Published Paper Details:

Dynamic memory management is vital in embedded systems as it allows efficient allocation and deallocation of memory blocks, optimizing resource utilization. It provides adaptability to changing runtime requirements, enabling embedded systems to handle varying data sizes and structures effectively. Furthermore, dynamic memory management plays a crucial role in memory optimization, minimizing fragmentation and maximizing memory usage for improved system performance. This paper investigates the potential of smart and programmable memory management methods to enhance performance and efficiency in MMU-less embedded systems, addressing the challenge of limited space and the increasing use of IoT. The current approach has achieved an improvement in allocation speed, around 3-4 times faster, with a slight trade-off in deallocation speed. Additionally, the outcome includes achieving 0 fragmented memory. Additionally, the paper provides detailed algorithms for implementing memory allocation, deallocation, and defragmentation processes directly within the application software that is already in use. These algorithms offer practical and feasible solutions for managing memory efficiently without requiring significant changes to the existing software infrastructure.