PicoDMBS: Scaling Down Database Techniques for the Smartcard
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
DELite: database support for embedded lightweight devices
Proceedings of the 4th ACM international conference on Embedded software
Design of flash-based DBMS: an in-page logging approach
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Developmental informatics at IIT Bombay
ACM SIGMOD Record
FAME-DBMS: tailor-made data management solutions for embedded systems
SETMDM '08 Proceedings of the 2008 EDBT workshop on Software engineering for tailor-made data management
Fine-grained updates in database management systems for flash memory
Information Sciences: an International Journal
Design and implementation of MLC NAND flash-based DBMS for mobile devices
Journal of Systems and Software
Tailor-made data management for embedded systems: A case study on Berkeley DB
Data & Knowledge Engineering
An efficient method for record management in flash memory environment
Journal of Systems Architecture: the EUROMICRO Journal
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Lightweight computing devices are becoming ubiquitous and an increasing number of applications are being developed for these devices. Many of these applications deal with significant amounts of data and involve complex joins and aggregate operations which necessitate a local database management system on the device. This is a challenge as these devices are constrained by limited stable storage and main memory. Hence new storage models that reduce storage costs are needed and a storage scheme should be selected based on data characteristics, nature of queries, and updates. Also, query execution plan should be chosen depending on the amount of available memory and the underlying storage scheme; memory should be optimally allocated among the database operators involved in the query. To achieve these goals, we utilize a novel storage model, ID based Storage, which reduces storage costs considerably. We present an exact algorithm for allocating memory among the database operators. Because of its high complexity, we also propose a heuristic solution based on the benefit of an operator per unit memory allocation.