TTLA: two-way trust between clients and fog servers using Bayesian learning automata

Fog computing is a promising paradigm for use as an efficient architecture Internet-of-Things applications. This architecture’s advantages include proximity, low latency, adaptable resource capacity, and distributed structure. A considerable amount of generated data their requisites to real-time processes cause fog nodes offload the number tasks others, causing trust issues. In this paper, each client prefers task trusted server, server serve clients. may take some time, especially if we wish reduce energy consumption. paper proposes Bayesian learning automaton-based two-way management strategy address issue. The proposed method outperforms current state-of-the-art methods regarding consumption, network usage, response value.