5,950 research outputs found

    Performance Analysis of Publish/Subscribe Systems

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    The Desktop Grid offers solutions to overcome several challenges and to answer increasingly needs of scientific computing. Its technology consists mainly in exploiting resources, geographically dispersed, to treat complex applications needing big power of calculation and/or important storage capacity. However, as resources number increases, the need for scalability, self-organisation, dynamic reconfigurations, decentralisation and performance becomes more and more essential. Since such properties are exhibited by P2P systems, the convergence of grid computing and P2P computing seems natural. In this context, this paper evaluates the scalability and performance of P2P tools for discovering and registering services. Three protocols are used for this purpose: Bonjour, Avahi and Free-Pastry. We have studied the behaviour of theses protocols related to two criteria: the elapsed time for registrations services and the needed time to discover new services. Our aim is to analyse these results in order to choose the best protocol we can use in order to create a decentralised middleware for desktop grid

    Building Near-Real-Time Processing Pipelines with the Spark-MPI Platform

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    Advances in detectors and computational technologies provide new opportunities for applied research and the fundamental sciences. Concurrently, dramatic increases in the three Vs (Volume, Velocity, and Variety) of experimental data and the scale of computational tasks produced the demand for new real-time processing systems at experimental facilities. Recently, this demand was addressed by the Spark-MPI approach connecting the Spark data-intensive platform with the MPI high-performance framework. In contrast with existing data management and analytics systems, Spark introduced a new middleware based on resilient distributed datasets (RDDs), which decoupled various data sources from high-level processing algorithms. The RDD middleware significantly advanced the scope of data-intensive applications, spreading from SQL queries to machine learning to graph processing. Spark-MPI further extended the Spark ecosystem with the MPI applications using the Process Management Interface. The paper explores this integrated platform within the context of online ptychographic and tomographic reconstruction pipelines.Comment: New York Scientific Data Summit, August 6-9, 201

    An innovative collaborative high-performance platform for simulation

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    This paper presents an innovative collaborative visualization platform for the simulation-based design applications. Following the scope and the main objectives, the general architecture based on the internet standard technologies is explained. Based on a multi-domain approach, several demonstrators are involved crossing interests of industrial and academic communities. Related to the field of process engineering, we adapt and deploy a web-based architecture research application on the targeted platform

    Experiences in teaching grid computing to advanced level students

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    The development of teaching materials for future software engineers is critical to the long term success of the grid. At present however there is considerable turmoil in the grid community both within the standards and the technology base underpinning these standards. In this context, it is especially challenging to develop teaching materials that have some sort of lifetime beyond the next wave of grid middleware and standards. In addition, the current way in which grid security is supported and delivered has two key problems. Firstly in the case of the UK e-Science community, scalability issues arise from a central certificate authority. Secondly, the current security mechanisms used by the grid community are not line grained enough. In this paper we outline how these issues are being addressed through the development of a grid computing module supported by an advanced authorisation infrastructure at the University of Glasgow

    Proof-of-Concept Application - Annual Report Year 1

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    In this document the Cat-COVITE Application for use in the CATNETS Project is introduced and motivated. Furthermore an introduction to the catallactic middleware and Web Services Agreement (WS-Agreement) concepts is given as a basis for the future work. Requirements for the application of Cat-COVITE with in catallactic systems are analysed. Finally the integration of the Cat-COVITE application and the catallactic middleware is described. --Grid Computing

    Big Data Model Simulation on a Graph Database for Surveillance in Wireless Multimedia Sensor Networks

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    Sensors are present in various forms all around the world such as mobile phones, surveillance cameras, smart televisions, intelligent refrigerators and blood pressure monitors. Usually, most of the sensors are a part of some other system with similar sensors that compose a network. One of such networks is composed of millions of sensors connect to the Internet which is called Internet of things (IoT). With the advances in wireless communication technologies, multimedia sensors and their networks are expected to be major components in IoT. Many studies have already been done on wireless multimedia sensor networks in diverse domains like fire detection, city surveillance, early warning systems, etc. All those applications position sensor nodes and collect their data for a long time period with real-time data flow, which is considered as big data. Big data may be structured or unstructured and needs to be stored for further processing and analyzing. Analyzing multimedia big data is a challenging task requiring a high-level modeling to efficiently extract valuable information/knowledge from data. In this study, we propose a big database model based on graph database model for handling data generated by wireless multimedia sensor networks. We introduce a simulator to generate synthetic data and store and query big data using graph model as a big database. For this purpose, we evaluate the well-known graph-based NoSQL databases, Neo4j and OrientDB, and a relational database, MySQL.We have run a number of query experiments on our implemented simulator to show that which database system(s) for surveillance in wireless multimedia sensor networks is efficient and scalable
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