On-The-Fly Metadata Stripping For Embedded Java Operating Systems

International audienceConsidering the typical amount of memory available on a smart card, it is essential to minimize the size of the runtime environment to leave as much memory as possible to applications. This paper shows that on-the-fly constant pool packing can result in a significant reduction of the memory footprint of an embedded Java runtime environment. We first present Jits, an architecture dedicated to building fully-customized Java runtime environments for smart cards. We then detail the op- timizations we have implemented in the class loading mechanism of Jits to reduce the size of the loaded class constant pool. By suppress- ing constant pool entries as they become unnecessary during the class loading process, we manage to compact constant pools of loaded classes to less than 8% of their initial size. We then present the results of our mechanism in term of constant pool and class size reductions, and conclude by suggesting some more aggressive optimizations

ON-THE-FLY METADATA STRIPPING FOR EMBEDDED JAVA OPERATING SYSTEMS

Abstract Considering the typical amount of memory available on a smart card, it is essential to minimize the size of the runtime environment to leave as much memory as possible to applications. This paper shows that on-the-fly constant pool packing can result in a significant reduction of the memory footprint of an embedded Java runtime environment. We first present Jits, an architecture dedicated to building fully-customized Java runtime environments for smart cards. We then detail the optimizations we have implemented in the class loading mechanism of Jits to reduce the size of the loaded class constant pool. By suppressing constant pool entries as they become unnecessary during the class loading process, we manage to compact constant pools of loaded classes to less than 8 % of their initial size. We then present the results of our mechanism in term of constant pool and class size reductions, and conclude by suggesting some more aggressive optimizations