256 research outputs found
Towards an efficient indexing and searching model for service discovery in a decentralised environment.
Given the growth and outreach of new information, communication, computing and electronic technologies in various dimensions, the amount of data has explosively increased in the recent years. Centralised systems suffer some limitations to dealing with this issue due to all data is stored in central data centres. Thus, decentralised systems are getting more attention and increasing in popularity. Moreover, efficient service discovery mechanisms have naturally become an essential component in both large-scale and small-scale decentralised systems and. This research study is aimed at modelling a novel efficient indexing and searching model for service discovery in decentralised environments comprising numerous repositories with massive stored services. The main contributions of this research study can be summarised in three components: a novel distributed multilevel indexing model, an optimised searching algorithm and a new simulation environment. Indexing model has been widely used for efficient service discovery. For instance; the inverted index is one of the popular indexing models used for service retrieval in consistent repositories. However, redundancies are inevitable in the inverted index which is significantly time-consuming in the service discovery and retrieval process. This theeis proposes a novel distributed multilevel indexing model (DM-index), which offers an efficient solution for service discovery and retrieval in distributed service repositories comprising massive stored services. The architecture of the proposed indexing model encompasses four hierarchical levels to eliminate redundancy information in service repositories, to narrow the searching space and to reduce the number of traversed services whilst discovering services. Distributed Hash Tables have been widely used to provide data lookup services with logarithmic message costs which only require maintenance of limited amounts of routing states. This thesis develops an optimised searching algorithm, named Double-layer No-redundancy Enhanced Bi-direction Chord (DNEB-Chord), to handle retrieval requests in distributed destination repositories efficiently. This DNEB-Chord algorithm achieves faster routing performances with the double-layer routing mechanism and optimal routing index. The efficiency of the developed indexing and searching model is evaluated through theoretical analysis and experimental evaluation in a newly developed simulation environment, named Distributed Multilevel Bi-direction Simulator (DMBSim), which can be used as cost efficient tool for exploring various service configurations, user retrieval requirements and other parameter settings. Both the theoretical validation and experimental evaluations demonstrate that the service discovery efficiency of the DM-index outperforms the sequential index and inverted index configurations. Furthermore, the experimental evaluation results demostrate that the DNEB-Chord algorithm performs better than the Chord in terms of reducing the incurred hop counts. Finally, simulation results demonstrate that the proposed indexing and searching model can achieve better service discovery performances in large-scale decentralised environments comprising numerous repositories with massive stored services.N/
A Location-Aware Middleware Framework for Collaborative Visual Information Discovery and Retrieval
This work addresses the problem of scalable location-aware distributed indexing to enable the leveraging of collaborative effort for the construction and maintenance of world-scale visual maps and models which could support numerous activities including navigation, visual localization, persistent surveillance, structure from motion, and hazard or disaster detection. Current distributed approaches to mapping and modeling fail to incorporate global geospatial addressing and are limited in their functionality to customize search. Our solution is a peer-to-peer middleware framework based on XOR distance routing which employs a Hilbert Space curve addressing scheme in a novel distributed geographic index. This allows for a universal addressing scheme supporting publish and search in dynamic environments while ensuring global availability of the model and scalability with respect to geographic size and number of users. The framework is evaluated using large-scale network simulations and a search application that supports visual navigation in real-world experiments
Peer-to-Peer Networks and Computation: Current Trends and Future Perspectives
This research papers examines the state-of-the-art in the area of P2P networks/computation. It attempts to identify the challenges that confront the community of P2P researchers and developers, which need to be addressed before the potential of P2P-based systems, can be effectively realized beyond content distribution and file-sharing applications to build real-world, intelligent and commercial software systems. Future perspectives and some thoughts on the evolution of P2P-based systems are also provided
Intelligent query processing in P2P networks: semantic issues and routing algorithms
P2P networks have become a commonly used way of disseminating content on the Internet. In this context, constructing efficient and distributed P2P routing algorithms for complex environments that include a huge number of distributed nodes with different computing and network capabilities is a major challenge. In the last years, query routing algorithms have evolved by taking into account different features (provenance, nodes' history, topic similarity, etc.). Such features are usually stored in auxiliary data structures (tables, matrices, etc.), which provide an extra knowledge engineering layer on top of the network, resulting in an added semantic value for specifying algorithms for efficient query routing. This article examines the main existing algorithms for query routing in unstructured P2P networks in which semantic aspects play a major role. A general comparative analysis is included, associated with a taxonomy of P2P networks based on their degree of decentralization and the different approaches adopted to exploit the available semantic aspects.Fil: Nicolini, Ana Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Lorenzetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
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
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