Dynamic storage allocation (DSA) algorithms have played an important role in the modern software engineering paradigms and techniques (as object oriented paradigm). Additionally, its utilization allows it to increase
the flexibility and functionalities of the applications. There exists in the literature a large number of works and references to this particular issue. However, in the real-time community the use of dynamic memory techniques has not been considered as an important issue because spatial and temporal worst case for allocation and deallocation operations were insufficiently bounded.

TLSF solves the problem of the worst case bound maintaining the efficiency of the allocation and deallocation operations allows the reasonable use of dynamic memory management in real-time applications. The proposed algorithm, with a constant cost Θ(1), opens new possibilities with respect to the use of dynamic memory in real-time applications. There exists an increasing number of emerging applications using high amounts of memory, such as multimedia systems, video streaming, video surveillance, virtual reality, scientific data gathering, or data acquisition in control systems.

This work is motivated by the necessity of including memory resource management in a real-time resource management framework. Dynamic storage allocation is considered one of the keys to add flexibility and
adaptability to the application programming. We propose a memory resource reservation model for flexible embedded systems requiring dynamic memory.

The main goals of this work are:

• A vision of the memory as a resource in the same way that other resources are considered.
• A memory model and a memory reservation architecture being able to manage the spare memory of the system.
• An acceptance test for memory reclamation and a memory reclaiming mechanism of the memory associated requests.