| 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 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.
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
See also
References
- ^ 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.