Connectivity Restoration in Wireless Sensor and Actor Networks using Distributed Learning Automata

Connectivity in WSNs is vital to preserve the network performance. Reported algorithms try to restore connectivity by appropriately selecting the failure handler. This paper, initially presents a hybrid algorithm based on distributed learning automata named DLA-BuS for critical node backup selection. Then, we present DLA-MRF to repair stimulant failure of two adjacent actors. Simulations using Castalia demonstrate that proposed algorithms outperform representative methods in terms of some well-known performance parameters.