# REERP: A Region-Based Energy-Efficient Routing Protocol for IoT Wireless Sensor Networks
## 2 Related Work
Based on ant colony optimization, [PERSON] et al. [16] proposed a new multi-agent routing protocol that effectively controls network services under realistic conditions. The suggested method locates the most energy-efficient best pathways, extending the useful life of the network in current and sequential scenarios. Compared to previous ACO-based routing protocols, the findings of the proposed technique have shown better output with respect to the network lifetime and energy utilization. [PERSON] et al. [17] concentrated on developing a novel node-swapping mode to extend the useful life of mobile nodes. The authors' method takes advantage of the configuration of nodes to reduce asymmetrical energy consumption by placing nodes in places with high power usage while maintaining the current topology. [PERSON] et al. [18] suggested a new protocol to improve energy conservation. The protocol prioritizes multiple aspects of energy optimization, such as reducing node energy usage, extending the lifetime of the entire network, improving system performance, improving network load balancing, and decreasing packet latency. [PERSON] et al. [19] covered design issues for schemes based on clusters, crucial parameters, and the categorization of clustering protocols. To assist users in choosing the best technique, existing techniques that are based on cluster and grid are examined while taking specific factors into account. The merits, drawbacks, and usability of various methods in certain situations are also described in a thorough summary. [PERSON] et al. [20] considered a refinement of the fundamental routing protocol for low power loss networks (RPL). The Energy Threshold RPL (ETRPL) protocol is recommended to reduce the energy use of the network. Additionally, an optimization model depending on the remaining energy of the desired parent is also proposed. [PERSON] et al. [21] discussed routing in WSN, particularly the AODV (Ad hoc on Demand Distance Vector) protocol, which is known to be particularly effective and useful for wireless services. The aim is to strengthen this protocol to consider the impact of communication topologies that can periodically transmit data from several nodes to a single node. [PERSON] et al. [22] suggest the environment-fusion multipath routing protocol (EFMRP) as a means of delivering reliable message forwarding in adverse conditions. The fundamental tenet of this strategy is to direct data packets to choose routes that optimize transmission delay, energy consumption, and routing survivability. The results demonstrate that EFMRP can substantially increase packet delivery rate and network longevity under challenging conditions. [PERSON] et al. [23] discussed the routing protocol and cluster formation based on a novel Neuro-Fuzzy rule for effective routing in WSN based on IoT. The presented routing algorithm delivered a maximum performance of the network in terms of the metrics measured, including energy utilization, packet delivery ratio, delay, and life expectancy of the network, according to the experiments conducted in this study utilizing the presented model. [PERSON] et al. [24] described the diffusion methods for a protected routing protocol, a data-centric protocol based on the Internet. This unique routing protocol is used to eliminate potential threats and attacks on the routing structure, and therefore, it is examined in terms of security considerations [25]. The authors of [26] stated that the election likelihood of picking cluster heads underwent changes due to the G-SEP approach, which factored in parameters such as distance, average distance, and residual energy of the advanced nodes. Additionally, the algorithm incorporated a central gateway node within the network and positioned the BS (Base Station) beyond the field's boundaries. Through simulations conducted in MATLAB R2017a, it was demonstrated that G-SEP outperformed the Zonal-Stable Election Protocol (ZSEP) in aspects such as coverage, stability period, and network lifetime extension.