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

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

Towards More Data-Aware Application Integration (extended version)

Although most business application data is stored in relational databases, programming languages and wire formats in integration middleware systems are not table-centric. Due to costly format conversions, data-shipments and faster computation, the trend is to "push-down" the integration operations closer to the storage representation. We address the alternative case of defining declarative, table-centric integration semantics within standard integration systems. For that, we replace the current operator implementations for the well-known Enterprise Integration Patterns by equivalent "in-memory" table processing, and show a practical realization in a conventional integration system for a non-reliable, "data-intensive" messaging example. The results of the runtime analysis show that table-centric processing is promising already in standard, "single-record" message routing and transformations, and can potentially excel the message throughput for "multi-record" table messages.Comment: 18 Pages, extended version of the contribution to British International Conference on Databases (BICOD), 2015, Edinburgh, Scotlan

Mobile Agent based Market Basket Analysis on Cloud

This paper describes the design and development of a location-based mobile shopping application for bakery product shops. Whole application is deployed on cloud. The three-tier architecture consists of, front-end, middle-ware and back-end. The front-end level is a location-based mobile shopping application for android mobile devices, for purchasing bakery products of nearby places. Front-end level also displays association among the purchased products. The middle-ware level provides a web service to generate JSON (JavaScript Object Notation) output from the relational database. It exchanges information and data between mobile application and servers in cloud. The back-end level provides the Apache Tomcat Web server and MySQL database. The application also uses the Google Cloud Messaging for generating and sending notification of orders to shopkeeper.Comment: 6 pages, 7 figure

Control Infrastructure for a Pulsed Ion Accelerator

We report on updates to the accelerator controls for the Neutralized Drift Compression Experiment II, a pulsed induction-type accelerator for heavy ions. The control infrastructure is built around a LabVIEW interface combined with an Apache Cassandra backend for data archiving. Recent upgrades added the storing and retrieving of device settings into the database, as well as ZeroMQ as a message broker that replaces LabVIEW's shared variables. Converting to ZeroMQ also allows easy access via other programming languages, such as Python

Final Research Report for Sound Design and Audio Player

This deliverable describes the work on Task 4.3 Algorithms for sound design and feature developments for audio player. The audio player runs on the in-store player (ISP) and takes care of rendering the music playlists via beat-synchronous automatic DJ mixing, taking advantage of the rich musical content description extracted in T4.2 (beat markers, structural segmentation into intro and outro, musical and sound content classification). The deliverable covers prototypes and final results on: (1) automatic beat-synchronous mixing by beat alignment and time stretching – we developed an algorithm for beat alignment and scheduling of time-stretched tracks; (2) compensation of play duration changes introduced by time stretching – in order to make the playlist generator independent of beat mixing, we chose to readjust the tempo of played tracks such that their stretched duration is the same as their original duration; (3) prospective research on the extraction of data from DJ mixes – to alleviate the lack of extensive ground truth databases of DJ mixing practices, we propose steps towards extracting this data from existing mixes by alignment and unmixing of the tracks in a mix. We also show how these methods can be evaluated even without labelled test data, and propose an open dataset for further research; (4) a description of the software player module, a GUI-less application to run on the ISP that performs streaming of tracks from disk and beat-synchronous mixing. The estimation of cue points where tracks should cross-fade is now described in D4.7 Final Research Report on Auto-Tagging of Music.EC/H2020/688122/EU/Artist-to-Business-to-Business-to-Consumer Audio Branding System/ABC D