A Survey on Efficient Routing Strategies For The Internet of Underwater Things (IoUT)

The Internet of Underwater Things (IoUT) is an emerging technology that promised to connect the underwater world to the land internet. It is enabled via the usage of the Underwater Acoustic Sensor Network (UASN). Therefore, it is affected by the challenges faced by UASNs such as the high dynamics of the underwater environment, the high transmission delays, low bandwidth, high-power consumption, and high bit error ratio. Due to these challenges, designing an efficient routing protocol for the IoUT is still a trade-off issue. In this paper, we discuss the specific challenges imposed by using UASN for enabling IoUT, we list and explain the general requirements for routing in the IoUT and we discuss how these challenges and requirements are addressed in literature routing protocols. Thus, the presented information lays a foundation for further investigations and futuristic proposals for efficient routing approaches in the IoUT

An effective data-collection scheme with AUV path planning in underwater wireless sensor networks

Data collection in underwater wireless sensor networks (UWSNs) using autonomous underwater vehicles (AUVs) is a more robust solution than traditional approaches, instead of transmitting data from each node to a destination node. However, the design of delay-aware and energy-efficient path planning for AUVs is one of the most crucial problems in collecting data for UWSNs. To reduce network delay and increase network lifetime, we proposed a novel reliable AUV-based data-collection routing protocol for UWSNs. The proposed protocol employs a route planning mechanism to collect data using AUVs. The sink node directs AUVs for data collection from sensor nodes to reduce energy consumption. First, sensor nodes are organized into clusters for better scalability, and then, these clusters are arranged into groups to assign an AUV to each group. Second, the traveling path for each AUV is crafted based on the Markov decision process (MDP) for the reliable collection of data. The simulation results affirm the effectiveness and efficiency of the proposed technique in terms of throughput, energy efficiency, delay, and reliability. © 2022 Wahab Khan et al

Multilink and AUV-Assisted Energy-Efficient Underwater Emergency Communications

Recent development in wireless communications has provided many reliable solutions to emergency response issues, especially in scenarios with dysfunctional or congested base stations. Prior studies on underwater emergency communications, however, remain under-studied, which poses a need for combining the merits of different underwater communication links (UCLs) and the manipulability of unmanned vehicles. To realize energy-efficient underwater emergency communications, we develop a novel underwater emergency communication network (UECN) assisted by multiple links, including underwater light, acoustic, and radio frequency links, and autonomous underwater vehicles (AUVs) for collecting and transmitting underwater emergency data. First, we determine the optimal emergency response mode for an underwater sensor node (USN) using greedy search and reinforcement learning (RL), so that isolated USNs (I-USNs) can be identified. Second, according to the distribution of I-USNs, we dispatch AUVs to assist I-USNs in data transmission, i.e., jointly optimizing the locations and controls of AUVs to minimize the time for data collection and underwater movement. Finally, an adaptive clustering-based multi-objective evolutionary algorithm is proposed to jointly optimize the number of AUVs and the transmit power of I-USNs, subject to a given set of constraints on transmit power, signal-to-interference-plus-noise ratios (SINRs), outage probabilities, and energy, which achieves the best tradeoff between the maximum emergency response time (ERT) and the total energy consumption (EC). Simulation results indicate that our proposed approach outperforms benchmark schemes in terms of energy efficiency (EE), contributing to underwater emergency communications.Comment: 15 page

Autonomous Underwater Vehicle: 5G Network Design and Simulation Based on Mimetic Technique Control System

The Internet of Underwater Things (IoUT) exhibits promising advancement with underwater acoustic wireless network communication (UWSN). Conventionally, IoUT has been utilized for the offshore monitoring and exploration of the environment within the underwater region. The data exchange between the IoUT has been performed with the 5G enabled-communication to establish the connection with the futuristic underwater monitoring. However, the acoustic waves in underwater communication are subjected to longer propagation delay and higher transmission energy. To overcome those issues autonomous underwater vehicle (AUV) is implemented for the data collection and routing based on cluster formation. This paper developed a memetic algorithm-based AUV monitoring system for the underwater environment. The proposed Autonomous 5G Memetic (A5GMEMETIC) model performs the data collection and transmission to increase the USAN performance. The A5GMEMETIC model data collection through the dynamic unaware clustering model minimizes energy consumption. The A5GMemetic optimizes the location of the nodes in the underwater environment for the optimal data path estimation for the data transmission in the network. Simulation analysis is performed comparatively with the proposed A5Gmemetic with the conventional AEDG, DGS, and HAMA models. The comparative analysis expressed that the proposed A5GMeMEMETIC model exhibits the ~12% increased packet delivery ratio (PDR), ~9% reduced delay and ~8% improved network lifetime

DEKCS: a dynamic clustering protocol to prolong underwater sensor networks

Energy consumption is a critical issue in the design of wireless underwater sensor networks (WUSNs). Data transfer in the harsh underwater channel requires higher transmission powers compared to an equivalent terrestrial-based network to achieve the same range. However, battery-operated underwater sensor nodes are energy-constrained and require that they transmit with low power to conserve power. Clustering is a technique for partitioning wireless networks into groups where a local base station (cluster head) is only one hop away. Due to the proximity to the cluster head, sensor nodes can lower their transmitting power, thereby improving the network energy efficiency. This paper describes the implementation of a new clustering algorithm to prolong the lifetime of WUSNs. We propose a new protocol called distance- and energy-constrained k-means clustering scheme (DEKCS) for cluster head selection. A potential cluster head is selected based on its position in the cluster and based on its residual battery level. We dynamically update the residual energy thresholds set for potential cluster heads to ensure that the network fully runs out of energy before it becomes disconnected. Also, we leverage the elbow method to dynamically select the optimal number of clusters according to the network size, thereby making the network scalable. Our evaluations show that the proposed scheme outperforms the conventional low-energy adaptive clustering hierarchy (LEACH) protocol by over 90% and an optimised version of LEACH based on k-means clustering by 42%

A systematic review on energy efficiency in the Internet of Underwater Things (IoUT): recent approaches and research gaps

Due to the advancement of wireless communications, Internet of Things (IoT) becomes a promising technology in today’s digital world. For the enhancement of underwater applications such as ocean exploration, deep-sea monitoring, underwater surveillance, diver network monitoring, location and object tracking, etc., Internet of underwater things (IoUT) has been introduced. However, underwater communication suffers from energy consumption due to fluctuations of the underwater environment and operational factors according to the distributions of objects or vehicles in shallow and deep water. The IoT quality of service (QoS) in underwater communication networks is critically affected by the different energy factors related to networking and the physical layer. Network topology and routing protocol are two important major factors affecting the power consumption of IoUT nodes and vehicles. The clustering approach is considered the best choice for IoUT, however it may suffer from various influences related to the underwater environment. The optimisation-based AI technologies in clustering approaches enable to achieve of energy efficiency for IoUT applications. This paper provides a systematic review of different energy efficiency methodologies for IoUT, and classified them according to the strategies used, in addition to the research gaps in clustering-based approaches, and future directions

PB-ACR: Node Payload Balanced Ant Colony Optimal Cooperative Routing for Multi-Hop Underwater Acoustic Sensor Networks

For a given source-destination pair in multi-hop underwater acoustic sensor networks (UASNs), an optimal route is the one with the lowest energy consumptions that usually consists of the same relay nodes even under different transmission tasks. However, this will lead to the unbalanced payload of the relay nodes in the multi-hop UASNs and accelerate the loss of the working ability for the entire system. In this paper, we propose a node payload balanced ant colony optimal cooperative routing (PB-ACR) protocol for multi-hop UASNs, through combining the ant colony algorithm and cooperative transmission. The proposed PB-ACR protocol is a relay node energy consumption balanced scheme, which considers both data priority and residual energy of each relay node, aiming to reduce the occurrence of energy holes and thereby prolong the lifetime of the entire UASNs. We compare the proposed PB-ACR protocol with the existing ant colony algorithm routing (ACAR) protocol to verify its performances in multi-hop UASNs, in terms of network throughput, energy consumption, and algorithm complexity. The simulation results show that the proposed PB-ACR protocol can effectively balance the energy consumption of underwater sensor nodes and hence prolong the network lifetime

Novel Approach using Robust Routing Protocol in Underwater Acoustic Wireless Sensor Network with Network Simulator 2: A Review

In recent year wireless sensor network has been an emerging technology and promising technology in unveiling the riddle of the marine life and other underwater applications. As it is a permutation of computation, sensing and communication. In the 70% of the earth a huge amount of unexploited resources lies covered by oceans. To coordinate interact and share information among themselves to carry out sensing and monitoring function underwater sensor network consists number of various sensors and autonomous underwater vehicles deployed underwater. The two most fundamental problems in underwater sensor network are sensing coverage and network connectivity. The coverage problem reflects how well a sensor network is tracked or monitored by sensors. An underwater wireless sensor networks is the emerging field that is having the challenges in each field such as the deployment of nodes, routing, floating movement of sensors etc. This paper is concerned about the underwater acoustic wireless sensor network of routing protocol applications and UW-ASNs deployments for monitoring and control of underwater domains

Underwater acoustic sensor networks node localization based on compressive sensing in water hydrology

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