An intelligent MAC protocol for mission critical applications in wireless sensor networks

Abstract

SummaryIn the current age, wireless sensor networks (WSN) are growing the attention of researchers. WSNs are significantly used in a broad scope of real‐time monitoring applications. With ongoing advances and requirements in industrial emerging time‐critical applications, WSNs have been accordingly stretched out to help the reliable, time‐bound data delivery. In WSNs, node organization, resource limitations, topology varieties, providing delay guarantees for channel access, and transmission time barrier are the most significant challenges in real‐time handling traffic. Suppose critical data packets arrive from sensor nodes simultaneously. In that case, finding the optimal path for the transmission of data packets so that data are reached within time bounds, taking into account the current network scenario, is a more inspiring task. With this perspective, in order to provide a priority‐based transmission scheme, an improved adaptive media access control (MAC) protocol is proposed to support priority‐based channel access considering the current network scenario, which ensures time‐bounded reliable transfer of critical data packets. The proposed system uses an adaptive learning‐centered approach to find the optimum path for sending critical data packets in varying network scenarios. The proposed mission‐critical MAC (MC‐MAC) protocol is assessed arithmetically to offer reliable and time‐bounded transmission for emergency data packets.

ML-Based Adaptive MAC Protocol for Real Time Data Transmission in Wireless Sensor Networks

“…Figure 1 gives different aspects of current methodologies used in various application domains. Many researchers have developed energy and latency-efficient communication protocols using ML-based techniques for WSNs [26], to improve the wireless sensor network performance of WSNs a few deep learning techniques is conducted in [27][28]. According to the current situation, routing decisions can be made similarly to those made by a humanoid mind using machine learning algorithms.…”