Affiliation:
1. Universität Stuttgart, Germany
Abstract
Virtual memory has been successfully used in different domains to extend the amount of memory available to applications. We have adapted this mechanism to sensor networks, where, traditionally, RAM is a severely constrained resource. In this paper we show that the overhead of virtual memory can be significantly reduced with compile-time optimizations to make it usable in practice, even with the resource limitations present in sensor networks.
Our approach,
ViMem
, creates an efficient memory layout based on variable access traces obtained from simulation tools. This layout is optimized to the memory access patterns of the application and to the specific properties of the sensor network hardware.
Our implementation is based on TinyOS. It includes a pre-compiler for nesC code that translates virtual memory accesses into calls of
ViMem's
runtime component.
ViMem
uses flash memory as secondary storage. In order to evaluate our system we have modified nontrivial existing applications to make use of virtual memory. We show that its runtime overhead is small even for large data sizes.
Publisher
Association for Computing Machinery (ACM)
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