Grid computing is a virtualized distributed computing environment aimed at enabling the sharing of geographically distributed resources. Grid resources have traditionally consisted of dedicated supercomputers, clusters, or storage units. With the present ubiquitous network connections and the growing computational and storage capabilities of modem everyday-use computers, more resources such as PCs, devices (e.g., PDAs and sensors), applications, and services are on grid networks. Grid is expected to evolve from a computing and data management facility to a pervasive, world-wide resource-sharing infrastructure. To fully utilize the wide range of grid resources, effective resource discovery mechanisms are required. However, resource discovery in a global-scale grid is challenging due to the considerable diversity, large number, dynamic behavior, and geographical distribution of the resources. The resource discovery technology required to achieve the ambitious global grid vision is still in its infancy, and existing applications have difficulties in achieving both rich searchability and good scalability. In this thesis, we investigate the resource discovery problem for open-networked global-scale grids. In particular, we propose a distributed semantics-based discovery framework. We show how this framework can be used to address the discovery problem in such grids and improve three aspects of performance: expressiveness, scalability, and efficiency. Expressiveness is the first characteristic that a grid resource-searching mechanism should have. Most existing search systems use simple keyword-based lookups, which limit the searchability of the system. Our framework improves search expressiveness from two directions: First, it uses a semantic metadata scheme to provide users with a rich and flexible representation mechanism, to enable effective descriptions of desired resource properties and query requirements. Second, we employ ontological domain knowledge to assist in the search process. The system is thus able to understand the semantics of query requests according to their meanings in a specific domain; this procedure helps the system to locate only semantically related results. The more expressive the resource description and query request, however, the more difficult it is to design a scalable and efficient search mechanism. We ensure scalability by reconfiguring the network with respect to shared ontologies. This reconfiguration partitions the large unorganized search space into multiple well-organized semantically related sub-spaces that we call semantic virtual organizations. Semantic virtual organizations help to discriminatively distribute resource information and queries to related nodes, thus reducing the search space and improving scalability. To further improve the efficiency of searching the virtual organizations, we propose two semantics-based resource-integrating and searching systems: GONID and OntoSum. These two systems address searching problems for applications based on different network topologies: structured and unstructured peer-to-peer overlay networks. Queries in the search systems are processed in a transparent way, so that users accessing the data can be insulated from the fact that the information is distributed across different sources and represented with different formats. In both systems, ontological knowledge is decomposed into different coarse-grained elements, and then these elements are indexed with different schemes to fit the requirements of different applications. Resource metadata reasoning, integrating, and searching are based on the index. A complex query can be evaluated by performing relational operations such as select, project, and join on combinations of the indexing elements. We evaluate the performance of our system with extensive simulation experiments, the results of which confirm the effectiveness of the design. In addition, we implement a prototype that incorporates our ontology-based virtual organization formation and semantics-based query mechanisms. Our deployment of the prototype verifies the system's feasibility and its applicability to real-world applications.

A Distributed Event-based System (DEBS) exhibits its desired behavior through its functional components collaborating with each other via event exchanging. Due to loose-coupling and flexibility, DEBS applications have become increasingly popular. Indeed, such systems are expected to appear in various application domains such as large-scale Internet applications and ubiquitous computing. Notwithstanding their popularity, current DEBS applications are still often developed in an informal process and are not modularized. On the individual event level, current DEBS developers can define what events a component can accept and publish, and, by registering event handlers, what action an event can trigger. Currently, developers lack structuring mechanisms for representing event interactions and dependencies in a modular way. While current research has made fruitful contributions to various aspects in the DEBS paradigm, such as, event delivery, event detection and composition, event visibility, its emphasis is on the individual event level. In this thesis, we advocate that by designing a new DEBS metamodel with extended behavioral interfaces and high-level structure mechanisms, we can (1) define an interface-based modular approach to model and design DEBS applications, (2) implement a prototype framework on a P2P network that provides built-in support to our proposed interface-based DEBS development, and (3) provide case studies illustrating the interface-based development process and the applicability of our proposed approach.

A Distributed Event-based System (DEBS) exhibits its desired behavior through its functional components collaborating with each other via event exchanging. Due to loose-coupling and flexibility, DEBS applications have become increasingly popular. Indeed, such systems are expected to appear in various application domains such as large-scale Internet applications and ubiquitous computing. Notwithstanding their popularity, current DEBS applications are still often developed in an informal process and are not modularized. On the individual event level, current DEBS developers can define what events a component can accept and publish, and, by registering event handlers, what action an event can trigger. Currently, developers lack structuring mechanisms for representing event interactions and dependencies in a modular way. While current research has made fruitful contributions to various aspects in the DEBS paradigm, such as, event delivery, event detection and composition, event visibility, its emphasis is on the individual event level. In this thesis, we advocate that by designing a new DEBS metamodel with extended behavioral interfaces and high-level structure mechanisms, we can (1) define an interface-based modular approach to model and design DEBS applications, (2) implement a prototype framework on a P2P network that provides built-in support to our proposed interface-based DEBS development, and (3) provide case studies illustrating the interface-based development process and the applicability of our proposed approach.

As online applications such as online newsgroups, internet game-rooms, online chat-rooms, and peer-to-peer (P2P) resources-sharing systems become popular, online community visualization became a hot research topic. Different forms and metaphors of visualizations focused on various aspects of online communities have been proposed. In this thesis, I propose one prototype of online community visualization which is designed to motivate user contributions in various aspects and stimulate users to participate in the online community more actively. The uneven participation is a well known problem in human society; according to the 80-20 rule, 20% of the people make 80% of contributions, for example, 20% of the employees in a company do 80% of the work. This problem exits in all kinds of online communities, e.g. newsgroups, chat-rooms, but it is particularly crucial for P2P online resources-sharing communities. Such communities do not have a central server and rely solely on the peers not just to provide contributions, but also to ensure the infrastructure. Large P2P file-sharing communities like KaZaA and Limewire can provide the redundancy of peers and resources needed to support the infrastructure and availability of resources. However, when an online community is small, for example, the students in a class, a research group, a department, or a school, the problem of lack of users it is hard to reach a critical mass of user participation, leading to poor service and resource availability, which reduces users interest in participating in the system. To attract users and motivate them to make more contributions into an online resources-sharing community, I propose to use motivational visualization of the community and the contributions of its members. The motivational effect of the visualization is grounded on two theories in social psychology which explain how individuals align their behaviour with each other and with their group (community). In this thesis, I discuss three stages in the design of the visualization and the subsequent redesigns following results from evaluation and user feedback.

The Service Oriented Architecture (SOA) is emerging as a new standard for building large loosely coupled systems. Web Services, the dominant implementation platform for SOA, use a server-centric approach to manage all components. This limits the deployment of Web Services to static domains, since a service invocation will fail if the server component changes its availability or location. <p>This research focuses on the possibilities of integrating P2P technology into the Web Services environment as a means of increasing its robustness. A P2P-Web Services architecture is presented that enables service discovery and service invocations in dynamic environments. The corresponding experiments on the reference system and the simulation system present the characteristics and improvements of the hybrid system.

In today’s world, technology is growing at a fast rate compared at other times. Sales have increased in the smart phone market, which has created new opportunities in pervasive computing. In pervasive computing, nodes enter and leave a network at any time. Within the network, nodes can transfer data to other nodes. The information is not retained in any static location such as a server. The mobile infrastructure requires a way to handle all the information in a dynamic way. The use of a centralized server in a mobile environment creates deterioration in the performance of obtaining information. The main goal of this paper is to provide data persistence using a “substrate” that is inherently not persistent. The data will be stored within the network for availability to all users. Saving data within a network would provide a means to obtain any type of information without relying on the source of where the data came from in the network. Users would also be able to continue downloading where they left off when they return to the network. Consider an environment where people can share music or books. For example, say that John Doe was searching for a particular song to download and in the network Jane has the song that was requested. John decides to download the song without knowing that it is from Jane. Then John decides to leave the network and the download stops. Whenever John rejoins the network the download of his song will continue where he left off, and his ability to access the information will not depend whether or not Jane is present in the network. John may retrieve the file from any other user who has the exact same file. The requested information that the user queries in a search engine will be stored as a metadata within the network, either by other nodes or a temporary server. This allows data to be obtained without relying on the "main user" or creator of the data to be present in the network. The users would also be able to retrieve the data at multiple times. / text

Grid computing is a virtualized distributed computing environment aimed at enabling the sharing of geographically distributed resources. Grid resources have traditionally consisted of dedicated supercomputers, clusters, or storage units. With the present ubiquitous network connections and the growing computational and storage capabilities of modem everyday-use computers, more resources such as PCs, devices (e.g., PDAs and sensors), applications, and services are on grid networks. Grid is expected to evolve from a computing and data management facility to a pervasive, world-wide resource-sharing infrastructure. To fully utilize the wide range of grid resources, effective resource discovery mechanisms are required. However, resource discovery in a global-scale grid is challenging due to the considerable diversity, large number, dynamic behavior, and geographical distribution of the resources. The resource discovery technology required to achieve the ambitious global grid vision is still in its infancy, and existing applications have difficulties in achieving both rich searchability and good scalability. In this thesis, we investigate the resource discovery problem for open-networked global-scale grids. In particular, we propose a distributed semantics-based discovery framework. We show how this framework can be used to address the discovery problem in such grids and improve three aspects of performance: expressiveness, scalability, and efficiency. Expressiveness is the first characteristic that a grid resource-searching mechanism should have. Most existing search systems use simple keyword-based lookups, which limit the searchability of the system. Our framework improves search expressiveness from two directions: First, it uses a semantic metadata scheme to provide users with a rich and flexible representation mechanism, to enable effective descriptions of desired resource properties and query requirements. Second, we employ ontological domain knowledge to assist in the search process. The system is thus able to understand the semantics of query requests according to their meanings in a specific domain; this procedure helps the system to locate only semantically related results. The more expressive the resource description and query request, however, the more difficult it is to design a scalable and efficient search mechanism. We ensure scalability by reconfiguring the network with respect to shared ontologies. This reconfiguration partitions the large unorganized search space into multiple well-organized semantically related sub-spaces that we call semantic virtual organizations. Semantic virtual organizations help to discriminatively distribute resource information and queries to related nodes, thus reducing the search space and improving scalability. To further improve the efficiency of searching the virtual organizations, we propose two semantics-based resource-integrating and searching systems: GONID and OntoSum. These two systems address searching problems for applications based on different network topologies: structured and unstructured peer-to-peer overlay networks. Queries in the search systems are processed in a transparent way, so that users accessing the data can be insulated from the fact that the information is distributed across different sources and represented with different formats. In both systems, ontological knowledge is decomposed into different coarse-grained elements, and then these elements are indexed with different schemes to fit the requirements of different applications. Resource metadata reasoning, integrating, and searching are based on the index. A complex query can be evaluated by performing relational operations such as select, project, and join on combinations of the indexing elements. We evaluate the performance of our system with extensive simulation experiments, the results of which confirm the effectiveness of the design. In addition, we implement a prototype that incorporates our ontology-based virtual organization formation and semantics-based query mechanisms. Our deployment of the prototype verifies the system's feasibility and its applicability to real-world applications.

Las redes Peer-to-Peer (P2P) puras no estructuradas como Gnutella, dónde los nodos se conectan entre sí como pares o iguales, sin roles diferenciados ni jerarquías de ninguna clase, son sistemas distribuidos, dinámicos, sin punto alguno de centralización, que favorecen la robustez y tolerancia a fallos. Sin embargo, la búsqueda de recursos en estos sistemas constituye un problema esencial. El algoritmo de búsqueda BFS de Gnutella genera gran cantidad de tráfico dificultando su escalabilidad. Esta tesis propone un nuevo algoritmo de búsqueda denominado Búsqueda Inteligente Incremental P2P (BII-P2P) en el que los nodos, asistidos por sus redes neuronales locales, propagan selectivamente las solicitudes de búsquedas sólo al subconjunto más apropiado de vecinos. Así se mejora significativamente el algoritmo de Gnutella consiguiendo mayor porcentaje de hallazgos con menor cantidad de tráfico generado sobre la red P2P. El rendimiento de este algoritmo de búsqueda inteligente se ve potenciado por una conveniente estrategia de exploración incremental.

Replication is a popular technique for increasing data availability and improving perfor- mance in peer-to-peer systems. Maintaining freshness of replicated data is challenging due to the high cost of update management. While updates have been studied in structured networks, they have been neglected in unstructured networks. We therefore confront the problem of maintaining fresh replicas of data in unstructured peer-to-peer networks. We propose techniques that leverage path replication to support efficient lazy updates and provide freshness for cached data in these systems using only local knowledge. In addition, we show that locally available information may be used to provide additional guarantees of freshness at an acceptable cost to performance. Through performance simulations based on both synthetic and real-world workloads from big data environments, we demonstrate the effectiveness of our approach.

Made available in DSpace on 2016-08-29T15:33:14Z (GMT). No. of bitstreams: 1 tese_4161_.pdf: 2648809 bytes, checksum: 9d0d29882117ba5d84d7b1eb586817c2 (MD5) Previous issue date: 2011-08-04 / Sistemas Par-a-Par de Video Sob Demanda consolidaram sua importância nos últimos anos. Tal consolidação é decorrente dos elevados ganhos que se pode ter em termos de economia na banda de transmissão dos servidores. Neste trabalho, avalia-se como esta tecnologia pode potencializar os ganhos de transmissão de mídia contínua na Internet. Para atingir este objetivo, a metodologia adotada apoia-se em um ambiente de simulação a nível de pacotes que possui características que permitem capturar iferentes variáveis referentes a dinâmica da Internet, tais como: simulação completa da pilha TCP/IP, considerações sobre topologia de rede e inserção de tráfego de fundo. Na simulação foi implementado um algoritmo de difusão de vídeo P2P VoD e um algoritmo de pré-busca. As análises dos resultados apontam para uma potencial economia de upload no servidor de conteúdo de 43% em um cenário menos idealizado do que a proposta de base que atingiu 73%. Em termos da percepção da qualidade de vídeo dos clientes, o presente trabalho indica que sua experiência pode ser degradada de forma considerável usando UDP quando existe o tráfego de fundo, mesmo com a economia do servidor se mantendo constante. Ainda na percepção dos clientes, percebeu-se também que, embora o uso da pré-busca seja benéfico aos mesmos, o grande fator diferencial na melhor qualidade percebida foi a escolha da camada de transporte apropriada.