2,584 research outputs found

    XML Schema-based Minification for Communication of Security Information and Event Management (SIEM) Systems in Cloud Environments

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    XML-based communication governs most of today's systems communication, due to its capability of representing complex structural and hierarchical data. However, XML document structure is considered a huge and bulky data that can be reduced to minimize bandwidth usage, transmission time, and maximize performance. This contributes to a more efficient and utilized resource usage. In cloud environments, this affects the amount of money the consumer pays. Several techniques are used to achieve this goal. This paper discusses these techniques and proposes a new XML Schema-based Minification technique. The proposed technique works on XML Structure reduction using minification. The proposed technique provides a separation between the meaningful names and the underlying minified names, which enhances software/code readability. This technique is applied to Intrusion Detection Message Exchange Format (IDMEF) messages, as part of Security Information and Event Management (SIEM) system communication hosted on Microsoft Azure Cloud. Test results show message size reduction ranging from 8.15% to 50.34% in the raw message, without using time-consuming compression techniques. Adding GZip compression to the proposed technique produces 66.1% shorter message size compared to original XML messages.Comment: XML, JSON, Minification, XML Schema, Cloud, Log, Communication, Compression, XMill, GZip, Code Generation, Code Readability, 9 pages, 12 figures, 5 tables, Journal Articl

    PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development

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    This paper describes PlinyCompute, a system for development of high-performance, data-intensive, distributed computing tools and libraries. In the large, PlinyCompute presents the programmer with a very high-level, declarative interface, relying on automatic, relational-database style optimization to figure out how to stage distributed computations. However, in the small, PlinyCompute presents the capable systems programmer with a persistent object data model and API (the "PC object model") and associated memory management system that has been designed from the ground-up for high performance, distributed, data-intensive computing. This contrasts with most other Big Data systems, which are constructed on top of the Java Virtual Machine (JVM), and hence must at least partially cede performance-critical concerns such as memory management (including layout and de/allocation) and virtual method/function dispatch to the JVM. This hybrid approach---declarative in the large, trusting the programmer's ability to utilize PC object model efficiently in the small---results in a system that is ideal for the development of reusable, data-intensive tools and libraries. Through extensive benchmarking, we show that implementing complex objects manipulation and non-trivial, library-style computations on top of PlinyCompute can result in a speedup of 2x to more than 50x or more compared to equivalent implementations on Spark.Comment: 48 pages, including references and Appendi

    Distributed Objects in C#

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    Today more and more programs run over a collection of autonomous computers linked by a network and are designed to produce an integrated computing facility. Java Distributed Objects (JDO) proposed by Dr. Axel T. Schreiner builds an infrastructure which allows distributed program components to communicate over a network in a transparent, reliable, efficient, and generic way. JDO was originally intended as a teaching device to assess design parameters for distributed objects. This project focuses on porting JDO, which is implemented in Java on Sun\u27s JDK, to C# on Microsoft\u27s .NET. On one hand, it builds an infrastructure in C# that simplifies the construction of distributed programs by hiding the distributed nature of remote objects. On the other hand, it generates insights into the differences between two platforms, namely, Java on Sun and C# on .NET, in the distributed objects area. This document illustrates the architectural design of the C# Distributed Objects system and compares programming technologies, which are required by this system design, in Java and C#
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