6438691
Event-Feeded Dimension Solution
From the point of view of a data warehouse system its part of collecting and receiving information from other systems is crucial for all subsequent business intelligence applications. The incoming information can be classified generally in two types, the state-snapshot data and the state-change or event data usually called transactional data, which contains information about the change processes applied on the instances of information objects. On the way towards active data warehouses it becomes more important to provide complete data with minimal latency. We focus in this paper on dimensional data provided by any data-master application. The information transfer is done via messages containing the change-information of the dimension instances. The receiving data warehouse system is able to validate the event-messages, reconstruct the complete history of the dimension and provide a well applicable “comprehensive slowly changing dimension” (cSCD) interface for well-performing queries on the historical and current state of the dimension. A prototype implementation of “active integration” of a data warehouse is proposed.
6251517
A Front-End Approach for User Query Generation and Information Retrieval in the SemanticLIFE Framework
Formulating unambiguous queries in the Semantic Web applications is a challenging task for users. This paper presents a new approach in guiding users to generate clear requests based on their common nature of querying for information. The approach known as the "front-end approach" gives users an overview about the system data through a "virtual data component" which stores the extracted metadata of the data storage sources in the form of an ontology. This approach reduces the ambiguities in users' requests at very early stage; and allows the query refinement process to easily to fulfill users's demands. Furthermore, the approach provide a powerful query engine, called "context-based querying", that recommends the appropriate query patterns according to the user's querying context. These features help the user in generating clear query more easier.
12195287
Towards service collaboration model in grid-based zero latency data stream warehouse (GZLDSWH)
A grid-based zero-latency data stream warehouse (GZLDSWH), built upon a set of OGSI-based grid services and GT3 toolkit, overcomes the resource limitation issue for data stream processing without using traditional approximate approaches. However, due to its "automated event-based reaction" characteristic, the GZLDSWH requires a mechanism which allows the grid services to be able to work together to fulfill the common tasks. This paper describes the collaboration model for the grid services which enables the automation of the GZLDSWH in capturing and storing continuous data streams, making analytical processing, and reacting autonomously in near real time with some kinds of events based on well-established knowledge base.
7825329
Zero-Latency Data Warehousing for Heterogeneous Data Sources and Continuous Data Streams
In this paper, a framework for building an overall Zero-Latency Data Warehouse system (ZLDWH) is provided. Such a ZLDWH requires tasks such as data changes detection, continuous loading and updating of new data, autonomous analysis and the execution of actions to be completed in the Data Warehouse (DWH). For this purpose, we combine (1) an existing solution for the continuous data integration and (2) the known approach of Active Data Warehousing (ADWH) by introducing protocols that enable the correct collaboration between the two. The continuous data integration is realized on the one hand by asynchronous communication between multiple information sources and the DWH through a message queuing system, and on the other hand by the continuous loading and updating. To obtain a low-latency time for this cycle, an “active rule evaluation” is provided between the data feeding stage and its loading into the DWH. This is realized by applying ECA-Techniques (EventCondition-Action) to obtain a more “active” characteristic of the DWH. A second goal of this paper is to take into consideration a special class of information source namely continuous data streams. Continuous data streams are information sources in which data arrives in high-volume, rapidly, bursty, and needs to be processed continuously. Therefore novel protocols and techniques are needed for capturing, storing and evaluate analysis decision based on new coming data from such continuous data stream sources.
15193485
Towards the Stream Analysis Model in Grid-based Zero-Latency Data Stream Warehouse
Recent emerging applications increasingly generate continuous, larger amounts of valuable data. The demand of conducting advanced analysis over fast and huge data streams to capture trends, patterns, and exceptions become crucial. However, fully extracting the latent knowledge within the data stream is a challenging task because of insufficient technology. While Data Warehouse (DWH) technologies have resulted in considerable information processing efficiencies, there is still a significant delay in the time to deliver mission critical information to data consumers. Traditional data stream processing focuses on statistical approaches hence produces approximate results. In this paper, we introduce the Stream Analysis Model with a Grid-based ZeroLatency Data Stream Warehouse (GZLDSWH) framework which allows to perform analytical processing on continuous data streams and to trigger relevant actions depending on patterns discovered in event streams without using statistical approximation. Essential data stream elements are captured, analysed on the fly and finally evaluated to detect abnormalities while the entire data streams are stored within a Grid and integrated into a virtual DWH for further analysis in the case of ambiguity or uncertainty.
1402747
'SemanticLIFE' - A Framework for Managing Information of A Human Lifetime
The SemanticLIFE' system is designed to store, manage and retrieve ones lifetime’s information entities. It enables the acquisition and storage of data while giving annotations to email messages, browsed web pages, phone calls, images, contacts, life events and other resources. 'SemanticLIFE' 
also provides intuitive and effective search mechanism based upon stored semantics. This paper presents the framework for the system to devise lifetime data store and search using recognized standards. We are aiming at a system which supports the long term memory by associating metadata with content and ontologies. The ultimate goal of our project is to build a Personal Information Management system over a Human Lifetime using ontologies as a basis for the representation of its content.
534199
GRAVY: Towards Virtual File System for the Grid
Today large-scale applications require access to data stored in heterogeneous storage systems located at geographically distributed virtual organizations. In such applications, users are forced to deal with different administrative policies and structures at each site, and various data access mechanisms on each storage system. This implies a lot of human interventions in order to develop dedicated programs and scripts for data transfer between theses systems. This paper presents GRid-enAbled Virtual file sYstem (GRAVY) architecture which enables the automation of data transfers between distributed file systems irrespective of their heterogeneity. This feature enables high-level schedulers integrated with GRAVY to control data placements like computational jobs. GRAVY supports multiple data access protocols and provides an easy-to-use interface for novice Grid users.
18341353
Alias verification for Fortran code optimization
Abstract Alias analysis for Fortran is less complicated than for programming languages with pointers but many real Fortran programs violate the standard: a formal parameter or a common variable that is aliased with another formal parameter is modified. Compilers, assuming standard-conforming programs, consider that an assignment to one variable will not change the value of any other variable, allowing optimizations involving the aliased variables. Higher performance results but anything may happen: the program may appear to run normally, or may produce incorrect answers, or may behave unpredictably. The results may depend on the compiler and the optimization level. To guarantee the standard conformance of programs and to maintain the referential transparency in order to make program analyses exact and program optimizations safe, precise alias information retrieval at a reasonable cost, especially the determination of overlaps between arrays are studied in this paper. Static analyses and code instrumentation are used to find all violations of the prohibitions against aliasing in Fortran code. Alias violation tests are inserted only at places where it cannot be proved statically that they are useless in order to reduce the number of dynamic checks at run-time. A specific memory location naming technique is used to compact representation and enhance the precision of alias analysis. Modifications on the dependence graph created by aliasing are also studied to show the impact of aliases on some program optimizing transformations. Experimental results on SPEC95 benchmark are presented and some related issues are also discussed.
18230962
Efficient and effective array bound checking
Array bound checking refers to determining whether all array references in a program are within their declared ranges. This checking is critical for software verification and validation because subscripting arrays beyond their declared sizes may produce unexpected results, security holes, or failures. It is available in most commercial compilers but current implementations are not as efficient and effective as one may have hoped: (1) the execution times of array bound checked programs are increased by a factor of up to 5, (2) the compilation times are increased, which is detrimental to development and debugging, (3) the related error messages do not usually carry information to locate the faulty references, and (4) the consistency between actual array sizes and formal array declarations is not often checked.This article presents two optimization techniques that deal with Points 1, 2, and 3, and a new algorithm to tackle Point 4, which is not addressed by the current literature. The first optimization technique is based on the elimination of redundant tests, to provide very accurate information about faulty references during development and testing phases. The second one is based on the insertion of unavoidable tests to provide the smallest possible slowdown during the production phase. The new algorithm ensures the absence of bound violations in every array access in the called procedure with respect to the array declarations in the calling procedure. Our experiments suggest that the optimization of array bound checking depends on several factors, not only the percentage of removed checks, usually considered as the best improvement measuring metrics. The debugging capability and compile-time and run-time performances of our techniques are better than current implementations. The execution times of SPEC95 CFP benchmarks with range checking added by PIPS, our Fortran research compiler, are slightly longer, less than 20%, than that of unchecked programs. More problems due to functional and data recursion would have to be solved to extend these results from Fortran to other languages such as C, C++, or Java, but the issues addressed in this article are nevertheless relevant.
16854388
Benchmarking Global Optimization and Constraint Satisfaction Codes
A benchmarking suite describing over 1000 optimization problems and constraint satisfaction problems covering problems from different traditions is described, annotated with best known solutions, and accompanied by recommended benchmarking protocols for comparing test results.
14226937
Self-Learning IP Traffic Classification Based on Statistical Flow Characteristics
A number of key areas in IP network engineering, management and surveillance greatly benefit from the ability to dynamically identify traffic flows according to the applications responsible for their creation. Currently such classifications rely on selected packet header fields (e.g. destination port) or application layer protocol decoding. These methods have a number of shortfalls e.g. many applications can use unpredictable port numbers and protocol decoding requires high resource usage or is simply infeasible in case protocols are unknown or encrypted. We propose a framework for application classification using an unsupervised machine learning (ML) technique. Flows are automatically classified based on their statistical characteristics. We also propose a systematic approach to identify an optimal set of flow attributes to use and evaluate the effectiveness of our approach using captured traffic traces.