910 research outputs found

    A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

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    Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

    Analyse the Performance of Mobile Peer to Peer Network using Ant Colony Optimization

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    A mobile peer-to-peer computer network is the one in which each computer in the network can act as a client or server for the other computers in the network. The communication process among the nodes in the mobile peer to peer network requires more no of messages. Due to this large number of messages passing, propose an interconnection structure called distributed Spanning Tree (DST) and it improves the efficiency of the mobile peer to peer network. The proposed method improves the data availability and consistency across the entire network and also reduces the data latency and the required number of message passes for any specific application in the network. Further to enhance the effectiveness of the proposed system, the DST network is optimized with the Ant Colony Optimization method. It gives the optimal solution of the DST method and increased availability, enhanced consistency and scalability of the network. The simulation results shows that reduces the number of message sent for any specific application and average delay and increases the packet delivery ratio in the network

    Data replication and update propagation in XML P2P data management systems

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    XML P2P data management systems are P2P systems that use XML as the underlying data format shared between peers in the network. These systems aim to bring the benefits of XML and P2P systems to the distributed data management field. However, P2P systems are known for their lack of central control and high degree of autonomy. Peers may leave the network at any time at will, increasing the risk of data loss. Despite this, most research in XML P2P systems focus on novel and efficient XML indexing and retrieval techniques. Mechanisms for ensuring data availability in XML P2P systems has received comparatively little attention. This project attempts to address this issue. We design an XML P2P data management framework to improve data availability. This framework includes mechanisms for wide-spread data replication, replica location and update propagation. It allows XML documents to be broken down into fragments. By doing so, we aim to reduce the cost of replicating data by distributing smaller XML fragments throughout the network rather than entire documents. To tackle the data replication problem, we propose a suite of selection and placement algorithms that may be interchanged to form a particular replication strategy. To support the placement of replicas anywhere in the network, we use a Fragment Location Catalogue, a global index that maintains the locations of replicas. We also propose a lazy update propagation algorithm to propagate updates to replicas. Experiments show that the data replication algorithms improve data availability in our experimental network environment. We also find that breaking XML documents into smaller pieces and replicating those instead of whole XML documents considerably reduces the replication cost, but at the price of some loss in data availability. For the update propagation tests, we find that the probability that queries return up-to-date results increases, but improvements to the algorithm are necessary to handle environments with high update rates

    Context-aware collaborative storage and programming for mobile users

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    Since people generate and access most digital content from mobile devices, novel innovative mobile apps and services are possible. Most people are interested in sharing this content with communities defined by friendship, similar interests, or geography in exchange for valuable services from these innovative apps. At the same time, they want to own and control their content. Collaborative mobile computing is an ideal choice for this situation. However, due to the distributed nature of this computing environment and the limited resources on mobile devices, maintaining content availability and storage fairness as well as providing efficient programming frameworks are challenging. This dissertation explores several techniques to improve these shortcomings of collaborative mobile computing platforms. First, it proposes a medley of three techniques into one system, MobiStore, that offers content availability in mobile peer-to-peer networks: topology maintenance with robust connectivity, structural reorientation based on the current state of the network, and gossip-based hierarchical updates. Experimental results showed that MobiStore outperforms a state-of-the-art comparison system in terms of content availability and resource usage fairness. Next, the dissertation explores the usage of social relationship properties (i.e., network centrality) to improve the fairness of resource allocation for collaborative computing in peer-to-peer online social networks. The challenge is how to provide fairness in content replication for P2P-OSN, given that the peers in these networks exchange information only with one-hop neighbors. The proposed solution provides fairness by selecting the peers to replicate content based on their potential to introduce the storage skewness, which is determined from their structural properties in the network. The proposed solution, Philia, achieves higher content availability and storage fairness than several comparison systems. The dissertation concludes with a high-level distributed programming model, which efficiently uses computing resources on a cloud-assisted, collaborative mobile computing platform. This platform pairs mobile devices with virtual machines (VMs) in the cloud for increased execution performance and availability. On such a platform, two important challenges arise: first, pairing the two computing entities into a seamless computation, communication, and storage unit; and second, using the computing resources in a cost-effective way. This dissertation proposes Moitree, a distributed programming model and middleware that translates high-level programming constructs into events and provides the illusion of a single computing entity over the mobile-VM pairs. From programmers’ viewpoint, the Moitree API models user collaborations into dynamic groups formed over location, time, or social hierarchies. Experimental results from a prototype implementation show that Moitree is scalable, suitable for real-time apps, and can improve the performance of collaborating apps regarding latency and energy consumption

    Search strategies in unstructured overlays

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    Trabalho de projecto de mestrado em Engenharia Informática, apresentado à Universidade de Lisboa, através da Faculdade de Ciências, 2008Unstructured peer-to-peer networks have a low maintenance cost, high resilience and tolerance to the continuous arrival and departure of nodes. In these networks search is usually performed by flooding, which generates a high number of duplicate messages. To improve scalability, unstructured overlays evolved to a two-tiered architecture where regular nodes rely on special nodes, called supernodes or superpeers, to locate resources, thus reducing the scope of flooding based searches. While this approach takes advantage of node heterogeneity, it makes the overlay less resilient to accidental and malicious faults, and less attractive to users concerned with the consumption of their resources and who may not desire to commit additional resources that are required by nodes selected as superpeers. Another point of concern is churn, defined as the constant entry and departure of nodes. Churn affects both structured and unstructured overlay networks and, in order to build resilient search protocols, it must be taken into account. This dissertation proposes a novel search algorithm, called FASE, which combines a replication policy and a search space division technique to achieve low hop counts using a small number of messages, on unstructured overlays with nonhierarquical topologies. The problem of churn is mitigated by a distributed monitoring algorithm designed with FASE in mind. Simulation results validate FASE efficiency when compared to other search algorithms for peer-to-peer networks. The evaluation of the distributed monitoring algorithm shows that it maintains FASE performance when subjected to churn.Os sistemas peer-to-peer, como aplicações de partilha e distribuição de conteúdos ou voz-sobre-IP, são construídos sobre redes sobrepostas. Redes sobrepostas são redes virtuais que existem sobre uma rede subjacente, em que a topologia da rede sobreposta não tem de ter uma correspondência com a topologia da rede subjacente. Ao contrário das suas congéneres estruturadas, as redes sobrepostas não-estru-turadas não restringem a localização dos seus participantes, ou seja, não limitam a escolha de vizinhos de um dado nó, o que torna a sua manutenção mais simples. O baixo custo de manutenção das redes sobrepostas não-estruturadas torna estas especialmente adequadas para a construção de sistemas peer-to-peer capazes de tolerar o comportamento dinâmico dos seus participantes, uma vez que estas redes são permanentemente afectadas pela entrada e saída de nós na rede, um fénomeno conhecido como churn. O algoritmo de pesquisa mais comum em redes sobrepostas não-estruturadas consiste em inundar a rede, o que origina uma grande quantidade de mensagens duplicadas por cada pesquisa. A escalabilidade destes algoritmos é limitada porque consomem demasiados recursos da rede em sistemas com muitos participantes. Para reduzir o número de mensagens, as redes sobrepostas não-estruturadas podem ser organizadas em topologias hierárquicas. Nestas topologias alguns nós da rede, chamados supernós, assumem um papel mais importante, responsabilizando-se pela localização de objectos. A utilização de supernós cria novos problemas, como a sua selecção e a dependência da rede de uma pequena percentagem dos nós. Esta dissertação apresenta um novo algoritmo de pesquisa, chamado FASE, criado para operar sobre redes sobrepostas não estruturadas com topologias não-hierárquicas. Este algoritmo combina uma política de replicação com uma técnica de divisão do espaço de procura para resolver pesquisas ao alcançe de um número reduzido de saltos com o menor custo possível. Adicionalmente, o algoritmo procura nivelar a contribuição dos participantes, já que todos contribuem de uma forma semelhante para o desempenho da pesquisa. A estratégia seguida pelo algo- ritmo consiste em dividir tanto os nós da rede como as chaves dos seus conteúdos por diferentes “frequências” e replicar chaves nas respectivas frequências, sem, no entanto, limitar a localização de um nó ou impor uma estrutura à rede ou mesmo aplicar uma definição rígida de chave. Com o objectivo de mitigar o problema do churn, é apresentado um algoritmo de monitorização distribuído para as réplicas originadas pelo FASE. Os algoritmos propostos são avaliados através de simulações, que validam a eficiência do FASE quando comparado com outros algoritmos de pesquisa em redes sobrepostas não-estruturadas. É também demonstrado que o FASE mantém o seu desempenho em redes sob o efeito do churn quando combinado com o algoritmo de monitorização
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