# A Secure Communication in IoT Enabled Underwater and Wireless Sensor Network for Smart Cities
###### Abstract  
Nowadays, there is a growing trend in smart cities. Therefore, the Internet of Things (IoT) enabled Underwater and Wireless Sensor Networks (I-UWSN) are mostly used for monitoring and exploring the environment with the help of smart technology, such as smart cities. The acoustic medium is used in underwater communication and radio frequency is mostly used for wireless sensor networks to make communication more reliable. Therefore, some challenging tasks still exist in I-UWSN, i.e., selection of multiple nodes' reliable paths towards the sink nodes; and efficient topology of the network. In this research, the novel routing protocol, namely Time Based Reliable Link (TBRL), for dynamic topology is proposed to support smart city. TBRL works in three phases. In the first phase, it discovers the topology of each node in network area using a topology discovery algorithm. In the second phase, the reliability of each established link has been determined while using two nodes reliable model for a smart environment. This reliability model reduces the chances of horizontal and higher depth level communication between nodes and selects next reliable forwarders. In the third phase, all paths are examined and the most reliable path is selected to send data packets. TBRL is simulated with the help of a network simulator tool (NS-2 AquaSim). The TBRL is compared with other well known routing protocols, i.e., Depth Based Routing (DBR) and Reliable Energy-efficient Routing Protocol (R-ER\(P^{2}\)R), to check the performance in terms of end to end delay, packet delivery ratio, and energy consumption of a network. Furthermore, the reliability of TBRL is compared with 2H-ACK and 3H-RM. The simulation results proved that TBRL performs approximately 15% better as compared to DBR and 10% better as compared to R-ER\(P^{2}\)R in terms of aforementioned performance metrics. topology discover; reliable; routing protocol; smart cities 1  
[PERSON], [PERSON], [PERSON] 4, [PERSON]. underwater objects, which is later known as IoT enabled Underwater and Wireless Sensor Networks (I-UWSN s). The smart objects are the different types of sensors, i.e., Autonomous Underwater Vehicles (AUVs), buoy, ship, watchman nodes, etc. Therefore, I-UWSN architecture is a novel class of IoT and is expected to support various practical applications, such as underwater exploration, environment monitoring, and disaster prevention. With these applications, I-UWSN is considered tp be one of the potential technologies towards the development of smart cities [1; 2]. I-UWSN is getting the attention of academia and researchers due to several reasons. One of the main reasons is that the 71% Earth is approximately covered by water and only less than 10% from it is explored. Therefore, it is an emerging technology, which promises the exploration and monitoring of the oceanic environment. There are different ways to deploy sensor nodes in I-UWSN for the aforementioned purposes. The nodes can be randomly deployed or in the form of a grid and tree-structure. Firstly, to provide reliable communication, each sensor node has computational, communication, and intelligence capabilities to deal with a smart environment, as in smart cities [3; 4]. Secondly, node sense the data and flood it towards the destination node. State of the art I-UWSN applications are environmental monitoring, disaster warning, assisted navigation, natural resources exploration, and military applications [4; 5; 6]. Several routing protocols have been proposed for the aforementioned applications. Existing terrestrial network routing protocols cannot be used in underwater and smart city communication [7; 8] due to their unique characteristics of communication medium, e.g., the limited bandwidth due to the uses of the acoustic medium. The speed of acoustic medium is five magnitudes less when compared to that of the radio frequency; therefore, the magnitude of propagation delay occurs in underwater environment is five times higher when compared to terrestrial environment.