# CT-RPL: Cluster Tree Based Routing Protocol to Maximize the Lifetime of Internet of Things
## 1 Introduction  
In today's world, the Internet of Things (IoT) provides a platform for the researchers to extend communication paradigm to new and varied levels. Computing and sensor devices in the IoT are connected to the Internet, and provide services anytime, anyplace, and anywhere [1; 2; 3; 4; 5]. It consists of homogeneous and heterogeneous systems and devices including computers, mobiles, laptop, home appliances, consumer electronics, sensors, and actuators [6; 7; 8; 9; 10]. The IoT devices and systems have been used to sense the location of the objects, relay sensor and location information, establish secure communication channels, create on-the-go ad-hoc infrastructures, and integrate with Cloud forthe remote control and processing of information [11; 12]. In many recent works, the IoT has been used in building automation, smart cities, smart farming, smart home, smart-retail management, and smart grid systems, among many more [13; 14]. The low power and lossy networks (LLN) is an IoT network that includes low power, limited processing capacity, and limited on-board memory and communication capabilities [15; 16; 17]. The routing protocol for low power and lossy networks (RPL) is a standardized protocol for LLNs. The RPL is a distance-vector routing protocol, which supports point-to-multipoint, point-to-point, and multipoint-to-point traffic patterns in LLN [18; 19]. In RPL, the parent selection is performed on the basis of the objective function (OF). The OF function defines the method of choosing the finest parent in the destination-oriented directed acyclic graph (DODAG). The RPL rank shows the participant node, how far from the root of the DODAG [20; 21]. In RPL, rank indicates the number of hops between participant node and DODAG root. Initially, the RPL protocol is introduced with a single routing metric to pick the parent node in the DODAG. Many research works have focused on expanding the lifespan of the network, reducing the data traffic across the network, and improving the quality of services, hence improving the route stability during the data transmission. The standard RPL protocol is based on the hop count, which is called an objective function-0 (OF-0). The expected transmission count is a routing metric, which is used to pick the efficient parent for the quality of services. Although various parameters, including expected lifetime [22], load balance, residual energy, and sigma routing metric [23], are introduced to prolong the lifespan of the network and quality of service, the single metric-based routing selection alone is not effective. Recent works have focused on the multiple routing metrics for selecting the parent to establish an efficient route. These works consider the routing metric residual energy and battery depletion index [24], queue utilization and expected transmission count, survivability of path, congestion, and interference so as to extend the network lifetime in different scenarios [25]. The average weighted method is not suitable for composite routing metrics with maximization and minimization properties of the network node and link metrics [26]. Researchers in [27] used the composite routing metric-based routing selection using fuzzy logic. Fuzzy logic is applied on the routing metric's expected transmission count and energy consumption, link quality level, end-to-end delay, hop count, and residual energy for selecting the best parent in the parent list. However, the composite routing metrics are only suitable for specific applications that support multi-hop routing. A joint energy supply and routing path selection algorithm for WSN was proposed by [PERSON] [28] to conserve the energy among the network nodes. The path selection algorithm adjusts the parameters dynamically that satisfy the network condition in order to extend the lifetime of the network. [PERSON] et al. proposed a hybrid architecture of distributed remote radio heads and a centralized baseband unit to improve the quality of service and conserve the energy in the network.