In underwater wireless sensor networks, the optimization strategies for localization might be seen as a new boon for the localization of sensor nodes (UWSNs). The techniques for optimization are those that repair the incorrect value, adapt it to the situation, and correct it. Because the algorithm could adapt to the constantly changing environment, it was widely used in terrestrial applications, and the same can be extended to the underwater environment with modifications. To address the localization issue that arises in UWSNs, the Underwater Salp Swarm Algorithm (USSA), a nature-inspired node localization algorithm, has been presented. With the help of this technique, an effort to discover a solution to the localization problem as an optimization problem is considered. The proposed algorithm is accessed in a simulated water environment. The energy is assigned to the anchor well as non-localized nodes, after deploying them in the simulated underwater network. The suggested algorithm is compared with other optimization algorithms, such as UPSO and UBOA, with reference to the computing time, localization accuracy, and the number of localized nodes. It is possible to localize a greater number of nodes in a much faster and more efficient way by considering the proposed algorithm.

The localization of non-localized sensor nodes is considered as a vital task in underwater communication, as it functions as the basic building block for several other capabilities, including tracking underwater nodes, coordinating the movements of an array of nodes and locating the underwater targets. Moreover, the localization also plays a key role in optimizing the medium access and routing protocols that facilitates the successful execution of Georouting, which in turn helps to get useful location-aware data. However, the localization is not an easy task as it faces several challenges, such as displacement of sensor nodes by water currents, multipath interference, high propagation delay, and fluctuations in the amplitude, etc. Another major challenge is the accurate determination of sensor node's 3D position coordinates in actual water environment. In this paper an attempt has been made in studying various approaches of existing localization and deployment techniques.

In this article, we explore a noteworthy aspect of Negative Capacitance FETs (NCFETs): the influence of transistor feature size on hysteresis behavior. The ferroelectric capacitance is directly proportional to the channel length, so as the transistor is scaled down, both the ferroelectric and MOS capacitances decrease. Our analysis shows that at a channel length of 16 nm, the ferroelectric capacitance falls below the MOS capacitance, resulting in the emergence of hysteresis in the device characteristics. Additionally, we investigate how scaling the transistor feature size impacts key phenomena such as negative Drain-Induced Barrier Lowering (DIBL), negative differential resistance (NDR), and the negative body effect coefficient. We also evaluate the performance of an NCFET-based inverter across different channel lengths and find that the device with a 22 nm channel length exhibits the lowest static and dynamic power dissipation among the cases studied.

The localization of underwater sensor network is essential for reliable data collection and monitoring for several ocean applications. For proper ocean exploration, it is necessary to find the location of all sensors accurately, as this can be important during military operations and resource collection. In this work, a range-free distance vector-hop (DV-hop) localization algorithm using the modified Selective Opposition Class Topper Optimization (SOCTO) algorithm is proposed. The algorithm uses a polynomial approximation to approximate the average hop distance between beacon nodes, yielding better results when the polynomial matches the relationship between the hop and physical distance. A rectification factor is included to improve distance measurements in underwater environments for variables such as temperature, salinity, Doppler shift, and multipath propagation. Specifically, DV-hop is a range-free method that allows anchor nodes to broadcast their locations to the other nearby nodes without requiring precisely known distances. The MATLAB simulations show that the modified SOCTO method showed a significant decrease in localization error as the number of beacon nodes increased. The error decreases to 0.24 at 25 beacon nodes, compared to 0.66 for DV-Hop and 0.42 for PSO corresponding to improvements of approximately 64% over DV-Hop and 43% over PSO. These outcomes demonstrate that the suggested Modified SOCTO-based DV-Hop algorithm outperforms the traditional DV-Hop and PSO techniques, resulting in significantly reduced localization errors.