Adaptive Layered Segregated Fit Scheme for Dynamic Memory Allocation

Abstract

Embedded applications are becoming more complex and are required to utilize computing platform resources more efficiently. Existing dynamic memory allocation (DSA) schemes cannot adaptively perform memory management according to the environment in which they are located or integrate various memory allocation strategies, making it impossible to guarantee a constant execution time. Efficient memory utilization is a crucial challenge for developers, especially in embedded OSs (operating systems). In this paper, we propose an adaptive layered segregated fit (ALSF) scheme for DSA. The ALSF scheme combines dynamic two-dimensional arrays and bitmaps, completes the allocation and freeing of memory blocks within constant execution time, and uses memory splitting technology to reduce internal fragmentation. The proposed scheme also adjusts the number of segregated lists by analyzing the system’s allocation of different memory sizes, which improves the matching accuracy of memory blocks. We conducted a comparative experimental analysis and investigation of the ALSF and two-level segregated fit (TLSF) schemes in the Zephyr OS. Experiments show that the average memory utilization of the proposed ALSF scheme reaches 94.95%. Compared with the TLSF scheme, our scheme has a 12.99% higher allocation success rate in the memory-scarce environment, and the execution speeds of the two are similar.