Quality of service (QoS) routing is one of the critical challenges in wireless sensor networks (WSNs) especially for surveillance systems. Multi-hop data transmission of WSNs, due to the high packet loss and energy-efficiency, requires reliable links for end-to-end data delivery. Current multipath routing works can provision QoS requirements like end-to-end reliability and delay, but suffer from a significant energy cost. To improve the efficiency of the network with multi constraints QoS parameters, we model the problem as a multi-constrained optimal path problem and propose a distributed learning automaton (DLA) based algorithm to preserve them. The proposed approach leverages the advantage of DLA to find the smallest number of nodes to preserve the desired QoS requirements. It takes several QoS routing constraints like end-to-end reliability and delay into account in path selection. We simulate the proposed algorithm and the obtained results verify the effectiveness of our solution. The results demonstrate that our algorithm has a better performance than current state-of-the-art competitive algorithms in terms of end-to-end delay and energy-efficiency.

Border surveillance is an application of wireless sensor networks (WSNs) and it is mainly used for security purpose. The present issue of implementing this application is a barrier coverage in WSNs. Due to energy constraints, minimizing energy consumption of sensors is a critical challenge. This paper presents a new distributed approach to the border surveillance in WSNs in order to maximize the number of barriers and minimize energy consumption. We use a learning automata scheme in our approach to solve this problem. We present distributed border surveillance (DBS) algorithm that aims to find the minimum possible number of nodes in each barrier to monitor the network borders. In DBS approach, learning automaton assists to find the best nodes to assure barrier coverage at any moment. The algorithm was implemented through computer simulations and compared to the existing competing algorithms. The simulation results show that the DBS scheme outperformed some state-of-art barrier-coverage algorithms.