Читать книгу Intelligent Security Management and Control in the IoT - Mohamed-Aymen Chalouf - Страница 50

In this chapter, we proposed a mechanism to control congestion of the access network, which is considered one of the most critical problems for IoT objects. We have proposed tackling congestion at its root by effectively managing random accesses from these devices thanks to use of the ACB mechanism.

The proposed access control mechanism is different from conventional methods, which generally rely on simple heuristics. Indeed, the proposed technique relies on recent advances in deep reinforcement learning, through use of the TD3 algorithm. The proposed approach has, in addition, the advantage of learning from its environment and could therefore enable it to adapt to variation of the access schema.

The simulation results make it possible to show the superiority of the proposed approach, which succeeds in maintaining a number of access attempts close to the optimum, despite the absence of exact information on the number of access attempts. This work also makes it possible to show the potential of using learning techniques in environments where the state cannot be known with precision.

In the context of our future work, we envisage improving estimation of the number of attempts using learning techniques.