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Increase Flash Memory in MMULess Embedded Systems


Affiliations
1 Shri JJT University, Jhunjhunu, Rajasthan-01, India
2 Department of ECE, R R Institute of Technology, Bengaluru, Karnataka-560 090, India
     

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Sensor Network nodes are least expensive, low power embedded systems. Random access memory (RAM) is tightly constrained in many embedded systems. The sensor network nodes have only 4-10KB of RAM and do not contain memory management units (MMUs). It is very difficult to implement complex applications under such tight memory constraints. It is proposed to use of compile-time and run-time techniques to increase the amount of usable memory in MMU-less embedded systems. The proposed techniques do not increase hardware cost, and are designed to require few changes to existing applications. It has been developed a fast compression algorithm well suited to this application, as well as runtime library routines and compiler transformations to control and optimize the automatic migration of application data between compressed and uncompressed memory regions. These techniques were experimentally evaluated on sensor network nodes running a number of data collection and signal processing applications. The results indicate that available memory can be increased by up to 26%.

Keywords

Embedded System, Wireless Sensor Network, Data Compression, MEMMU, Fragmentation.
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  • Increase Flash Memory in MMULess Embedded Systems

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Authors

N. Rajesha
Shri JJT University, Jhunjhunu, Rajasthan-01, India
H. L. Viswanath
Department of ECE, R R Institute of Technology, Bengaluru, Karnataka-560 090, India

Abstract


Sensor Network nodes are least expensive, low power embedded systems. Random access memory (RAM) is tightly constrained in many embedded systems. The sensor network nodes have only 4-10KB of RAM and do not contain memory management units (MMUs). It is very difficult to implement complex applications under such tight memory constraints. It is proposed to use of compile-time and run-time techniques to increase the amount of usable memory in MMU-less embedded systems. The proposed techniques do not increase hardware cost, and are designed to require few changes to existing applications. It has been developed a fast compression algorithm well suited to this application, as well as runtime library routines and compiler transformations to control and optimize the automatic migration of application data between compressed and uncompressed memory regions. These techniques were experimentally evaluated on sensor network nodes running a number of data collection and signal processing applications. The results indicate that available memory can be increased by up to 26%.

Keywords


Embedded System, Wireless Sensor Network, Data Compression, MEMMU, Fragmentation.