# Dwarf Mongoose Optimization-Based Secure Clustering with Routing Technique in Internet of Drones
## 1 Introduction  
With the growth of modern wireless communication technology, the Internet of things (IoT) is becoming a broadly utilized technology in the domain of several intellectual applications and services [1]. Eventually, the rise in interconnectivity between numerous things or objects has produced massive data. But, such IoT applications were not as muchas effective for making decisions, and data perception lacked the participation of human cognition processing. Currently, cognitive computing has grabbed the attention of IoT authors [2]. The IoT with the cognitive capability called cognitive IoT (CIoT) allows an object or things to study several data from devices or gadgets which is connected, i.e., sensors, UAVs, etc. Drones or unmanned aerial vehicles (UAV) are becoming a developing technology that has communication, sensing, storage, and processing abilities [3]. It is employed in diverse industries such as the Internet of things (IoT) scenarios, intelligent transportation systems, and smart cities. The placement of a swarm of UAVs for IoT services is a reality for numerous applications namely tracking and surveillance, package delivery, search and rescue, and public safety [4]. Such IoT-assisted applications facilitate the new pattern called the Internet of drones (IoD). It could offer a capability to a UAV drone network for accessing drones and users through the Internet. The features of drones are easy mobility and deployment, which makes UAVs helpful for transmission. Since drones are movable, it is utilized as information carriers i.e., sending the data to remote destinations [5]. When the destination does not in direct interaction range of the UAV, the transmission happens through multiple hops. The swarm of UAVs cooperates to constitute a network for sending the data to the destinations. Though reliability, survivability, and scalability were the distinctive traits of IoD; however, it put forward many complexities in transmissions and drones networking [6]. The UAV's higher mobility makes the topologies very rapid, leading to communication issues.  
The self-organizing UAV network constitutes a plurality of clusters by a clustering technique, with every cluster made up of some cluster members (CM) and a cluster head (CH) [7]. Such CHs form the high-layer virtual backbone network and present two critical operations they are direct interactions between CHs and a medium for cross-cluster transmission. The CMs in the same cluster interact directly via a single hop; however, the data sent between clusters were initially forwarded to the CH, and then forwarded to the CH of the cluster in which the destiny node was positioned via the virtual backbone networks [8]. The CH after sends to the destiny nodes for achieving cross-cluster transmission. In a clustered IoD, when a compromised node was chosen as a CH, this node not just illegitimately acquired information from the normal node but even forge data distributed to the sink [9]. In addition, attackers could grab control of the entire network by compromising tiny CHs; compromising every CHs becomes a very alluring target for them. As a drone-related network suffers from the same susceptibilities, secure CH choosing for the IoD becomes vital for its successful operations [10].