Energy-Aware Multi-level Routing Algorithm for Two-Tier Wireless Sensor Networks

An Enhanced Cluster-Based Routing Model for Energy-Efficient Wireless Sensor Networks

“…11, No. 2, June 2023: 586 -609 588 a directed virtual backbone (DVB) of CHs firmly grounded at the sink [11]. Other approaches to adaptive energy-efficient and clustering routing techniques for WSNs that have been proposed also include a Hybrid Energy-Efficient Distributed (HEED) clustering technique for ad-hoc sensor networks, which uses a distributed method to choose CH nodes so that the CH nodes are evenly distributed throughout the network [12], a Centralized Energy-Efficient Routing Protocol (CEERP) for WSNs, which uses an iterative random algorithm and chooses a clustering strategy with uniform node density where each CH is responsible for the equivalent number of member nodes in order to prevent CH overload [13], and an iterative topology reconstruction mechanism in selecting CH nodes as determined by the residual energy of each node [14].…”

“…Also, various routing schemes were proposed in order to provide robust network stability, increase sensor network lifetime, and reduce the energy hole problem in WSN. For instance, an energy-aware routing scheme that employs a centralized single-hop evolutionary routing protocol to improve the selection of CH for cluster formation [11] [15], iterative random selection of the optimal route based on node residual energy and node distribution density in each cluster [16], a virtual hybrid potential field that forwards data packs using the normalized field strength with respect to the residual energy of each node Iterative topology reconstruction mechanisms primarily based on residual energy of the nodes and transmission distance during CH election [17], iterative random selection technique to choose a CH node using residual energy and node transmission distance [2], a decentralized iterative topology reconstruction mechanism to choose the CH node using residual energy and node transmission distance [18], a technique called the Stable Election Protocol Energy Consider (SEP-EC) dependent on node residual energy [19], Q-learning-based data-aggregation-aware energy-efficient routing technique that leveraged on reinforcement learning to optimize rewards [20], and an Energy-Efficient Layered Routing Protocol (EELRP) that segregates the network into some concentric circles of different radii [21]. These routing-based methods offered important knowledge about energy-balanced data collection protocols for the WSN.…”