Memory size estimation for multimedia applications
Proceedings of the 6th international workshop on Hardware/software codesign
Embedded system synthesis under memory constraints
CODES '99 Proceedings of the seventh international workshop on Hardware/software codesign
Data and memory optimization techniques for embedded systems
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Storage requirement estimation for optimized design of data intensive applications
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Intelligent prognostics tools and e-maintenance
Computers in Industry - Special issue: E-maintenance
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Memory estimation and allocation algorithms for MDVM system
AICCSA '05 Proceedings of the ACS/IEEE 2005 International Conference on Computer Systems and Applications
System architecture for closed-loop PLM
International Journal of Computer Integrated Manufacturing - Integrated Design of Product and Processes
Information dissemination framework for context-aware products
Computers and Industrial Engineering
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Over the last decade, emerging information communication technologies have changed our stereotype of manufacturing and service companies. Now products equipped with embedded systems can be wirelessly networked, which leads to gathering and analyzing product status, and taking appropriate actions for maintenance operations during product lifecycle in an ubiquitous way. In this environment, it is necessary to determine the appropriate memory size of embedded systems for minimizing total maintenance system costs because the memory cost is a main cost factor for implementing the ubiquitous maintenance environment. We call it memory size decision problem in this study. We have formulated this problem with a non-linear model having constraints. The decision variable is the memory size of each embedded system. To solve this problem, we have proposed a meta heuristic search method based on genetic algorithms. To show the usefulness of the proposed heuristic, we have carried out computational experiments.