A Machine Learning-Based Approach for Network Optimization in WSNs

With the advancements in interconnected devices and automation, wireless sensor networks have gained substantial importance. Energy constraint is one of the main issues that wireless sensor networks (WSNs) must deal with. Moreover, to enhance the effectiveness, it is necessary to reduce the latency as much as possible. Wireless sensor networks can be optimized for latency and energy consumption using a variety of protocols, with their own pros and cons. This paper investigates different aspects related to wireless sensor networks along with the relevant approaches. The intent of this paper is to present a reinforcement learning-based approach for optimized routing in WSNs. The protocol is designed to cater to the constraints of limited energy and latency, with the evaluation of the proposed algorithm in terms of network lifetime and latency.