An Energy-Efficient Redundant Transmission Control Clustering Approach for Underwater Acoustic Networks

Abstract

Underwater Acoustic Network (UAN) is an emerging technology with attractive applications. In such type of networks, the control-overhead, redundant inner-network transmissions management, and data-similarity are still very challenging. The cluster-based frameworks manage the control-overhead and redundant inner-network transmissions persuasively. However, the current clustering protocols consume a big part of their energy resources in data-similarity as these protocols periodically sense and forward the same information. In this paper, we introduce a novel two-level Redundant Transmission Control (RTC) approach that ensures the data-similarity using some statistical tests with an appropriate degree of confidence. Later, the Cluster Head (CH) and the Region Head (RH) remove the data-similarity from the original data before forwarding it to the next level. We also introduce a new spatiotemporal and dynamic CH role rotation technique which is capable to adjust the drifted field nodes because of water current movements. The beauty of the proposed model is that the RH controls the communications and redundant transmission between the CH and Mobile Sink (MS), while the CH controls the redundant inner-network transmissions and data-similarity between the cluster members. We conduct simulations to evaluate the performance of our designed framework under different criteria such as average end-to-end delay, the packet delivery ratio, and energy consumption of the network with respect to the recent schemes. The presented results reveal that the proposed model outperforms the current approaches in terms of the selected metrics.

An Energy Optimization Clustering Scheme for Multi-Hop Underwater Acoustic Cooperative Sensor Networks

“…However, it is really difficult to obtain the precise location information in the underwater environment. In [30], Ahmed et al proposed to reduce the system energy consumption by using the region node and the CH node to control the redundant transmission. Furthermore, they considered the motion of the underwater node caused by the ocean current in their study.…”

Underwater Wireless Sensor Networks: An Energy-Efficient Clustering Routing Protocol Based on Data Fusion and Genetic Algorithms

“…However, the multi-hop routing path has not been optimized in [33]. Ahmed et al introduced an underwater clustering protocol according to redundant transmission control (RTC), which eliminates the data redundancy at the CHN level and at the region head level [6]. Moreover, the authors presented a dynamic CHN rotation method, which can balance the energy consumption and improve the reliability of the network.…”

“…The responsibility of the sensor nodes is to monitor the underwater environment such as the temperature, and send the collected data to a sink node (SN) through a single hop or multiple hops [5]. The SN, located on the sea surface, has the ability to receive the data from underwater sensor nodes through acoustic signals and send the received data to terrestrial network devices through radio signals [6]. In the underwater environment, the radio signals face the absorption problem and attenuate quickly [7].…”

“…Sci. 2021, 11, 312. https://doi.org/10.3390/app11010312 https://www.mdpi.com/journal/applsci communications because it is less affected by attenuation, scattering, as well as absorption loss [6]. The acoustic signals propagate slowly, which causes the high propagation delay [8].…”

A Clustering Routing Algorithm Based on Improved Ant Colony Optimization Algorithms for Underwater Wireless Sensor Networks

“…Additionally, to alleviate the problems of data collision and traffic load balance, it is important to design a reliable network topology [11]. Many studies have shown that the clustering routing algorithm is capable of saving energy, avoiding collisions, and balancing traffic load because it employs the clustering topology and uses a multi-hop mechanism during the inter-cluster data transmission [12,13]. In clustering routing algorithms, the network is divided into many clusters and each cluster consists of one cluster head node (CHN) and several cluster member nodes (CMNs) [14].…”