Database Systems Journal

ISSN 2069 - 3230

The journal is published under the sponsorship of
The Bucharest University of Economic Studies
and it is produced by the university's own publishing division,
The Bucharest University of Economic Studies Publishing House

Database Systems Journal, Vol. VII, Issue 2/2016
Issue Topic: Database systems development

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1. A technique for n-way joins in wireless sensor networks (p. 3-9)
Djail BOUBEKEUR, LCSI Laboratory National High School for Computer Science (ESI) Algiers, Algeria
Hidouci Walid KHALED, LCSI Laboratory National High School for Computer Science (ESI) Algiers, Algeria
Loudini MALIK, LCSI Laboratory National High School for Computer Science (ESI) Algiers, Algeria
The join queries are operations that require more energy for their execution. In wireless sensor networks, energy is a determinant factor for the network survival. However, high energy consumption caused by such requests needs the implementation of very appropriate techniques for their execution. Research in this field considered especially binary joins. Few studies have addressed n-way joins. In this paper, we propose 'Nway Local Join', an energy-efficient technique for n-way join operations. We adopt an in-network execution at each step of the join operation. We compare our solution with an execution at the sink. NLJ shows the best performance for low selectivity factor.
Keywords: wireless sensor networks, communication cost, in-network join, n-way join.
2. eLearning Mobile App for Android and Ios "English Grammar Learn & Test" (p. 10-18)
Anca-Georgiana FODOR,, Romania
Bogdan Vasile COVACI,, Romania
This article is aiming to present the architecture and few elements from the developing cycle of "English Grammar Learn & Test" app. This is an e-learning tool for people who want to improve their English Grammar and Vocabulary. The app was approved by Google Play and Apple Store and it is available for free on both platforms as following:
The app already reached350.000 users, it is rated at 4.43out of maximum 5.0 in Google Play Store. Since mid-June 2016, we launched the app also in the Apple Store iOS devices.
Keywords: e-learning, m-Learning,English Grammar Learn & Test, Android Mobile Apps, IOS Mobile Apps, SQLite, Eclipse, XCode, Java, Swift.
3. A new approach to adaptive data models (p. 19-27)
Ion LUNGU, University of Economic Studies, Bucharest, Romania
Andrei MIHALACHE, University of Economic Studies, Bucharest, Romania
Over the last decade, there has been a substantial increase in the volume and complexity of data we collect, store and process. We are now aware of the increasing demand for real time data processing in every continuous business process that evolves within the organization. We witness a shift from a traditional static data approach to a more adaptive model approach. This article aims to extend understanding in the field of data models used in information systems by examining how an adaptive data model approach for managing business processes can help organizations accommodate on the fly and build dynamic capabilities to react in a dynamic environment.
Keywords: adaptive data model, dynamic capabilities, data models.
4. Big Data Mining: Challenges, Technologies, Tools and Applications (p. 28-33)
Asha M. PAWAR, Computer Engineering Department, SKNCOE, Pune, India
Big data is a data with large size means it has large volume, velocity and variety. Now a day's big data is expanding in a various science and engineering fields. And so there are many challenges to manage and analyse big data using various tools. This paper introduces the big data and its Characteristic concepts and Next section elaborates about the Challenges in Big data. In Particular, wed discuss about the technologies used in big data Analysis and Which Tools are mainly used to analyse the data. As big data is growing day by day there are lot of application areas where we need to use any of the technology and tools discussed in paper. Mainly this paper focuses on the Challenges, Technologies, Tools and Applications used for big data Analysis.
Keywords: big data, big data analysis, mining, heterogeneous data.
5. Efficient Partitioning of Large Databases without Query Statistics (p. 34-53)
Shahidul Islam KHAN, Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh
An efficient way of improving the performance of a database management system is distributed processing. Distribution of data involves fragmentation or partitioning, replication, and allocation process. Previous research works provided partitioning based on empirical data about the type and frequency of the queries. These solutions are not suitable at the initial stage of a distributed database as query statistics are not available then. In this paper, I have presented a fragmentation technique, Matrix based Fragmentation (MMF), which can be applied at the initial stage as well as at later stages of distributed databases. Instead of using empirical data, I have developed a matrix, Modified Create, Read, Update and Delete (MCRUD), to partition a large database properly. Allocation of fragments is done simultaneously in my proposed technique. So using MMF, no additional complexity is added for allocating the fragments to the sites of a distributed database as fragmentation is synchronized with allocation. The performance of a DDBMS can be improved significantly by avoiding frequent remote access and high data transfer among the sites. Results show that proposed technique can solve the initial partitioning problem of large distributed databases.
Keywords: Distributed Database, Partitioning, Fragmentation, Allocation, MCRUD matrix.