to simulate multi-parameter dependent temperature field in multi-scale thermal/fluid systems such as data centers. The methods are verified to achieve an adaptable, robust, and energy efficient thermal design of an air-cooled data center cell with an annual increase in the power consumption for the next ten years. Also, a simpler reduced order modeling approach centered on POD technique with modal coefficient interpolation is validated against experimental measurements in an operational data center facility.

Time series data arise in many applications, from motion capture, environmental monitoring, temperatures in data centers, to physiological signals in health care. In the thesis, I will focus on the theme of learning and mining large collections of co-evolving sequences, with the goal of developing fast algorithms for finding patterns, summarization, and anomalies. In particular, this thesis will answer the following recurring challenges for time series: 1. Forecasting and imputation: How to do forecasting and to recover missing values in time series data? 2. Pattern discovery and summarization: How to identify the patterns in the time sequences that would facilitate further mining tasks such as compression, segmentation and anomaly detection? 3. Similarity and feature extraction: How to extract compact and meaningful features from multiple co-evolving sequences that will enable better clustering and similarity queries of time series? 4. Scale up: How to handle large data sets on modern computing hardware? We develop models to mine time series with missing values, to extract compact representation from time sequences, to segment the sequences, and to do forecasting. For large scale data, we propose algorithms for learning time series models, in particular, including Linear Dynamical Systems (LDS) and Hidden Markov Models (HMM). We also develop a distributed algorithm for finding patterns in large web-click streams. Our thesis will present special models and algorithms that incorporate domain knowledge. For motion capture, we will describe the natural motion stitching and occlusion filling for human motion. In particular, we provide a metric for evaluating the naturalness of motion stitching, based which we choose the best stitching. Thanks to domain knowledge (body structure and bone lengths), our algorithm is capable of recovering occlusions in mocap sequences, better in accuracy and longer in missing period. We also develop an algorithm for forecasting thermal conditions in a warehouse-sized data center. The forecast will help us control and manage the data center in a energy-efficient way, which can save a significant percentage of electric power consumption in data centers.