# REERP: A Region-Based Energy-Efficient Routing Protocol for IoT Wireless Sensor Networks
## 2 Related Work  
Various work has been completed in recent years. [PERSON] et al. [5] proposed the SSE path routing protocol as a sustainable, reliable, and flexible routing protocol for WSN-IoT. It uses the least populated route available to send the packets of data from the sender to the receiver. [PERSON] et al. [6] suggested the Advanced Zone-Stable Election Protocol (AZ-SEP), which takes into account the characteristics of various WSNs in IoT scenarios. The authors developed AZ-SEP and made a comparison with the conventional routing protocol known as LEACH. Compared to the existing LEACH convention, the suggested AZ-SEP convention outperforms it with an increase 64% in better results in the form of capacity and an increase in the number of live micro nodes to 2702 rounds, which can be used to extend the IoT lifecycle. [PERSON] et al. [7] suggested a method that is a variation of the AODV protocol and takes into account collisions and energy when establishing a route. The suggested method retrieves collision counts from the MAC layer and connection-relevant data from the PHY layer to create a path and help the network layer make routing decisions. [PERSON] et al. [8] proposed a reform of the routing protocol, which is dependent on the maximal parent-objective function count (MNP-OF) for the WSN-IoT based on the neighboring metric (N-metric). He tested and compared the proposed MNP based on the remaining energy (MRE) protocol to the standard routing protocol for lossy inexpensive networks (RPL). [PERSON] et al. [9] introduced Opportunistic Source Routing (OSR), which provides a flexible and trustworthy downward routing mechanism for WSNs. The authors discussed an analytical model and assesses the performance of OSR using simulations and testbed experiments conducted in the real world. [PERSON] et al. [10] discussed the CH, which uses the protocol named LTE-M, and the intracluster, which deploys the low power wide area network (LPWAN) self-networking protocol in the WSN. The number of cluster heads and the ideal scale inside each cluster are investigated using the conventional K-mean algorithm. Additionally, based on an enhanced K-means algorithm, a distributed dynamic cluster head selection and clustering strategy are provided. [PERSON] et al. [11] suggested a system in which optimized cluster-based routing having efficient energy and network longevity is increased by utilizing a strategy based on hierarchical routing for IoT applications in the context of 5G. Before the chaining phase is activated for the remaining transmitting data, the clustering phase is activated unless three-fourths of the nodes are deceased. [PERSON] et al. [12] developed a protocol that is intended to function in networks with a lot of traffic, since it frequently occurs in IoT applications for healthcare monitoring when numerous sources attempt to send messages to a receiver at the same time. Simulation analysis shows that the designed protocol works better in terms of data transmission, delay, packet delivery ratio, and the remaining energy of the node. [PERSON] et al. [13] suggested three RPL-based dynamic routing techniques and combined them into a custom IPv6 communication network for IoT. The test results demonstrate that, as compared to the conventional RPL solution, the suggested techniques have improved energy efficiency, network load balancing, etc. These techniques have been deployed in the OMNET++ simulator. [PERSON] et al. [14] concentrated on an effective cluster head election method that alternates the cluster head movements between nodes with higher levels of energy than other nodes. The updated version outperforms the LEACH protocol, according to the simulation study, by increasing throughput by 61%, lifetime by 66%, and residual energy by 65%. [PERSON] et al. [15] concentrated at the same time on wireless power and data transfer technology (SWIPT) and routing mechanisms and applied them to WSN clustering based on multi-hop, in which each cluster can interpret data and acquire energy from a transmitted radio transmitter.