Energy-efficient Multilevel Clustering Protocol for Underwater Wireless Sensor Networks

Bansal, Rubal; Maheshwari, Saurabh; Awwal, Payal

doi:10.1109/confluence.2019.8776984

Cited by 6 publications

(4 citation statements)

References 31 publications

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“…A landslide detection system uses a wireless sensor network to detect minute soil movements and changes in several parameters that may happen before or during a landslide. It may be feasible to predict the occurrence of landslides using the data collected well before when they occur [73,74].…”

Section: Detection Of Landslidesmentioning

confidence: 99%

Review of Localization and Clustering in USV and AUV for Underwater Wireless Sensor Networks

Sathish

Venkata

Anbazhagan

et al. 2023

Telecom

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Oceanographic data collection, disaster prevention, aided navigation, critical observation sub-missions, contaminant screening, and seaward scanning are just a few of the submissions that use underwater sensor hubs. Unmanned submerged vehicles (USVs) or autonomous acoustic underwater vehicles (AUVs) through sensors would similarly be able to explore unique underwater resources and gather data when utilized in conjunction with integrated screen operations. The most advanced technological method of oceanic observation is wireless information routing beneath the ocean or generally underwater. Water bottoms are typically observed using oceanographic sensors that collect data at certain ocean zones. Most research on UWSNs focuses on physical levels, even though the localization level, such as guiding processes, is a more recent zone. Analyzing the presenting metrics of the current direction conventions for UWSNs is crucial for considering additional enhancements in a procedure employing underwater wireless sensor networks for locating sensors (UWSNs). Due to their severely constrained propagation, radio frequency (RF) transmissions are inappropriate for underwater environments. This makes it difficult to maintain network connectivity and localization. This provided a plan for employing adequate reliability and improved communication and is used to locate the node exactly using a variety of methods. In order to minimize inaccuracies, specific techniques are utilized to calculate the distance to the destination. It has a variety of qualities, such as limited bandwidth, high latency, low energy, and a high error probability. Both nodes enable technical professionals stationed on land to communicate data from the chosen oceanic zones rapidly. This study investigates the significance, uses, network architecture, requirements, and difficulties of undersea sensors.

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Section: Detection Of Landslidesmentioning

confidence: 99%

Review of Localization and Clustering in USV and AUV for Underwater Wireless Sensor Networks

Sathish

Venkata

Anbazhagan

et al. 2023

Telecom

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“…However, it compromises E2ED due to which clustering based routing is not a good choice for applications where delay is the main concern. Another protocol named Energy-efficient Multilevel Clustering Protocol for UWSNs [21] is proposed in which the clusters or logical levels are developed on the basis of residual energy. Nodes having a similar level of energy are considered in the same level.…”

Section: Related Workmentioning

confidence: 99%

Reliable Path Selection and Opportunistic Routing Protocol for Underwater Wireless Sensor Networks

et al. 2020

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The increased need to gather scientific data and the renewed drive to explore underwater natural resources has led more and more researchers to study the underwater environment. This has resulted in enormous attention being given to Underwater Wireless Sensor Networks (UWSNs) all over the world. However, UWSNs are faced with some major challenges including harsh environment, higher propagation delay, and limited battery power of the sensor nodes. To address these challenges, several routing schemes have been proposed. In this paper, we propose a routing strategy, called Reliable Path Selection and Opportunistic Routing (RPSOR) for UWSNs, which is a significantly improved version of Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR). RPSOR is based on three main factors: Advancement factor (ADV f), which depends on the depth of current as well as next hop forwarding node; Reliability index (REL i), which depends on the energy of the current forwarder as well as average energy in the next expected forwarding region; and Shortest Path Index (SP i), which is calculated on the basis of number of hops to the sink and average depth of neighbors in the next expected hop. To deal with the void hole problem and improve the Packet Delivery Ratio (PDR), we follow the more reliable path towards the sink by calculating REL i for a node. At the end, we perform extensive simulations and compare our proposed scheme with WDFAD-DBR, the results of which prove that RPSOR shows better performance in terms of PDR and energy tax in comparison to WDFAD-DBR. However, the proposed work compromises end-to-end delay in sparse networks. INDEX TERMS Underwater wireless sensor networks (UWSNs), reliability, potential forwarding nodes (PFNs), end-to-end delay (E2ED), packet delivery ratio (PDR), priority function (PF), void hole.

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“…The selection of CHNs and the routing rules are in the light of node energy, but the influence of the distance has not been considered. Bansal et al provided a multilevel underwater clustering protocol [36], where the cluster and the logical level are formed based on the remaining energy of nodes rather than the geography. The nodes with the similar level of energy are thought to be in the same level and only the nodes with the highest level of energy communicate with the SN.…”

Section: The Clustering Routing Protocolmentioning

confidence: 99%

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

2020

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Due to the limited battery energy of underwater wireless sensor nodes and the difficulty in replacing or recharging the battery underwater, it is of great significance to improve the energy efficiency of underwater wireless sensor networks (UWSNs). We propose a novel energy-efficient clustering routing protocol based on data fusion and genetic algorithms (GAs) for UWSNs. In the clustering routing protocol, the cluster head node (CHN) gathers the data from cluster member nodes (CMNs), aggregates the data through an improved back propagation neural network (BPNN), and transmits the aggregated data to a sink node (SN) through a multi-hop scheme. The effective multi-hop transmission path between the CHN and the SN is determined through the enhanced GA, thereby improving transmission efficiency and reducing energy consumption. This paper presents the GA based on a specific encoding scheme, a particular crossover operation, and an enhanced mutation operation. Additionally, the BPNN employed for data fusion is improved by adopting an optimized momentum method, which can reduce energy consumption through the elimination of data redundancy and the decrease of the amount of transferred data. Moreover, we introduce an optimized CHN selecting scheme considering residual energy and positions of nodes. The experiments demonstrate that our proposed protocol outperforms its competitors in terms of the energy expenditure, the network lifespan, and the packet loss rate.

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Energy-efficient Multilevel Clustering Protocol for Underwater Wireless Sensor Networks

Cited by 6 publications

References 31 publications

Review of Localization and Clustering in USV and AUV for Underwater Wireless Sensor Networks

Review of Localization and Clustering in USV and AUV for Underwater Wireless Sensor Networks

Reliable Path Selection and Opportunistic Routing Protocol for Underwater Wireless Sensor Networks

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

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