Research Papers Database Systems

Research Papers Database Systems-20
The first V concerns the Volume of data generated by traditional and new providers.To illustrate the data deluge, let consider three examples of data providers: (i) the massive use of sensors (e.g.

The database storage systems are evolving towards decentralized commodity clusters that can scale in terms of capacity, processing power, and network throughput. Traditionally, storage systems managed databases that were primarily stored on secondary storage and only a small part of the data could fit in main memory.

The efforts that have been deployed to design such systems ). Hive QL, Spark SQL), Actor (e.g., Akka, Storm), (5) statistical and analytical (e.g. Oozie, Dryad), (7) Bulk Synchronous Parallel (BSP) (e.g. Therefore, disk Input-Output (IO) was the dominating cost factor. GPU, FPGA, APU) are available and can be used in parallel in order to process database operations, where each processor is optimized for a certain application scenario (Breß et al. The database community, including researchers, industrials and funding organizations has spared no effort to conduct advanced research, by exploiting the achievements and above opportunities, to satisfy the requirements of companies in terms of data management and exploitation.

The ADBIS conference is one of concrete examples of these efforts.

The ADBIS conference has been widely accepted as a key technology for enterprises and organizations to improve their abilities in data modeling, data management, data exploitation and information systems.

Considerations above open the door to innovative research directions and challenges for the database research community, yet exploiting two opportunities: (i) computational and storage resource modeling and organization; (ii) Big Data programming models and (iii) processing power.

This can be accomplished by means of actual powerful hardware and infrastructures as well as new programming models available at now.

10 Terabyte of data are generated by planes every 30 minutes), (ii) the massive use of social networks (e.g., 340 million tweets per day), (iii) transactions (Walmart handles more than 1 million customer transactions every hour, which is imported into databases estimated to contain more than 2.5 Peta-bytes of data).

The second V is associated to the Variety, where data may come from various data sources, in different formats such as transactions, log data, social network, sensors, etc.

Special Issues devoted to important topics in intelligent information and database systems and related subjects are welcome.

The services dedicated to data concern mainly the following tasks: collecting, cleaning, filtering, integration, sharing, storing, transferring, visualizing, analyzing, securing.


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