The year-by-year increase in electricity consumption significantly affects all nations today from environmental, social, and economic perspectives. Various studies show that, among the contributors of this increase, power consumption of the equipment forming the Internet infrastructure is significant. Consequently, considerable attention is given to finding solutions to reduce power consumption of the systems that run the Internet. Current literature suggests that the optical backbone network is responsible for the majority of the consumed power, particularly at high traffic loads. This highlights the importance of formulating solutions to reduce power consumption in backbone networks. In this paper, we provide a comprehensive survey of the most relevant research efforts on minimizing power consumption of backbone networks. We categorize our review into four broad approaches: network redesign, traffic engineering, power-aware networking, and load-adaptive operation. We highlight the findings of relevant studies and provide an analysis of their limitations. We also evaluate the technological differences of similar work and identify a number of future directions. Finally, we demonstrate that the adoption of these technologies is gathering pace among prominent research bodies, device manufacturers, and network operators.

Traffic grooming and multipath routing are two techniques that are widely adopted to increase the performance of traditional wavelength division multiplexed networks. They have been recently applied in elastic optical networks to increase spectral efficiency. In this study, we investigate the potential gains by jointly employing the two techniques in combination with a realistic physical impairment model. To allocate resources and quantify spectral efficiency gains over existing impairment-aware schemes, we present an analytical optimization formulation for small networks and a heuristic for large networks. Through numerical simulations, we demonstrate that traffic grooming and multipath routing, together, increase spectral efficiency and reduce resource consumption over existing schemes. We show that the proposed scheme offers significant performance improvements in networks with low degrees of connectivity, high traffic loads, and long links.

This paper proposes a novel network planning strategy to jointly allocate physical layer resources together with the routing and spectrum assignment in transparent nonlinear flexible-grid optical networks with static traffic demands. The physical layer resources, such as power spectral density, modulation format, and carrier frequency, are optimized for each connection. By linearizing the Gaussian noise model, both an optimal formulation and a low complexity decomposition heuristic are proposed. Our methods minimize the spectrum usage of networks, while satisfying requirements on the throughput and quality of transmission. Compared with existing schemes that allocate a uniform power spectral density to all connections, our proposed methods relax this constraint and, thus, utilize network resources more efficiently. Numerical results show that by optimizing the power spectral density per connection, the spectrum usage can be reduced by around 20% over uniform power spectral density schemes.

Underwater wireless communications face significant challenges due to high attenuation, turbulence, and water turbidity. Traditional methods like acoustic and radio frequency (RF) communication suffer from low data rates (1 s), and limited transmission distances (<10 km).Visible Light Communication (VLC) emerges as a promising alternative, offering high-speed data transmission (up to 5 Gbps), low latency (<1 ms), and immunity to electromagnetic interference. This paper provides an in-depth review of underwater VLC, covering fundamental principles, environmental factors (scattering, absorption), and dynamic water properties. We analyze modulation techniques, including adaptive and hybrid schemes (QAM-OFDM achieving 4.92 Gbps over 1.5 m), and demonstrate their superiority over conventional methods. Practical applications—underwater exploration, autonomous vehicle control, and environmental monitoring—are discussed alongside security challenges. Key findings highlight UVLC’s ability to overcome traditional limitations, with experimental results showing 500 Mbps over 150 m using PAM4 modulation. Future research directions include integrating quantum communication and Reconfigurable Intelligent Surfaces (RISs) to further enhance performance, with simulations projecting 40% improved spectral efficiency in turbulent conditions.

The water treatment process involves a series of physical, chemical, and biological techniques and methods designed to remove contaminants, impurities, and undesirable substances from raw or untreated water to make it safe, clean, and usable. Adverse weather conditions, such as rainy seasons and floods, present significant challenges, and difficulties to the water treatment process. Alum is mainly used for reducing the turbidity of the water in the treatment process. In Sri Lanka, all water treatment plants use the Jar Test to determine the Alum dosage manually. They conduct Jar Tests to measure raw water quality in their laboratories. The Alum addition valve is set to a pre-determined quantity and the value is decided based on the experience of the technicians. Since there is no specific formula, the presence of an experienced technician is required to determine alum dosage using the Jar test. Thus, this study intends to propose an automated system for determining the optimum Alum quantity to be added to a given raw water sample. This is achieved by designing an Internet of Things (IoT)-enabled sensing device for measuring the water quality, which feeds data to a Machine Learning Model trained to predict the Alum quantity to be added. The task of the Machine learning model is to identify the pattern of raw water parameters and Alum dosage. By doing this, a could be provided a guideline for determining alum dosage instead of a manual Jar test and removed the necessity of experienced technician support always. A user-friendly web interface will allow the operators to customize the parameters according to the requirement and display a detailed analysis report. The predetermined quantity of Alum is transmitted to the output Alum adding value, to enhance its performance as an automated control rather than doing the addition process manually. This is a conceptual study on how to determine the Alum dosage using Raw water parameters and past experiment results.

The hybridization of Near-Field Communication (NFC) with Visible Light Communication (VLC) presents a promising framework for robust, secure, and efficient wireless transmission. By combining proximity-based authentication of NFC with high-speed and interference-resistant data transfer of VLC, this approach mitigates the inherent limitations of each technology, such as the restricted range of NFC and authentication challenges of VLC. The resulting hybrid system leverages NFC for secure handshaking and VLC for high-throughput communication, enabling scalable, real-time applications across diverse domains. This study examines integration strategies, technical enablers, and potential use cases, including smart street poles for secure citizen engagement, patient authentication and record access systems in healthcare, personalized retail advertising, and automated attendance tracking in education. Additionally, this paper addresses key challenges in hybridization and explores future research directions, such as the integration of Artificial Intelligence and 6G networks.