2019
DOI: 10.1145/3341170
|View full text |Cite
|
Sign up to set email alerts
|

Improved Ahead-of-time Compilation of Stack-based JVM Bytecode on Resource-constrained Devices

Abstract: Many virtual machines exist for sensor nodes with only a few KB RAM and tens to a few hundred KB flash memory. They pack an impressive set of features, but suffer from a slowdown of one to two orders of magnitude compared to optimised native code, reducing throughput and increasing power consumption.Compiling bytecode to native code to improve performance has been studied extensively for larger devices, but the restricted resources on sensor nodes mean most modern techniques cannot be applied. Simply replacing… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2019
2019
2022
2022

Publication Types

Select...
3
3

Relationship

1
5

Authors

Journals

citations
Cited by 8 publications
(2 citation statements)
references
References 33 publications
0
2
0
Order By: Relevance
“…Alternatively, interpreted languages enable the dynamic execution of programs speeding up the development process, and allowing debugging and modifications to the programs even at runtime. These interpreters usually run atop a generalpurpose operating system or need to be embedded inside an application [17], dramatically increasing resource consumption and memory occupation [18], and limiting the access to the underlying hardware.…”
Section: Symbolic Execution Platformmentioning
confidence: 99%
“…Alternatively, interpreted languages enable the dynamic execution of programs speeding up the development process, and allowing debugging and modifications to the programs even at runtime. These interpreters usually run atop a generalpurpose operating system or need to be embedded inside an application [17], dramatically increasing resource consumption and memory occupation [18], and limiting the access to the underlying hardware.…”
Section: Symbolic Execution Platformmentioning
confidence: 99%
“…Different from traditional JVM, the Darjeeling VM uses the AOT (Ahead-of-Time) compiler rather than the JIT, to reduce the memory and storage usage requirements. The memory footprint of DarjeelingVM is less than 80 kB and the optimized Java executable code is only 86% slower than the optimized native C executable code (Reijers and Shih, 2017). (Other Java JIT compilers are from 30 to 200 times slower compared with the optimized C implementation.…”
Section: 2mentioning
confidence: 99%