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Energy conservation is one of the most critical challenges in the Internet of Things (IoT). IoT devices are incredibly resource-constrained and possess miniature power sources, small memory, and limited processing ability. Clustering is a popular method to avoid duplicate data transfer from the participant node to the destination. The selection of the cluster head (CH) plays a crucial role in gathering and aggregating the data from the cluster members and forwarding the data to the sink node. The inefficient CH selection causes packet failures during the data transfer and early battery depletion nearer to the sink. This paper proposes a cluster tree-based routing protocol (CT-RPL) to increase the life span of the network and avoid the data traffic among the network nodes. The CT-RPL involves three processes, namely cluster formation, cluster head selection, and route establishment. The cluster is formed based on the Euclidean distance. The CH selection is accomplished using a game theoretic approach. Finally, the route is established using the metrics residual energy ratio (RER), queue utilization (QU), and expected transmission count (ETX). The simulation is carried out by using a COOJA simulator. The efficiency of a CT-RPL is compared with the Routing Protocol for Low Power and Lossy Networks (RPL) and energy-efficient heterogeneous ring clustering routing (E2HRC-RPL), which reduces the traffic load and decreases the packet loss ratio. Thus, the CT-RPL enhances the lifetime of the network by 30–40% and the packet delivery ratio by 5–10%.

Internet of Things (IoT) is a recent paradigm to improve human lifestyle. Nowadays, number devices are connected to the Internet drastically. Thus, the people can control and monitor the physical things in real-time without delay. The IoT plays a vital role in all kind of fields in our world such as agriculture, livestock, transport, and healthcare, grid system, connected home, elderly people carrying system, cypher physical system, retail, and intelligent systems. In IoT energy conservation is a challenging task, as the devices are made up of low-cost and low-power sensing devices and local processing. IoT networks have significant challenges in two areas: network lifespan and energy usage. Therefore, the clustering is a right choice to prolong the energy in the network. In LEACH clustering protocol, sometimes the same node acts as CH again and again probabilistically. To overcome these issues, this paper proposes the Energy-Aware Cluster-based Routing (EACRLEACH) protocol in WSN based IoT. The Cluster Head (CH) selection is a crucial task in clustering protocol inWSN based IoT. In EACR-LEACH, the CH is selected by using the routing metrics, Residual Energy (RER), Number of Neighbors (NoN), Distance between Sensor Node and Sink (Distance) and Number of Time Node Act as CH (NTNACH). An extensive simulation is conducted on MATLAB 2019a. The accomplishment of EACR-LEACH is compared to LEACH and SE-LEACH. The proposed EACR-LEACH protocol extends the network's lifetime by 4%-8% and boosts throughput by 16%-24%. [ABSTRACT FROM AUTHOR]

Energy conservation is a major challenge in the Internet of Things (IoT) as the number of resource‐constrained devices is connected to the network. Routing plays a vital role in IoT to extend the lifespan of the network. Routing protocol for low‐power and lossy networks (RPL) is a standard routing protocol in IoT. The parent selection is a crucial role in the routing process to exchange the data. In RPL, the researchers have introduced a single metric, composite metric, and multiobjective optimization algorithm for parent selection. However, the improper parent selection causes the packet losses, congestion among the network nodes, depletes more energy, and increases the convergence time. To overcome these issues, this article proposes energy efficient optimal parent selection in RPL (EEOPS‐RPL) using firefly optimization algorithm to extend the lifespan of the IoT network. In EEOPS‐RPL, each node in the network is considered to be firefly and also calculates the current location of firefly, attraction of the fireflies, random function, velocity, and the global best values in the network. Residual energy and expected transmission count are attractiveness parameters and distance is a movement parameter to choose the optimum parent in the destination‐oriented directed acyclic graph for data transmission. The simulation is conducted using COOJA. The EEOPS‐RPL provides better performance in comparison to the efficient parent selection for RPL (EPC‐RPL) and the E‐RPL. The EEOPS‐RPL improves the packet transmission ratio and lifespan of the network by 2% to 5%, and 5% to 10%, respectively, compared with EPC‐RPL and E‐RPL. In EEOPS‐RPL, each participant node applies the firefly algorithm over the parent node information such as distance, residual energy, and expected transmission count through DODAG information object control message to pick the best parent node in the DODAG. The firefly algorithm provides the fast convergence that able to choose the optimal parent quickly. Thus, it avoids the packet loss during the route establishment in network. Thus, EEOPS‐RPL extends the lifespan of the network and reduces the convergence time. [ABSTRACT FROM AUTHOR]

Nowadays, there is a drastic increase in the number of sensors enabled devices connected to the Internet. Low power and lossy network (LLN) is a network, which consists of several embedded devices with limited memory, power and processing resources. Energy preservation and network lifetime enhancement are the major challenges in LNN. Hence, the routing plays a vital role in LLN, as an Internet of Things (IoT) device need to take the decision accordingly. In LNN, the inefficient route selection results in increased energy depletion, traffic and packet loss ratio. The proposed work introduces Load and battery discharge index (BDI) based composite routing metric in IPV6 Routing Protocol for Low power and lossy network (RPL). The COOJA simulator used to evaluate the performance of the proposed work. It provides the better result in terms of network lifetime and packet delivery ratio (PDR) against the routing metric such as hop count, ETX, RER, RER (BDI) and traffic load. [ABSTRACT FROM AUTHOR]