# An Energy Balance Clustering Routing Protocol for Intra-Body Wireless Nanosensor Networks
## 1 Introduction
Because of the adoption of the energy harvesting mechanism, the consideration of the tradeoff between energy harvesting and energy consumption, and the establishment of multi-hop routing based on the transmission characteristics of the terahertz channel, the routing protocol can maximize the throughput of the network while ensuring that the network lifetime is infinite. Using the energy harvesting mechanism to make the network lifetime infinite is a major innovation in this protocol. However, the protocol proposed in this paper is too complicated. In the simulation, the maximum number of hops is two, which is not enough for the practical application of the routing in WNSNs. [PERSON] and [PERSON] take into account the current state of energy collected by the communication nodes, and proposed an energy model based on the Markov decision process for data propagation [15]. However, due to the complexity of the proposed model, the authors adopted a lightweight heuristic scheme. [PERSON] et al. proposed a multipath routing protocol EHMR [16] based on energy harvesting. The protocol uses a piezoelectric energy harvesting system to break through the bottleneck of node energy and quantify the contribution of nodes joining paths through the game routing model and establishes multiple feasible paths to improve the stability of the transmission. However, in the route maintenance phase of the EHMR protocol, the forwarding failure is handled by switching the route, and the delay is exchanged for the transmission reliability, which is not applicable to the iWNSN with high delay requirement. At present, the research on routing protocols is still in infancy, although [17] proposed a cluster-based network topology, the proposed routing proposal did not consider the characteristics of the intra-body nanonetwork firstly, and secondly there was no reasonable cluster head node update mechanism. In addition, the author did not give a routing decision process for nodes between clusters. Therefore, we will study the routing protocol of iWNNSNs in this paper that considers the special application environment in the human body. Due to the small size of the nanosensors, the calculation and processing capabilities of the nano-nodes are limited, and the energy they store is also very limited. However, the nanosensor is very easy to deploy because of its small size. Usually, many nano-nodes are deployed in the target area to ensure that enough data can be collected to complete the monitoring task. Due to the large scale of the network and the small communication range of the nano-nodes, clustering is used to realize data transmission. In response to the above problems, we propose an Energy Balance Clustering Routing protocol (EBCR). The protocol adopts a new layered clustering method to reduce the communication load of the nano-nodes, and it also can reduce the number of member nodes in the cluster, and the data packet within the cluster can be transmitted to the cluster head in one hop. In addition, by continuously updating the cluster head node, the node with higher residual energy is selected as the cluster head, which prevents the cluster head node from exhausting energy due to frequent data forwarding, and can also balance the energy consumption in the network. Finally, the cluster head nodes transmit data to the nano control node through multi-hop routing. When selecting the next hop, the distance and the channel capacity is compromised to ensure that the data packet is successfully transmitted while reducing the energy consumption. The remainder of this paper is organized as follows. In Section 2, the system model is introduced. Next, the clustering routing framework is described in Section 3. In Section 4, we introduce the simulation scenario and define four evaluation indicators: average residual energy, number of dead nodes, data packet transmission success rate and control overhead to evaluate the performance of the new EBCR protocol.