MEMMU

Abstract

Random access memory (RAM) is tightly constrained in the least expensive, lowest-power embedded systems such as sensor network nodes and portable consumer electronics. The most widely used sensor network nodes have only 4 to 10KB of RAM and do not contain memory management units (MMUs). It is difficult to implement complex applications under such tight memory constraints. Nonetheless, price and power-consumption constraints make it unlikely that increases in RAM in these systems will keep pace with the increasing memory requirements of applications. We propose the use of automated compile-time and runtime techniques to increase the amount of usable memory in MMU-less embedded systems. The proposed techniques do not increase hardware cost, and require few or no changes to existing applications. We have developed runtime library routines and compiler transformations to control and optimize the automatic migration of application data between compressed and uncompressed memory regions, as well as a fast compression algorithm well suited to this application. These techniques were experimentally evaluated on Crossbow TelosB sensor network nodes running a number of data-collection and signal-processing applications. Our results indicate that available memory can be increased by up to 50% with less than 10% performance degradation for most benchmarks.