Linux kernel compaction through cold code swapping

Abstract. There is a growing trend to use general-purpose operating systems like Linux in embedded systems. Previous research focused on us-ing compaction and specialization techniques to adapt a general-purpose OS to the memory-constrained environment presented by most embed-ded systems. However, there is still room for improvement: it has been shown that even after application of the aforementioned techniques more than 50 % of the kernel code remains unexecuted under normal system operation. We introduce a new technique that reduces the Linux kernel code memory footprint through on-demand code loading of infrequently executed code, for systems that support virtual memory. In this paper, we describe our general approach, and we study code placement algo-rithms to minimize the performance impact of the code loading. A code size reduction of 68 % is achieved, with a 2.2 % execution speedup of the system-mode execution time, for a case study based on the MediaBench II benchmark suite.