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Distributed and Parallel Databases

An International Journal

Distributed and Parallel Databases OnlineFirst articles


Multi-join query optimization in bucket-based encrypted databases using an enhanced ant colony optimization algorithm

One of the organizations’ main concerns is to protect sensitive data in database systems, especially the ones outsourced to untrusted service providers. An effective solution for this issue is to employ database encryption methods. Among different …


How to exploit high performance computing in population-based metaheuristics for solving association rule mining problem

The application of population-based metaheuristics approaches to the association rules mining problem is explored in this paper. The combination of GPU and cluster-based parallel computing techniques is investigated for the purpose of accelerating …


An adaptive multi-objective evolutionary algorithm for constrained workflow scheduling in Clouds

The Cloud workflow scheduling is to find proper Cloud resources for the execution of workflow tasks to efficiently utilize resources and meet different user’s quality of service requirements. Cloud workflow scheduling is a constrained and …


Flexible partitioning for selective binary theta-joins in a massively parallel setting

Efficient join processing plays an important role in big data analysis. In this work, we focus on generic theta joins in a massively parallel environment, such as MapReduce and Spark. Theta joins are notoriously slow due to their inherent …


Executable schema mappings for statistical data processing

Data processing is the core of any statistical information system. Statisticians are interested in specifying transformations and manipulations of data at a high level, in terms of entities of statistical models. We illustrate here a proposal …

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Distributed and parallel database technology has been the subject of intense research and development effort. Numerous practical application and commercial products that exploit this technology also exist. Since the mid-1990s, web-based information management has used distributed and/or parallel data management to replace their centralized cousins. The maturation of the field, together with the new issues that are raised by the changes in the underlying technology, requires a central focus for work in the area. Distributed and Parallel Databases provides such a focus for the presentation and dissemination of new research results, systems development efforts, and user experiences in distributed and parallel database systems.

Distributed and Parallel Databases publishes papers in all the traditional as well as most emerging areas of database research, including: Data Integration, Data Sharing, Security and Privacy, Transaction Management, Process and Workflow Management, Information Extraction, Query Processing and Optimization, the Analysis, Mining and Visualization of large data sets, Storage, Data Fragmentation, Placement and Allocation, Replication Protocols, Reliability, Fault Tolerance, Persistence, Preservations, Performance and Scalability, and Use of various communication and dissemination platforms and middleware.

Example sets of issues in the context of distributed and parallel systems include:

  • Mobile, Service, P2P, grid and cloud computing for managing data and processes
  • Managing Heterogeneity and Autonomy in Distributed Systems
  • Semantic interoperability and integration (matching, mapping)
  • Linked Data, Open Data, Mobile Data, Streaming Data, Sensor Data, Multimedia and Multimodal Data
  • Metadata, Knowledge Bases, Ontologies
  • Web scale data management
  • Relational, Object-Oriented, XML, Graph, RDF, Event data management
  • Supporting Group/Collaborative Work
  • Support for Non-Traditional Applications (e.g., Soft Computing applied to Data Processing, Translational medicine exploiting a variety of data)
  • Alternative Software and Hardware Architectures Related to Data Management
  • The Use of Distributed and Parallel Database Technology in Managing Biological, Geographic, Spatial, Temporal, Scientific and Statistical Data
  • System Support and Interface Issues for Data Management
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Safety & Security – Erfolgsfaktoren von sensitiven Robotertechnologien

Forderungen von Industrie 4.0 nach vollständiger Vernetzung der Systeme geben der "Robotersicherheit" einen besonderen Stellenwert: Hierbei umfasst der deutsche Begriff Sicherheit die – im Englischen einerseits durch Safety umrissene physische Sicherheit – sowie andererseits die durch Security definierte informationstechnische Cyber-Sicherheit. Dieser Fachbeitrag aus der e&i beleuchtet eingehend die wesentlichen Aspekte von Safety und Security in der Robotik.
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