With the advances of technology and the popularization of mobile devices, the need of researching and discussing subjects related to mobile devices has raised. One of the subjects that needs to be further analyzed is data replication. This study investigates data replication on mobile devices focusing on power consumption. It presents four different scenarios that propose, describe, apply and evaluate data replication mechanisms, with the purpose of finding the best scenario that presents less energy consumption. In order to make the experiments, Sun SPOT was chosen as a mobile device. This device is fully programmed in a java environment. A different software was created in each scenario in order to verify the performance of the mobile devices regarding energy saving. The results found did not meet the expectations. While trying to find the best scenario a hardware limitation was found. Although software can be easily changed to fix errors, hardware cannot be changed as easily. The implications for the hardware limitation found in this study prevented the results to be optimal. The results found also imply that new hardware should be used in further experimentation. As this study proved to be limited, it suggests that additional studies should be carried out applying the new version of the hardware used in this study.

This paper revisits Grunfeld's well-known investment data, one of the most widely used data sets in all of econometrics, on the occasion of their 50th anniversary. It presents, apparently for the first time after the publication of the original Chicago Ph.D. thesis, the full data set and points out errors and inconsistencies in several currently available versions. It also revisits a number of empirical studies from the literature of the last five decades. / Series: Research Report Series / Department of Statistics and Mathematics

Certain scientific application domains, such as High-Energy Physics or Earth Observation, are expected to produce several Petabytes (220 Gigabyes) of data that is analyzed and evaluated by the scientists all over the world. In the context of data grid technology, data replication is mostly used to reduce access latency and bandwidth consumption. In this thesis, we adopt the typical Data Grid architecture, three kinds of nodes: server, cache, and client nodes. A server node represents a main storage site. A client node represents a site where data access requests are generated, and a cache node represents an intermediate storage site. However, the access latency of the hierarchical storage system may be of the order of seconds up to hours. The static replication strategy can be used to improve such long delay; however, it cannot adapt to changes of users¡¦ behaviors. Therefore, the dynamic data replication strategy is used in Data Grids. Three fundamental design issues in a dynamic replication strategy are: (1) when to create the replicas, (2) which files to be replicated, and (3) where the replicas to be placed. Two of well known replication strategies are Fast-Spread and Cascading, which can work well for different kinds of access patterns individually. For example, the Fast-Spread strategy works well for random access patterns, and the Cascading strategy works well for the patterns with the properties of localities. However, for so many different access patterns, if we use a strategy for one kind of access patterns and another strategy for another kind of access patterns, the system may become too complex. Therefore, in this thesis, we propose one strategy which can work for any kind of access patterns. We propose a replication approach, a Different Threshold (DT) approach to data replication in Data Grids, which can be dynamically adapted to several kinds of access patterns and provide even better performance than Cascading and Fast-Spread strategies. In our approach, there are different thresholds for different layers. Based on this approach, first, we propose a static DT strategy in which the threshold at each layer is fixed. So, by carefully adjusting the difference between the thresholds Ti, where i is the i-th layer of the tree structure, we can even provide the better performance than the above two well-known strategies. Moreover, among large amount of different data files, there may exist some hot data files. Those files which have been mostly requested are hot data files. To reduce the number of requests for the hot files, next, we propose the dynamic DT strategy. In the dynamic DT strategy, each data file even has its own threshold. We let data replication of hot files occur earlier than others by decreasing the thresholds of hot files earlier than the normal ones. From our simulation results, we show that the response time in our static DT strategy is less than that in the Cascading and the Fast-Spread strategies. Moreover, we can show that the performance of the dynamic DT strategy is better than that of the static DT strategy.

The main purpose of this research is to incorporate additional higher-level semantics into the existing data replication strategies in such a way that their flexibility and performance can be improved in favour of both data providers and consumers. The resulting approach from this research is referred to as the selective data replication system. With this system, the data that has been updated by a data provider is captured and batched into messages known as update notifications. Once update notifications are received by data consumers, they are used to evaluate so-called update policies, which are specified by data consumers containing details on when data replications need to occur and what data needs to be updated during the replications.

The advancement in computing in the last three decades has introduced many devices in our daily lives including personal computers, laptops, cellular devices and many more. The data we need for our processing needs is scattered among these devices. The availability of all the scattered data in the devices in use associated to an individual user as one is achieved in a Personal Information Environment. Data recharging is a technique used to achieve a Personal Information Environment for an individual user using data replication. In this thesis, we propose a data recharging scheme for an individual user’s Personal Information Environment. We study the data availability to a user by conducting a simulation using the data recharging algorithm. This data recharging approach is achieved by using master-slave data replication technique. / Thesis (Master, Computing) -- Queen's University, 2009-08-06 00:18:00.19

The main purpose of this research is to incorporate additional higher-level semantics into the existing data replication strategies in such a way that their flexibility and performance can be improved in favour of both data providers and consumers. The resulting approach from this research is referred to as the selective data replication system. With this system, the data that has been updated by a data provider is captured and batched into messages known as update notifications. Once update notifications are received by data consumers, they are used to evaluate so-called update policies, which are specified by data consumers containing details on when data replications need to occur and what data needs to be updated during the replications.

É um resultado conhecido que em Data Grids, onde o processamento envolve grandes quantidades de dados, pode ser mais eficaz escalonar os processos para execução nos sites que já dispõem dos dados do que transferir os dados para um site onde o processo que irá necessitar deles foi escalonado. Os estudos existentes se baseiam em pequenas quantidades de sites, com conhecimento centralizado sobre o estado dos diversos sites. Essa opção não é escalável para Grids com grande número de participantes. Este trabalho analisa versões distribuídas com informação local para os algoritmos de escalonamento de processo e replicação de dados, mostrando o efeito das topologias de interconexão de sites no desempenho desses. É observado que, considerando a existência apenas de informações locais devido às restrições topologicas, resultados diferentes quanto aos melhores algoritmos de escalonamento de processos e replicação de dados são encontrados. / It is a known result that in Data Grids, where the processing involves large amounts of data, can be more effective schedule processes to run on sites that already have the data than transfering data to a site where the process that will require them was installed. The existing studies are based on small numbers of sites, with centralized knowledge about the state of the various sites. This option is not scalable for grids with large numbers of participants. This paper will propose distributed versions with local information for process scheduling algorithms and data replication, showing the effect of interconnect topologies on the performance of these sites. It is observed that, considering the existence of only local information due to topological constraints, different results related to the best scheduling algorithms and data replication processes are found.

A modelagem evolutiva de bancos de dados é necessária devido às frequentes mudanças de requisitos das aplicações. O desafio é ainda maior quando o banco de dados tem de atender simultaneamente a várias aplicações. A solução proposta por Scott Ambler para evolução utiliza refatorações e define um período de transição, durante o qual tanto o esquema antigo quanto o novo coexistem e os dados são replicados por meio de um processo síncrono que apresenta várias dificuldades, como a interferência no funcionamento normal das aplicações. Para minimizar essas dificuldades, esta tese propõe um processo assíncrono para manter atualizados esses esquemas e apresenta um protótipo de uma ferramenta para auxiliar as evoluções dos bancos de dados. A proposta foi validada por meio de um experimento em laboratório que comparou a solução aqui apresentada com a proposta por Ambler. / Evolutionary database modeling is necessary due to the frequent changes in application requirements. The challenge is greater when the database must support multiple applications simultaneously. The solution for evolution proposed by Scott Ambler is refactoring with a transition period, during which both the old and the new database schemas coexist and data is replicated via a synchronous process, what brings several difficulties, such as interference with the normal operation of applications. To minimize these difficulties, this thesis proposes an asynchronous process to keep these schemas updated and presents a prototype tool to evolve databases. The proposal was validated by a laboratory experiment in which the solution presented here was compared with the one proposed by Ambler.

É um resultado conhecido que em Data Grids, onde o processamento envolve grandes quantidades de dados, pode ser mais eficaz escalonar os processos para execução nos sites que já dispõem dos dados do que transferir os dados para um site onde o processo que irá necessitar deles foi escalonado. Os estudos existentes se baseiam em pequenas quantidades de sites, com conhecimento centralizado sobre o estado dos diversos sites. Essa opção não é escalável para Grids com grande número de participantes. Este trabalho analisa versões distribuídas com informação local para os algoritmos de escalonamento de processo e replicação de dados, mostrando o efeito das topologias de interconexão de sites no desempenho desses. É observado que, considerando a existência apenas de informações locais devido às restrições topologicas, resultados diferentes quanto aos melhores algoritmos de escalonamento de processos e replicação de dados são encontrados. / It is a known result that in Data Grids, where the processing involves large amounts of data, can be more effective schedule processes to run on sites that already have the data than transfering data to a site where the process that will require them was installed. The existing studies are based on small numbers of sites, with centralized knowledge about the state of the various sites. This option is not scalable for grids with large numbers of participants. This paper will propose distributed versions with local information for process scheduling algorithms and data replication, showing the effect of interconnect topologies on the performance of these sites. It is observed that, considering the existence of only local information due to topological constraints, different results related to the best scheduling algorithms and data replication processes are found.

<p>Distributed real-time databases can be used to support data sharing</p><p>for applications in wireless ad-hoc networks. In such networks, topology changes frequently and partitions may be unpredictable and last for an unbounded period. In this thesis, the existing database replication protocol PRiDe is extended to handle such long-lasting partitions. The protocol uses optimistic and detached replication to provide predictable response times in unpredictable networks and forward conflict resolution to guarantee progress.</p><p>The extension, pPRiDe, combines update and state transfer strategies. Update transfer for intra-partition communication can reduce bandwidth usage and ease conflict resolution. State transfer for inter partition conflicts removes dependency on a common state between partitions prior to the merge to apply update messages on. This makes the resource usage independent of the life span of partitions. This independence comes at the cost of global data stability guarantees and pPRiDe can thus only provide per partition guarantees. The protocol supports application specific conflict resolution routines for both</p><p>state and update conflicts. A basic simulator for mobile ad-hoc networks has been developed to validate that pPRiDe provides eventual consistency.</p><p>pPRiDe shows that a hybrid approach to change propagation strategy can be beneficial in networks where collaboration by data sharing within long lasting partitions and predictable resource usage is necessary. These types of systems already require the conflict management routines necessary for pPRiDe and can benefit from an existing protocol.</p><p>In addition to pPRiDe and the simulator this thesis provides a flexible object database suitable for future works and an implementation of PRiDe on top of that database.</p>