TakaTuka is a Java virtual machine (JVM) mainly focused on wireless sensor network devices.[1][2][3] The VM focussed on supporting small devices with at least 4 KiB of RAM and greater than 48 KiB of flash memory. TakaTuka currently offers CLDC compatible library support.
| Developer(s) | University of Freiburg, LUMS |
|---|---|
| Written in | Java, C, nesC |
| Operating system | Unix-like and TinyOS |
| Type | Java Virtual Machine |
| License | GNU General Public License |
| Website | takatuka.sourceforge.net |
TakaTuka was developed by University of Freiburg and first went public on SourceForge in 2009.[1][2][4] It was created to reduce the learning time of developing wireless sensor network applications by introducing a common Java language among all supported mote.
TakaTuka stores Java Class files into a highly compact format named Tuk. This format strips all unnecessary information, such as class names and retains only essential information for runtime. It also shares a similar Split VM architecture with Squawk virtual machine.[1][2] Furthermore, TakaTuka also employs extensive bytecode compaction that results in smaller code size and faster bytecode execution.[1][2]
Supported motes edit
See also edit
References edit
- ^ a b c d Aslam; et al. (5 November 2008). Introducing TakaTuka: a Java virtual machine for motes. ACM SenSys 2008. pp. 399–400. doi:10.1145/1460412.1460472. ISBN 9781595939906. S2CID 10211172. Retrieved 2010-06-21.
- ^ a b c d Aslam; et al. "Optimized Java Binary and Virtual Machine for Tiny Motes". DCOSS 2010. Archived from the original on 2010-06-25. Retrieved 2010-06-21.
- ^ Brouwers; et al. (2009). "Darjeeling, a feature-rich VM for the resource poor". Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems - Sen Sys '09. ACM SenSys 2009. p. 169. doi:10.1145/1644038.1644056. ISBN 9781605585192. S2CID 13090987. Retrieved 2010-06-22.
- ^ O'Grady; et al. (2010). "Towards evolutionary ambient assisted living systems". Journal of Ambient Intelligence and Humanized Computing. Journal of Ambient Intelligence and Humanized Computing. 1: 15–29. doi:10.1007/s12652-009-0003-5. hdl:10197/1915. S2CID 13299294.