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Average power consumption per user with respect to the increase in network access rate according to the results in [21]
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The concept of energy-efficient networking has begun to spread in the past few years, gaining increasing popularity. Besides the widespread sensitivity to ecological issues, such interest also stems from economic needs, since both energy costs and electrical requirements of telcos' and Internet Service Providers' infrastructures around the world sh...
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... determine the energy consumption of the network, they have used information about the quantity of various types of networking equipment and the power consumption of these pieces of equipment, as minutely described in [20]. As outlined in Figure 6, the model exploitation highlighted that, not surprisingly, the overall energy consumption will increase as the capacity of the network expands. In this respect, it is worth noting that today's average access rates are about 2 Mbps. ...
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... this respect, it is worth noting that today's average access rates are about 2 Mbps. Thus, starting from the data in Figure 6, today energy requirements of access networks account twice with respect to the core. The estimate in Figure 6 is also confirmed by an internal report from Alcatel-Lucent, which estimates that, in a typical ISP/telco network configuration, the power consumption of transport and core network represents about 30% of the overall network requirement, and access devices weigh for 70% (Figure 8). ...
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... starting from the data in Figure 6, today energy requirements of access networks account twice with respect to the core. The estimate in Figure 6 is also confirmed by an internal report from Alcatel-Lucent, which estimates that, in a typical ISP/telco network configuration, the power consumption of transport and core network represents about 30% of the overall network requirement, and access devices weigh for 70% (Figure 8). ...
Citations
... Integrar fuentes de energía renovable, como la solar y la eólica, en estas infraestructuras es esencial para mitigar su impacto ambiental. Las tecnologías de almacenamiento de energía, como las baterías de litio, están evolucionando rápidamente para satisfacer estas demandas crecientes de energía (Bolla et al., 2010). ...
Introducción: Este estudio revisa los desarrollos significativos en el procesamiento del lenguaje natural (PLN) y su impacto en la inteligencia artificial (IA), enfocándose en los avances en modelos de lenguaje, infraestructuras computacionales y la integración de métodos de aprendizaje automático. Metodología: Se realizó una revisión sistemática de la literatura utilizando las directrices PRISMA, centrada en artículos publicados entre 2022 y 2024. Se utilizó Web of Science, con términos de búsqueda como "procesamiento del lenguaje natural", "PLN". Resultados: La revisión destaca el papel crítico de los modelos de lenguaje avanzados como GPT-4, BERT y sus variantes en la mejora de la comprensión y generación del lenguaje natural, la importancia de infraestructuras de computación de alto rendimiento y el uso de técnicas de aprendizaje automático para optimizar tareas de PLN. Discusión: Los hallazgos confirman la relevancia de infraestructuras computacionales robustas y revelan nuevas perspectivas sobre la rápida evolución y adopción más amplia de técnicas de PLN en diversos sectores. Conclusiones: Es esencial continuar invirtiendo en infraestructuras computacionales y el desarrollo de modelos de lenguaje avanzados. La investigación futura debe ampliar el periodo de estudio, diversificar los idiomas, incluir literatura gris, realizar estudios longitudinales y explorar los desafíos de la ética y la privacidad en la implementación de técnicas de PLN.
... Unavoidably, as urbanization and population growth continue to rise, so does the need for energy. This elevated demand places tremendous strain on the energy infrastructure we currently have, making it imperative to create policies that encourage energy efficiency [1]. The demand response (DR) strategy is one such mechanism that is essential to intelligent energy systems and smart grids. ...
Smart meter data provide an in-depth perspective on household energy usage. This research leverages on such data to enhance demand response (DR) programs through a novel application of ensemble clustering. Despite its promising capabilities, our literature review identified a notable under-utilization of ensemble clustering in this domain. To address this shortcoming, we applied an advanced ensemble clustering method and compared its performance with traditional algorithms, namely, K-Means++, fuzzy K-Means, Hierarchical Agglomerative Clustering, Spectral Clustering, Gaussian Mixture Models (GMMs), BIRCH, and Self-Organizing Maps (SOMs), across a dataset of 5567 households for a range of cluster counts from three to nine. The performance of these algorithms was assessed using an extensive set of evaluation metrics, including the Silhouette Score, the Davies–Bouldin Score, the Calinski–Harabasz Score, and the Dunn Index. Notably, while ensemble clustering often ranked among the top performers, it did not consistently surpass all individual algorithms, indicating its potential for further optimization. Unlike approaches that seek the algorithmically optimal number of clusters, our method proposes a practical six-cluster solution designed to meet the operational needs of utility providers. For this case, the best performing algorithm according to the evaluation metrics was ensemble clustering. This study is further enhanced by integrating Explainable AI (xAI) techniques, which improve the interpretability and transparency of our clustering results.
... In addressing the challenge of minimizing the Internet's carbon footprint, the escalating demand for data and the subsequent surge in energy consumption pose significant hurdles [29]. Websites and digital applications, in their pursuit of greater data intensity, demand increased bandwidth and processing power, leading to higher energy consumption and associated carbon emissions [30]. ...
Placing sustainability at the core of computing practices, the industry is poised to pioneer positive changes and create a cleaner and more sustainable world for future generations. The environmentally sustainable computing (ESC) framework is introduced in this paper as an innovative solution to revolutionize sustainability practices across various computing domains and cover multiple aspects of sustainable information technology (IT). The ESC framework includes the entire lifecycle of computing systems, including critical stages such as design, development, monitoring, refactoring, and regulatory compliance. Through the adoption of the ESC framework, academia and industry stakeholders can gain a powerful tool to evaluate and measure sustainability factors across different computing domains and can integrate eco-friendly computing principles and patterns throughout their products and services. This can significantly reduce their carbon footprint while complying with environmental regulations. In addition to presenting the ESC framework, the paper showcases real-world use cases. The first involves a leading Italian bank, emphasizing the significance of monitoring and compliance in achieving sustainable solutions within carbon-aware computing. The second use case explores resource efficiency optimization in Kubernetes clusters, illustrating how the ESC framework aligns with cloud infrastructure management trends.
... The Internet infrastructure has developed in the last fifty years into a hyperscale digital infrastructure which significantly contributes to worldwide energy consumption, accounting for 2-3% of the world's annual electricity production [1], from which~40% is needed at the data plane [2]. This constitutes 33% of network operational expenditure (OPEX) [1]. ...
... The latter results from the ever-increasing user traffic/compute functions/management functions/service functions that enable operators to deploy resource overprovisioning and redundancy to cope with peak demand and provide some levels of reliability. An idle network system is assumed to have an energy consumption of~30-40% over the same system running at full capacity [2]. In addition, in typical networking devices, only roughly half of the energy consumption is associated with the data plane [2]. ...
... An idle network system is assumed to have an energy consumption of~30-40% over the same system running at full capacity [2]. In addition, in typical networking devices, only roughly half of the energy consumption is associated with the data plane [2]. An idle base system typically consumes more than half of the power over the same system running at full load [3,4]. ...
This paper presents a comprehensive set of design methods for making future Internet networking fully energy-aware and sustainably minimizing and managing the energy footprint. It includes (a) 41 energy-aware design methods, grouped into Service Operations Support, Management Operations Support, Compute Operations Support, Connectivity/Forwarding Operations Support, Traffic Engineering Methods, Architectural Support for Energy Instrumentation, and Network Configuration; (b) energy consumption models and energy metrics are identified and specified. It specifies the requirements for energy-defined network compliance, which include energy-measurable network devices with the support of several control messages: registration, discovery, provisioning, discharge, monitoring, synchronization, flooding, performance, and pushback.
... The IP core routes the traffic to other networks through the Internet Exchange Point (IEP). The embodied energy with networking devices is generally a fraction of their operational energy [30], and their expected lifetime is usually long, lasting years after their deployment until they are obsolesced or break. The footprint associated with the networking infrastructure has grown in the years, however, at a slower rate than other ICT components. ...
... The network itself is composed of an IP core network, transport nodes, and access nodes. The latter accounts for 70% of the energy requirements according to [30]. A more recent work dealing with the 4G Long Term Evolution (LTE) network [32] analyzes the carbon footprint of several districts, dividing it in several components and confirming that the network access requires the most operational energy, together with the end-user devices. ...
The Internet of Sounds (IoS) is an emerging field promoted by a large network of research institutions and companies, which fosters research and new industrial and civil applications in domains such as audio processing, music performance, entertainment and environmental monitoring. Being based on novel technologies and computing paradigms, its environmental costs are yet to be assessed. In previous works, the foundations for an environmental impact assessment in the field were laid down. In this paper, a methodology is built based on an extensive literature survey to identify the foremost emission drivers in the IoS, and apply the collected knowledge to the qualitative analysis of five relevant case studies in the IoS that the authors identify. These are identified from the IoS literature in order to cover two orthogonal axes: artistic-functional and emerging-mature. Their discussion allows a qualitative prediction of their impact, which is positive in two over five cases, negative in the other two and very low in the last one. Considerations, design tips, social suggestions, and future challenges are also outlined.
... Related to that, "green networking" is used by industries and researchers to refer to efforts to achieve energy efficiency and reduce CO 2 footprints of network infrastructures. Derived from the literature [12], [31], [32], reducing network energy consumption for achieving green networking has six strategies: hardware-based improvements, dynamic adaptation, sleep modes, network heterogeneity, energy heterogeneity, and machine learning. Table II shows the strategies and relation with the affected elements in networking, which are described as energy consumption contributors in subsection II-A. ...
... With multiple modes (e.g., active, sleep, idle) network devices can consume less energy. It cannot be realized without hardware support for compute, memory, and network components, i.e., hardware-based improvements from the manufacturers or involving external small devices that take over the connection to the network for the main device (proxy) [12]. Components that can be set to sleep modes are device, line cards, and ports in wired network devices. ...
With the dynamic demands and stringent requirements of various applications, networks need to be high-performance, scalable, and adaptive to changes. Researchers and industries view network softwarization as the best enabler for the evolution of networking to tackle current and prospective challenges. Network softwarization must provide programmability and flexibility to network infrastructures and allow agile management, along with higher control for operators. While satisfying the demands and requirements of network services, energy cannot be overlooked, considering the effects on the sustainability of the environment and business. This paper discusses energy efficiency in modern and future networks with three network softwarization technologies: SDN, NFV, and NS, introduced in an energy-oriented context. With that framework in mind, we review the literature based on network scenarios, control/MANO layers, and energy-efficiency strategies. Following that, we compare the references regarding approach, evaluation method, criterion, and metric attributes to demonstrate the state-of-the-art. Last, we analyze the classified literature, summarize lessons learned, and present ten essential concerns to open discussions about future research opportunities on energy-efficient softwarized networks.
... This requires a strict and standardized combination of environmental policy tools to be formulated by government departments in the process of industrial development at all levels, fully utilizing various digital technologies, promoting the upgrading of regulatory instruments and improving regulatory effectiveness [11]; forming "industry barriers" to existing or upcoming energy-consuming industries; and changing the production method that uses capital, labor and land as traditional industrial factors [12]. In addition, the implementation of strict environmental policies by the government can increase the production costs of enterprises, but when environmental regulations are properly implemented, they can stimulate enterprises to clarify the direction of technological change and thus generate "innovation compensation" to compensate for the short-term increase in production costs, thus achieving the joint improvement of environmental protection, innovation level and economic development [13,14]. Ultimately, a series of environmental regulations will force enterprises to integrate digital resources; reduce the proportion of polluting output; form "digital content, digital intelligence, and digital industry" as the main production factors; and improve the total factor productivity of industry, which will become an important initiative for the development of the digital economy [15]. ...
The digital economy and environmental regulation are important drivers of sustainable development, and exploring the coupling of the three is important for promoting the coordinated development of regional economy, society and environment. However, integrating the three into the same system and evaluating their coupling and coordination has been little studied in academia. This research employs the entropy method with objective weighting to measure the levels of digital economy, environmental regulation and sustainable development in 30 provinces (autonomous regions and municipalities directly under the central government) in China from 2011 to 2020, invokes the concept of coupling in physics, constructs a coupling coordination degree model and identifies the spatial and temporal divergence characteristics of the coupled and coordinated development of the three subsystems. The results of the study demonstrate that: (1) the levels of digital economy, environmental regulation and sustainable development reveal a fluctuating trend of growth, with environmental regulation having the highest overall level; (2) there are spatial and temporal differences in the degree of coupling and coordination of the three subsystems, with a national coupling and coordination degree at the temporal level lying between moderate and good coordination, and showing a “W”-shaped upward trend in general and a “chain” at the spatial level; (3) There is a significant spatial autocorrelation in the degree of coupling coordination, with a localized “high–high” and “high–high” pattern. Based on the above results, the article concludes with suggestions to enhance the development level of each subsystem, providing thoughts for the improvement of the coupling and coordination degree of the three in the later stage.
... Theoretically, due to the progress of information technology, e-commerce accelerates the flow of information, benefiting enterprises in technological innovation, leading to increased production efficiency and reduced energy waste [19,20]. Additionally, e-Energies 2023, 16, 4718 3 of 22 ...
... The rapid progress of the internet presents opportunities for e-commerce to flourish. The increased level of internet development not only improves technological innovation and energy efficiency but also promotes definite improvements in productivity across industries [19]. The increased level of internet development further enhances the role of technological innovation in saving energy. ...
This study provides a viable path to save energy by means of e-commerce development. Taking the national e-commerce demonstration cities (NEDC) pilots policy implemented in China as a quasi-natural experiment, based on the city panel data from 2006 to 2019, this study applies the multi-period difference-in-difference (DID) method to evaluate the effect of NEDC on energy saving in pilot cities. The empirical results suggest that the NEDC policy obviously contributes to energy conservation. The treated cities reduced energy consumption by 14.2% as a result of the implementation of NEDC, relative to the untreated cities. The conclusions remain valid after conducting robustness tests such as placebo test, instrumental variables regression, propensity score matching-difference-in-difference (PSM-DID), and synthetic difference-in-difference (SDID). The NEDC achieves energy-saving effects through technological innovation, industrial restructuring, and economic agglomeration. Furthermore, the heterogeneity analysis indicates that, in cities with high levels of human capital, well-developed information infrastructure, non-resource-based cities, and favorable business environments, the impact of NEDC on energy saving is more significant. Analysis of spatial effects shows that the implementation of NEDC has negative externalities, increasing energy consumption in the surrounding area. In the context of the digital economy, this paper presents new insights on the relationship between e-commerce and energy consumption and provides policy direction for countries looking for energy-saving solutions.
... Recently, many research efforts have been devoted to greening the internet to reduce its carbon footprint and impact on the environment [2,3]. In [1], a MILP optimization model and energy efficient heuristics were developed to reduce power consumption for the IP over WDM networks. ...
As the Internet grows in capacity, the energy consumption of Information and Communication Technologies (ICT) are significantly increasing. Significant research efforts on energy conservation have been devoted to devise different technological solutions to address raised concerns surrounding the power consumption of networking equipment and its impact firstly on the emission of greenhouse gases and secondly on electricity bills. In this work, we investigate energy-efficient physical topologies for NSF IP over wavelength-division multiplexing (WDM) network for the purpose of minimizing energy consumption by redesigning its current physical connectivity. We implement different network topologies, such as implementing the small-world, scale-free (SFN), and random networks on the NSF network, then evaluate and compare its physical properties and network power consumption with the current NSF topology design using a mixed-integer linear programming model, all with the aim of minimizing the network total power consumption. The evaluation shall optimize and minimize the embodied energy consumption of network equipment in the IP and optical layers. Results have demonstrated that the implementation of the proposed energy-minimized topology designs can significantly improve the node’s clustering coefficient, reduce network’s diameter, and reduce energy consumption of the NSF IP over WDM network to 28% if compared with the current design implementation.
... Being familiar, and with the continuously growing trends, the consumption of energy may be well evaluated implementing the virtual machine techniques. Bolla et al. (2011) in their work focused on implementation of fifth generation (5G) wireless cellular network technology, so as to support the drastic demands of user subscriptions and data bandwidths. It has also been focused towards major challenges related to green communication technologies. ...
The term internet of things (IoT) in general connects various types of things/objects to the internet with the help of various information perception devices towards exchanging information. In this case, data can be considered as one of the most valuable aspects of internet of things. Accordingly, the data linked to internet of things have specific characteristics towards modernising and improving the technologies associated with relational-based database management. As, there is huge increase of devices, the amount of data generated are also be too large, the main intention is to organise the large amount of data to build a new future of computing into a globally connected network. It is obvious to face the challenges through better sensing and monitoring of production through internet of things understanding the specific farming conditions. This paper aims at providing and implementing adaptive, efficient remote and logistic operations by actuators to realise dynamic semantic integration.
