In Wireless Sensor Networks, network lifetime optimization has challenging and significant issue. Subsequently, most of the existing works delineate several factors to improve the network lifetime: by decreasing the amount of the consumption of energy, reducing latency, load balancing, clustering, efficient data aggregating and by minimizing the data transmission delays. This paper provides a review of recent techniques and presents a Machine Learning-based Optimized Hierarchical Routing Protocols for WSN Lifetime. Research has been done, and reviews have been studied to explore the energy management schemes using optimized routing approach and Machine Learning Adaptability for WSN’s. Further, recommend future directions related to the Optimized Clustering Approaches to enhance wsn lifetime.
Machine Learning-Based Optimized Hierarchical Routing Protocols for WSN Lifetime: A Review
