The cloud, in the past few years, has become the preferred platform for hosting web applications. Many of these web applications store their data in a distributed cloud storage system, which greatly simplifies application development and provides increased availability and reliability. However, with increasing user demand for web applications, these cloud storage systems often become the performance bottleneck. To address the cloud's performance demands, many storage system features, such as strong consistency and transactional support, are often omitted in favour of performance. Nonetheless, transactions remain necessary to ensure data integrity and application correctness. In this thesis, we introduce CrossStitch, which is an efficient transaction processing framework for distributed key-value storage systems. CrossStitch supports general transactions, where transactions include both computation and key accesses. It is specifically optimized for short-lived transactions that are typical of cloud-deployed web applications. In CrossStitch, a transaction is partitioned into a series of components that form a transaction chain. These components are executed and the transaction is propagated along the storage servers instead of being executed on the application server. This chained structure, in which servers only communicate with their immediate neighbours, enables CrossStitch to implement a pipelined version of two-phase commit to ensure transactional atomicity. CrossStitch is able to eliminate a significant amount of setup overhead using this structure by executing the transaction and the atomic commit protocol concurrently. Therefore, CrossStitch provides low latency and efficient transactional support for cloud storage systems. Our evaluation demonstrates that CrossStitch is a scalable and efficient transaction processing framework for web transactions.

Elastic deformation has wide applications in medical simulations, therefore when it comes to designing physical behavior of objects for realistic training applications, determining material parameters so that objects behave in a desired way becomes a crucial. In this work we consider the problem of elasticity parameter estimation for deformable bodies, which is important for accurate medical simulations. Our work has two major steps: the first step is the data acquisition and preparation, and the second step is the parameter estimation. The experimental setup for data acquisition consists of depth and force sensors. Surface deformations are acquired as a series of images along with the corresponding applied forces. The contact point of the force sensor on the surface is found visually and the corresponding applied forces are acquired directly from the force sensor. A complete mesh deformation which is obtained from a surface tracking method is employed along with force measurements in the elasticity parameter estimation method. Our approach to estimate the physical material properties is based on an inverse linear finite element method. We have experimented with two approaches to optimize the elasticity parameters: a linear iterative method and a force-displacement error minimization method. The two methods were tested on the simulation data, and the second method was tested on three deformable objects. The results are presented for the data captured by two different depth sensors. The result is a set of two parameters, the Young's modulus and the Poisson's ratio, which represents the stiffness of the object under test.

This thesis focuses on computatal problems regarding the allocation of resources within a data center that services a cloud. This problem is formally know as Resource Consolidation Managmenet (RCM). In this thesis we analyse current RCM methods from the literature with respect to computational problem defintions and propose a framework to allow the classification and comparison of RCM solutions. With a decade of research in the field, this framework should be intuitive such that any researcher can easily use it to define computational problems in the field of RCM and reverse engineer problem definitions from exisiting solutions for RCM Problems. Finally our framework should be extendable: as the field continues to grow, the framework should be able to adapt to meet future needs. Besides presenting the framework, we analyse computational problems obtained by the framework in terms of its classical complexity. We show several of those problems to be NP-complete and discuss variants that are solvable in polynomial time. A further contribution is the exploration of different comparison tools for solutions of RCM problems. / Graduate

No description available.

Typescript. / Bibliography: leaves [57]-61. / ix, 63, A-2, B-2 l illus

Thesis (Ph. D.)--University of Oklahoma, 1994. / Includes bibliographical references (247-256 leaves).

Ce travail doctoral s’intéresse aux impacts sécuritaires de l’usage du cloud computing dans les petites et moyennes entreprises (PME). Il repose sur une méthodologie de recherche mixte, à la fois qualitative et quantitative, en adoptant une posture épistémologique orientée réalisme critique (Mingers, 2002,2004). Son objectif est de mettre en lumière les éléments d’une théorie d’explication et de prédiction (Gregor, 2006) de la portée sécuritaire de l’adoption du cloud computing dans les petites et moyennes entreprises. Les résultats de notre recherche se matérialisent au travers la présentation et la publication de quatre travaux académiques : Un premier article publié (un modèle d’acheminement des données depuis les PME vers ses fournisseurs cloud potentiels), deux articles acceptés pour publication (un modèle du transfert des risques SI dans un écosystème cloud computing, une mise en lumière de la délégation du rôle du DSI) et un dernier article en cours d’évaluation (la caractérisation de la réversibilité d’un service cloud). La thèse contribue à une meilleure compréhension des conséquences sécuritaires inter- et intra-organisationnelles, entre autres à travers la mobilisation des théories de la firme et la modélisation mathématique. Elle propose, en outre, un nouveau coefficient d’estimation de la concordance pour des hypothèses indépendantes, / This doctoral work focuses on security impacts of the cloud computing use in SMEs. It is elaborated through a mixed research methodology by adopting a critical realism position (Mingers, 2002, 2004). Its objective is to implement a theory of explanation and prediction (Gregor, 2006) applied to the safe scope of the cloud computing adoption in small and medium enterprises. The results of our research are materialized through the publication of an article (a model of data transmission from SMEs to its potential cloud suppliers) two articles accepted for publication (a model of the transfer of risks SI in a cloud computing ecosystem, highlighting the delegation of the role of the CIO) and an article under evaluation (the characterization of the reversibility of a cloud service). The thesis contributes to a better understanding of the inter- and intra-organizational security consequences, among others through the mobilization of firm theories and the mathematical modeling. It also proposes a new coefficient of agreement estimation for independent assumptions.

Submitted by Irene Nascimento (irene.kessia@ufpe.br) on 2016-10-18T19:25:38Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) mestrado_thiago_jamir.pdf: 1864217 bytes, checksum: 4e432bf2e6196fc2e2fb739007114e2e (MD5) / Made available in DSpace on 2016-10-18T19:25:38Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) mestrado_thiago_jamir.pdf: 1864217 bytes, checksum: 4e432bf2e6196fc2e2fb739007114e2e (MD5) Previous issue date: 2014-04-05 / Nos últimos anos, o volume de dados gerados por indivíduos e organizações tem crescido exponencialmente. Estima-se que globalmente existia 2.7 zetabytes em 2012 e esse número tem dobrado a cada dois anos. Além disso, com a popularização de dispositivos móveis conectados, cresceu-se a necessidade de que usuários tenham acesso a arquivos de forma ubíqua. As soluções tradicionais de backup e armazenamento de arquivos online já não conseguem suprir as necessidades atuais dos usuários. A utilização de Cloud Storage para backup e sincronização de arquivos vem a ser uma ferramenta de grande valia para esse tipo de problema. Porém, implementar um sistema deste tipo vem a ser um desafio tecnológico relevante. Nesse sentido, este trabalho se propõe a resolver o problema de armazenamento de arquivos, propondo uma arquitetura de Cloud Storage para armazenamento de arquivos. Ao longo trabalho, é feita uma análise dos principais direcionadores de negócio para Cloud Storage e armazenamento de arquivos, levantando insumos para se projetar uma arquitetura. Tal arquitetura é descrita em nível de detalhe para que se possa ser implementada. Finalmente, o trabalho é validado através de uma avaliação de arquitetura cuja metodologia foi adaptada de acordo com as características da equipe de avaliação. / In the last years, the amount of data generated by individuals and organizations has grown exponentially. It is estimated that there were 2.7 zettabytes of global data in 2012, and this number has doubled each two years. In addition to this, with the popularization of mobile connected devices, the user’s need to have ubiquous access has grown. Traditional solutions for backup and online file storage can no longer meet the current needs. The use of cloud storage for backup and file synchronization becomes a tool of great value to this kind of problem. However, implementing such a system becomes a significant technological challenge. Thus, this works proposes to solve the problem of storing files, designing a Cloud Storage architecture for storing archives. Throughout work, an analysis of the key business drivers for Cloud Storage and File storage is done by lifting inputs for designing an architecture. This architecture is described in detail for level that can be implemented. Finally, the work is validated through an evaluation of architecture whose methodology was adapted according to the characteristics of the evaluation team.

Managing information security in the cloud is a challenge. Traditional checklist approaches to standards compliance might well provide compliance, but may not provide adequate security assurance. The complexity of cloud relationships must be acknowledged and explicitly managed by recognising the implications of the self-interest of each party involved. We develop a conceptual modelling framework for cloud security assurance that can be used as a starting point for achieving effective continuous security assurance, together with a high level of compliance.

Elastic deformation has wide applications in medical simulations, therefore when it comes to designing physical behavior of objects for realistic training applications, determining material parameters so that objects behave in a desired way becomes a crucial. In this work we consider the problem of elasticity parameter estimation for deformable bodies, which is important for accurate medical simulations. Our work has two major steps: the first step is the data acquisition and preparation, and the second step is the parameter estimation. The experimental setup for data acquisition consists of depth and force sensors. Surface deformations are acquired as a series of images along with the corresponding applied forces. The contact point of the force sensor on the surface is found visually and the corresponding applied forces are acquired directly from the force sensor. A complete mesh deformation which is obtained from a surface tracking method is employed along with force measurements in the elasticity parameter estimation method. Our approach to estimate the physical material properties is based on an inverse linear finite element method. We have experimented with two approaches to optimize the elasticity parameters: a linear iterative method and a force-displacement error minimization method. The two methods were tested on the simulation data, and the second method was tested on three deformable objects. The results are presented for the data captured by two different depth sensors. The result is a set of two parameters, the Young's modulus and the Poisson's ratio, which represents the stiffness of the object under test.