In view of some features of great importance, e.g., the irregular topologies, multiple nodes, and variable structures of the Internet of things (IoT) networks, choosing the best routing protocols (RPs) directly impacts their efficiency. Wireless sensor networks (WSNs) hold limited sources of energy due to using batteries. For that reason, reducing energy consumption rate in the WSNs used in the IoT networks to extend their lifetime is one of the essential parameters which need to be taken into account. For IoT networks based on sensor networks, numerous routing strategies have been proposed so far, but this issue is still one of the most important challenges of this type of networks. This paper is proposed a novel inter-layer cluster based fast-lookup cuckoo filter-based RP (FLCFRP) for a battery-powered IoT network that focuses on two parameters: consume energy and throughput. In this method, routing is divided into intra- and inter-cluster parts. The fast-lookup cuckoo filter (FLCF)-based ad hoc on-demand distance vector (AODV) RP is accordingly employed as the base to discover the network topology which both intra- and inter-cluster RPs use its information. The FLCF is a new probabilistic filter suggested in this paper. In light of the key characteristics of this filter, viz., compression and high search speed, utilizing it instead of a routing table makes each node keep less data and find routes with a reduced amount of time and energy all through searches. The FLCFRP is simulated via the Objective Modular Network Testbed in C++ (OmNet++) 6.0.1, and then compared with other ones. The evaluation results demonstrate that the given protocol can boost network performance as compared to other related works with respect to energy consumption and throughput rates. Increasing the number of packets in this method improves the throughput rate by 34.16% and 33.43%, respectively, as compared to other methods.
