# CT-RPL: Cluster Tree Based Routing Protocol to Maximize the Lifetime of Internet of Things
## 1 Introduction
It is noted that implementing the complex interference scenarios is challenging and takes more time for decision-making [29]. Moreover, the sensor devices can generate redundant data that may not have any useful information, all of which is forwarded to the DODAG root. As a solution, the authors in [30; 31; 32] used clustering as a necessary process for particular IoT applications, such as thermal monitoring, radiation monitoring, and weather monitoring. Clustering is an essential process for extending the lifespan of the network [33]. Such protocols resolve many issues like energy efficiency, scalability, reliability, and the network lifetime. The sensor nodes are located randomly in the IoT network, and the clusters form the following criteria. The cluster head (CH) is elected from each cluster, based on certain parameters, including residual energy, link quality, and queue size. The CH nodes forward the data packets to the sink [34]. The low-energy adaptive clustering hierarchy (LEACH) protocol is a standard clustering protocol in WSN [35]. A drawback in LEACH is the uneven distribution of clusters due to the random placements of nodes in the network; as a result, cluster members (CM's) are unable to send the data to the sink due to the CH node failure by the hotspot problem [36]. Researchers have worked on cluster-based RPL protocol and game theory-based CH selection for increasing the lifespan of IoT networks. This paper presents how the cluster-tree-based routing protocol (CT-RPL) is an improvement over the existing work in the cluster formation process, cluster head selection process, and route establishment process. The cluster is constructed based on the Euclidean distance of network nodes. The game theoretic approach is used to perform the CH selection. The route establishment process is based on the metric queue utilization (QU) and expected transmission count (ETX) to select the optimal CH parent for efficient data transfer and to extend the lifespan of the network. The main objectives of this paper are as follows. * An in-depth analysis of the literature concerning various clustering protocol proposed by various researchers to enhance the performance parameters for the IoT network in terms of energy efficiency, packet delivery ratio, and end-end delivery. * In CT-RPL, the virtual clusters are created using Euclidean distance. Later on, a game theoretic approach is proposed for selecting the effective CH node among the clusters. As a consequence, the nodes maintain effective energy utilization and exhibit a gradual depletion of the energy in the network nodes. * Additionally, the CT-RPL reduces the network traffic and avoids a bottleneck problem at the root. It is achieved by considering the routing metrics expected transmission count (ETX), residual energy ratio (RER), and queue utilization (QU) for data transmission. * The simulation is conducted, and the performance of the CT-RPL is compared with RPL and energy-efficient heterogeneous ring clustering routing (E2 HRC-RPL). The CT-RPL increases the network lifetime and decreases the end-to-end delay. The rest of the paper is organized as follows: Section 2 discusses the related works. Section 3 presents the cluster tree-based RPL (CT-RPL) using a game theoretical approach. The results and discussions are addressed in Section 4. Finally, the conclusion and future works of the paper are mentioned in Section 5.