## 1 Introduction  
Smart coasts (SCs) are one of the key factors for the sustainable community [1]. The main objectives of the SC are to monitor the quality of water, the ecosystem, water pollution, seismic activity and management of the coastal zone(s). All of these objectives are hard to achieve without continuous detection, collection, monitoring, and management of the oceanographic parameters. This uninterrupted collection and communication of the aquatic parameters are not possible without Underwater Sensor Networks (USN) [2], which is one of the key technologies in the realm of SCs. USN consists of the battery operated nodes deployed in the aquatic environment, where each node has the capability to sense the physical aquatic and physical parameters, communicate the sensed parameters, and temporarily store a small amount of data due to limited storage. Sensed data is communicated to the Sink(s) that is/are floating at the sea surface that forward(s) data to the onshore monitoring station. Communication in the underwater environment poses many challenges for all the communication approaches that have been considered [3] e.g., radio or electromagnetic [4; 5], optical [6; 7], and acoustic communication modes [2; 8]. Electromagnetic signals at radio frequencies are more suitable for terrestrial communication and offer high bandwidth, low per bit energy, and small propagation delay. Hence, this communication method is enabled over the Sink(s) to communicate with the onshore monitoring station. However, electromagnetic signals at radio frequencies in the underwater environment observe severe attenuation that leads to a very large absorption loss due to high water conductivity. Similarly, the optical signals are not preferable in the aquatic environment because it requires the precise line of sight between sender and receiver, which is quite hard in the presence of the ocean current. Furthermore, the water turbidity severely limits the optical communication distance. Acoustic communication modality is one of the most widely and preferable for underwater networks, also called underwater acoustic sensor networks (UASNs). It faces challenges such as high error rate due to fading and multipath that limits the available bandwidth [9]. In addition to that, the acoustic speed in an aquatic environment is far less than radio communication in the terrestrial environment. All these factors limit the data routing, synchronization, and maintaining the network state information. Hence, the solutions designed for terrestrial sensor networks can not directly be applied to UASNs. Long propagation delay, high energy consumption, low bandwidth, and large error rate are the salient and intrinsic characteristics as well as the challenges of acoustic communication in the underwater networks. Most of these challenges are correlated with each other. Most of the vector based routing schemes proposed for the UASN employ holding time that is distributively computed by each node using the local node or network parameters, e.g., distance to sink, proximity to the center of the virtual pipeline between the sender and sink, distance to the previous hop sender and the receiving node, etc. First, nodes check either they are within the virtual pipeline or not. Once a node ensures that it is located within the virtual pipeline, then it estimates the holding time. Holding time is estimated every time when a node receives the first copy of the packet from downstream nodes. The timer is triggered and its duration is set to the estimated holding time period. Once the timer expires and if that node does not receive any other copy from its neighbors, it will forward the packet and all the other nodes will suppress the packet forwarding. A preferable forwarder must have the smallest holding time compared to its immediate neighbors and is desirable to forward the packet.