An Architecture Dynamic Modeling Language for Self-Healing Systems

AbstractAs modern software-based systems increase in complexity, recovery from malicious attacks and rectification of system faults become more difficult, labor-intensive, and error-prone. These factors have actuated research dealing with the concept of self-healing systems, which employ architectural models to monitor system behavior and use inputs obtaining therefore to adapt themselves to the run-time environment. Numerous architectural description languages (ADLs) have been developed, each providing complementary capabilities for architectural development and analysis. Unfortunately, few ADLs embrace dynamic change as a fundamental consideration and support a broad class of adaptive changes at the architectural level. The Architecture Dynamic Modeling Language (ADML) is being developed as a new formal language and/or conceptual model for representing dynamic software architectures. TheADML couple the static information provided by the system requirements and the dynamic knowledge provided by tactics, and offer a uniform way to represent and reason about both static and dynamic aspects of self-healing systems. Because the ADML is based on the Dynamic Description Logic DDL, architectural ontology entailment for the ADML languages can be reduced to knowledge base satisfiability in DDL

DAS: a data management system for instrument tests and operations

The Data Access System (DAS) is a metadata and data management software system, providing a reusable solution for the storage of data acquired both from telescopes and auxiliary data sources during the instrument development phases and operations. It is part of the Customizable Instrument WorkStation system (CIWS-FW), a framework for the storage, processing and quick-look at the data acquired from scientific instruments. The DAS provides a data access layer mainly targeted to software applications: quick-look displays, pre-processing pipelines and scientific workflows. It is logically organized in three main components: an intuitive and compact Data Definition Language (DAS DDL) in XML format, aimed for user-defined data types; an Application Programming Interface (DAS API), automatically adding classes and methods supporting the DDL data types, and providing an object-oriented query language; a data management component, which maps the metadata of the DDL data types in a relational Data Base Management System (DBMS), and stores the data in a shared (network) file system. With the DAS DDL, developers define the data model for a particular project, specifying for each data type the metadata attributes, the data format and layout (if applicable), and named references to related or aggregated data types. Together with the DDL user-defined data types, the DAS API acts as the only interface to store, query and retrieve the metadata and data in the DAS system, providing both an abstract interface and a data model specific one in C, C++ and Python. The mapping of metadata in the back-end database is automatic and supports several relational DBMSs, including MySQL, Oracle and PostgreSQL.Comment: Accepted for pubblication on ADASS Conference Serie

CIWS-FW: a Customizable InstrumentWorkstation Software Framework for instrument-independent data handling

The CIWS-FW is aimed at providing a common and standard solution for the storage, processing and quick look at the data acquired from scientific instruments for astrophysics. The target system is the instrument workstation either in the context of the Electrical Ground Support Equipment for space-borne experiments, or in the context of the data acquisition system for instrumentation. The CIWS-FW core includes software developed by team members for previous experiments and provides new components and tools that improve the software reusability, configurability and extensibility attributes. The CIWS-FW mainly consists of two packages: the data processing system and the data access system. The former provides the software components and libraries to support the data acquisition, transformation, display and storage in near real time of either a data packet stream and/or a sequence of data files generated by the instrument. The latter is a meta-data and data management system, providing a reusable solution for the archiving and retrieval of the acquired data. A built-in operator GUI allows to control and configure the IW. In addition, the framework provides mechanisms for system error and logging handling. A web portal provides the access to the CIWS-FW documentation, software repository and bug tracking tools for CIWS-FW developers. We will describe the CIWS-FW architecture and summarize the project status.Comment: Accepted for pubblication on ADASS Conference Serie

Database Systems - Present and Future

The database systems have nowadays an increasingly important role in the knowledge-based society, in which computers have penetrated all fields of activity and the Internet tends to develop worldwide. In the current informatics context, the development of the applications with databases is the work of the specialists. Using databases, reach a database from various applications, and also some of related concepts, have become accessible to all categories of IT users. This paper aims to summarize the curricular area regarding the fundamental database systems issues, which are necessary in order to train specialists in economic informatics higher education. The database systems integrate and interfere with several informatics technologies and therefore are more difficult to understand and use. Thus, students should know already a set of minimum, mandatory concepts and their practical implementation: computer systems, programming techniques, programming languages, data structures. The article also presents the actual trends in the evolution of the database systems, in the context of economic informatics.database systems - DBS, database management systems – DBMS, database – DB, programming languages, data models, database design, relational database, object-oriented systems, distributed systems, advanced database systems

Designing Normative Theories for Ethical and Legal Reasoning: LogiKEy Framework, Methodology, and Tool Support

A framework and methodology---termed LogiKEy---for the design and engineering of ethical reasoners, normative theories and deontic logics is presented. The overall motivation is the development of suitable means for the control and governance of intelligent autonomous systems. LogiKEy's unifying formal framework is based on semantical embeddings of deontic logics, logic combinations and ethico-legal domain theories in expressive classic higher-order logic (HOL). This meta-logical approach enables the provision of powerful tool support in LogiKEy: off-the-shelf theorem provers and model finders for HOL are assisting the LogiKEy designer of ethical intelligent agents to flexibly experiment with underlying logics and their combinations, with ethico-legal domain theories, and with concrete examples---all at the same time. Continuous improvements of these off-the-shelf provers, without further ado, leverage the reasoning performance in LogiKEy. Case studies, in which the LogiKEy framework and methodology has been applied and tested, give evidence that HOL's undecidability often does not hinder efficient experimentation.Comment: 50 pages; 10 figure

XML Security in Certificate Management - XML Certificator

The trend of rapid growing use of XML format in data/document management system reveals that security measures should be urgently considered into next generation's data/document systems. This paper presents a new certificate management system developed on the basis of XML security mechanisms. The system is supported by the theories of XML security as well as Object oriented technology and database. Finally it has been successfully implemented in using C&#, SQL, XML signature and XML encryption. An implementation metrics is evidently presented

Hadoop Performance Analysis Model with Deep Data Locality

Background: Hadoop has become the base framework on the big data system via the simple concept that moving computation is cheaper than moving data. Hadoop increases a data locality in the Hadoop Distributed File System (HDFS) to improve the performance of the system. The network traffic among nodes in the big data system is reduced by increasing a data-local on the machine. Traditional research increased the data-local on one of the MapReduce stages to increase the Hadoop performance. However, there is currently no mathematical performance model for the data locality on the Hadoop. Methods: This study made the Hadoop performance analysis model with data locality for analyzing the entire process of MapReduce. In this paper, the data locality concept on the map stage and shuffle stage was explained. Also, this research showed how to apply the Hadoop performance analysis model to increase the performance of the Hadoop system by making the deep data locality. Results: This research proved the deep data locality for increasing performance of Hadoop via three tests, such as, a simulation base test, a cloud test and a physical test. According to the test, the authors improved the Hadoop system by over 34% by using the deep data locality. Conclusions: The deep data locality improved the Hadoop performance by reducing the data movement in HDFS