Energy-Aware Multilevel Clustering Scheme for Underwater Wireless Sensor Networks

Abstract

The expansion of wireless sensor networks in the underwater environment resulted in underwater wireless sensor networks. It has dramatically impacted the research arena because of its widespread and real-time applications. But successful implementation of underwater wireless sensor networks faces many issues. The primary concern in the underwater sensor network is sensor nodes' energy depletion problem. In this paper, to improve the lifetime of the underwater wireless sensor network, an Energy-Aware Multi-level Clustering Scheme is proposed. The underwater network region is considered 3D concentric cylinders with multiple levels. Further, each level is divided into various blocks, representing one cluster. The proposed algorithm follows vertical communication mode from the sea bed to the surface area in a bottom-up fashion. Multiple levels with varying heights overcome the communication issues due to high water pressure towards the sea bed. Simulations are carried out to show the efficiency of the proposed algorithm, which performs better in terms of a prolonged network lifetime and average residual energy. The simulation result shows significant improvement in the network lifetime compared with current algorithms.

Multi Objective Energy Based Improved Jellyfish Swarm Optimization for Effective Cluster Head Discovery in UWSN

“…The implementation and simulation of the MOEIJSO-ACO are developed in MATLAB R2020b where the system uses the i5 processor and 6GB of RAM. The underwater scenario is designed with 50 sensors deployed in the area of 100 × 100 × 50𝑚 3 . The base station for this UWSN scenario is located in the coordinates of 50, 50, 𝑎𝑛𝑑 50 whereas the sensors are equipped with 5J of energy.…”

“…Accordingly, an exploration of the underwater environment is possible with the use of wireless technology [1,2]. UWSN is developing technology that is utilized for observing and discovering the changes in an aqueous environment [3]. UWSN is a wireless network that comprises a group of sensors and autonomous underwater vehicles for collecting and sensing data.…”

COVID-19 identification in chest X-ray images using intelligent multi-level classification scenario

“…Provided a mini batch B = { x 1 , x 2 , x 3 ... x n } of the batch size ( n ) and the normalized value is given by and the equation of linear transformation, thus Batch normalization is given by ( BN γ ). The transformation (β) is denoted by β: x 1 , x 2 , x 3 ... x n → y 1 , y 2 , y 3 ... y n ( 9 ) and is calculated as Where μ B the mini batch mean and is the variance, (β) and (γ) learnable parameters through back propagation. (ε) a positive value.…”

“…Test diagnosis is performed using Real-Time reverse Polymerase Chain Reaction (RRT-PCR) [ 7 , 8 ]. The biological samples, such as blood or sputum, are collected from the affected patients, and results are available within a couple of hours or a day [ 9 , 10 ]. The easiest way of diagnosing COVID-19 is using radiological imaging [ 11 , 12 ].…”

Energy and Path-Aware-Reliable Routing in Underwater Acoustic Wireless Sensor Networks

“…An energy-aware multilevel clustering scheme is suggested in [29], to increase the lifetime of the underwater wireless sensor network. The undersea network area is composed of 3D concentric cylinders with many layers, and each level is separated into several blocks, each of which represents a cluster.…”