A Flexible Machine Learning-Aware Architecture for Future WLANs

Authors: Francesc Wilhelmi, Sergio Barrachina-Muñoz, Boris Bellalta, Cristina Cano, Anders Jonsson & Vishnu Ram.

Abstract: Lots of hopes have been placed in Machine Learning (ML) as a key enabler of future wireless networks. By taking advantage of the large volumes of data generated by networks, ML is expected to deal with the ever-increasing complexity of networking problems. Unfortunately, current networking systems are not yet prepared for supporting the ensuing requirements of ML-based applications, especially for enabling procedures related to data collection, processing, and output distribution. This article points out the architectural requirements that are needed to pervasively include ML as part of future wireless networks operation. To this aim, we propose to adopt the International Telecommunications Union (ITU) unified architecture for 5G and beyond. Specifically, we look into Wireless Local Area Networks (WLANs), which, due to their nature, can be found in multiple forms, ranging from cloud-based to edge-computing-like deployments. Based on ITU's architecture, we provide insights on the main requirements and the major challenges of introducing ML to the multiple modalities of WLANs.

Dataset description: This is the dataset generated for training a Neural Network (NN) in the Access Point (AP) (re)association problem in IEEE 802.11 Wireless Local Area Networks (WLANs).

In particular, the NN is meant to output a prediction function of the throughput that a given station (STA) can obtain from a given Access Point (AP) after association. The features included in the dataset are:

Identifier of the AP to which the STA has been associated.

RSSI obtained from the AP to which the STA has been associated.

Data rate in bits per second (bps) that the STA is allowed to use for the selected AP.

Load in packets per second (pkt/s) that the STA generates.

Percentage of data that the AP is able to serve before the user association is done.

Amount of traffic load in pkt/s handled by the AP before the user association is done.

Airtime in % that the AP enjoys before the user association is done.

Throughput in pkt/s that the STA receives after the user association is done.

The dataset has been generated through random simulations, based on the model provided in https://github.com/toniadame/WiFi_AP_Selection_Framework. More details regarding the dataset generation have been provided in https://github.com/fwilhelmi/machine_learning_aware_architecture_wlans.

Ethernet Switch and Routers Sales Market Outlook

As of 2023, the global Ethernet switch and routers sales market size is estimated to be around USD 45 billion, with a projected growth to approximately USD 70 billion by 2032, reflecting a steady compound annual growth rate (CAGR) of 4.8%. The primary growth drivers include the escalating demand for high-speed internet and data-intensive applications, increased adoption of cloud services, and the proliferation of connected devices in the Internet of Things (IoT) ecosystem.

The surge in data traffic, driven by the growing use of smartphones, tablets, and other connected devices, is a significant factor propelling the Ethernet switch and routers market. The exponential growth in data consumption necessitates advanced networking solutions capable of handling large volumes of data with minimal latency. This is particularly critical for applications in data centers, enterprises, and service provider networks, which require robust and scalable infrastructure to maintain efficiency and reliability.

Another crucial growth factor is the widespread adoption of cloud computing services. As organizations continue to migrate their operations to cloud-based platforms, there is an increased need for efficient networking equipment to ensure seamless connectivity and optimal performance. Ethernet switches and routers play a vital role in establishing and maintaining these connections, enabling businesses to leverage the full potential of cloud technologies. Additionally, the ongoing advancements in 5G technology are expected to further drive market growth by providing faster and more reliable mobile network connections.

The rise of smart cities and smart infrastructure initiatives across the globe also contributes to the market’s expansion. Governments and private enterprises are heavily investing in smart technologies to enhance urban living, improve energy efficiency, and streamline public services. Ethernet switches and routers are fundamental components of these smart systems, facilitating real-time data transmission and connectivity between various devices and sensors.

From a regional perspective, North America currently holds the largest market share, driven by the early adoption of advanced technologies and substantial investments in network infrastructure. The Asia Pacific region, however, is expected to witness the highest growth rate due to rapid urbanization, expanding telecommunications networks, and increasing digitalization efforts in emerging economies such as China and India. Europe also presents significant growth opportunities, supported by the region’s robust industrial base and ongoing digital transformation initiatives.

Product Type Analysis

The Ethernet switch and routers market is segmented based on product type, which includes Fixed Managed, Fixed Unmanaged, Modular Switches, Core Routers, Edge Routers, and Others. Each of these product types caters to specific networking needs and offers unique advantages in various applications. Fixed Managed switches provide enhanced control and security features, making them ideal for complex network environments where centralized management is crucial. These switches are extensively used in enterprise networks, data centers, and service provider infrastructure due to their ability to handle large volumes of traffic with high efficiency.

Fixed Unmanaged switches, on the other hand, are designed for simpler network setups where ease of use and cost-effectiveness are primary considerations. These switches are commonly deployed in small to medium-sized enterprises (SMEs) and home networks where advanced network management is not required. Their plug-and-play functionality makes them an attractive option for users with limited technical expertise, ensuring reliable connectivity without the need for extensive configuration.

Modular switches offer a high degree of flexibility and scalability, allowing organizations to customize their network infrastructure according to specific requirements. These switches are equipped with interchangeable modules that can be easily added or replaced, enabling seamless upgrades and expansions. This adaptability makes modular switches an excellent choice for large-scale enterprises and data centers that anticipate growth and evolving network demands.

Core routers and edge routers serve distinct roles within network architectures. Core routers are typically used in the backbone of large networks to manage data traffic between different network segments, ensuri

According to Cognitive Market Research, the global Data Center Networking market size in 2023 was XX Million. The Data Center Networking Industry's compound annual growth rate (CAGR) will be XX% from 2025 to 2033.

The global Data Center Networking market will expand significantly by XX% CAGR between 2025 to 2033.
North America held the major market of more than XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a compound annual growth rate (CAGR) of XX% from 2025 to 2033.
IT & Telecom Sector held the highest Data Center Networking market revenue share in 2025.

Market Dynamics of the Data Center Networking Market

Key Drivers of the Data Center Networking Market

Evolving Cloud Computing Fuels the Demand for the Data Center Networking Market

It is anticipated that the requirement for data centre networking solutions will increase as cloud computing becomes more widely used across a range of businesses. The market is anticipated to increase as a result of the virtualization and advanced operating model trends. Decentralisation and disaggregation of data centre infrastructure are becoming necessary as a result of large organisations spreading their workload across several cloud platforms. In order to streamline cloud computing operations and provide new market prospects, customised networking platforms are required.

For instance, CBRE predicts that the need for data centres will continue to be high due to the rapid development of artificial intelligence and other contemporary technologies like streaming, gaming, and self-driving cars. Operators will be motivated to deliver the capacity necessary to meet the higher power density requirements of high-performance computing, which will drive improvements in data centre design and technology.

https://www.cbre.com/insights/reports/global-data-center-trends-2023

Leveraging Machine Learning Drives the Data Center Networking Market Further

Data centre networking solutions aid in increasing the effectiveness of data centres by making the best use of the resources at hand. As a result, communication service providers have already begun offering sophisticated networking solutions through intelligent networking. These networking solutions have the ability to simplify troubleshooting procedures in the data centre environment, decrease downtime on the network, and expedite network maintenance. Additionally, by enabling data centre operators to take use of cutting-edge technologies like machine learning, these networking solutions will propel the market's growth throughout the projected timeframe.

For instance, artificial intelligence and machine learning (AI/ML) applications are becoming more and more common in data centres, according to market leader Cisco. One of the most popular uses of AI is machine learning, a subset of the field. Machine learning (ML) is the process by which computer systems may learn to infer and make predictions from observations and data.

https://www.cisco.com/c/en/us/td/docs/dcn/whitepapers/cisco-data-center-networking-blueprint-for-ai-ml-applications.html

Key Restraints of the Data Center Networking Market

Latency and Network Complexity Restricts the Data Center Networking Market Growth

Because of the distance that data must travel between sites, latency is a major problem in data centres. In order to minimise latency problems, fibre optic connections and data must move quickly while networking in data centres. Because equipment prioritises packet routing, resulting in data travelling via several connections and increasing delay, network complexity is also crucial, significantly influencing the market's need for networking solutions while waiting for more technological developments.

For instance, traditional data centre networks, as per DgtlInfra, mostly depend on hardware and on-premises servers; this dependence can give rise to issues with latency, storage constraints, and dependability, especially when data volumes keep increasing quickly.

https://dgtlinfra.com/data-center-architecture/

Impact of COVID-19 on the Data Center Networking Market

The market for data centre networking has been greatly disrupted by the COVID-19 outbreak. Worldwide manufacturing and production were forced to stop as a result. This epidemic had a significant negative effect on the world economy as well, which created further c...

The size of the Cloud Network Infrastructure Market was valued at USD 1.34 Billion in 2023 and is projected to reach USD 1.92 Billion by 2032, with an expected CAGR of 5.25% during the forecast period. Observe that the marketplace is undergoing a surge of cloud network infrastructure, as the inclination of businesses toward cloud operations continues to grow. Cloud network infrastructure comprises the virtual hardware and software that support cloud services and applications, some like network components such as servers, storage, routers, switches, and security mechanisms. This is supposed to be configurable, scalable, and optimized for any cloud environment. This is mainly driven by some of these features, namely: an easy-to-effect scaling of cloud applications; the adoption of such by cloud-based applications is rapidly on the rise; it is an easy way to increase network scalability while also improving cost-efficient as well as flexible network management. The main market driver is: both the increase in the acceptance of cloud-based applications driven by analysis and the need for good scaling due to increased performance and superior cost efficiency and technology features in network management related to reliance on real and physical hardware off-premise, with flexibility for scaling as may be required by increased demand. As enterprises move on to hybrid and multi-cloud administration, there is a growing need for sophisticated network management solutions that guarantee uninterrupted operation across different cloud-based networks. Recent developments include: The large share is mainly attributed to the increasing IT capacity requirements and growing adoption of new data center technologies. The cloud network infrastructure market in the United States will develop at an exponential rate, owing to a large number of businesses opting for cloud services to avoid the upfront costs of creating new data centers for business continuity. HP Enterprise has released the Hyper-Converged 380 (HC 380), an all-in-one compute, software-defined storage, and intelligent virtualization appliance for mid-sized and remote office/branch office (ROBO) businesses. The HC 380 is a cost-effective hybrid IT infrastructure solution based on HPE ProLiant DL380 servers. Dell, Inc. (US) and Securonix have teamed up to provide sophisticated security analytics for active directory and enterprise applications. The FlexPod with All Flash FAS (AFF) system, which is a high-speed data storage and data management version of Cisco and NetApp's FlexPod convergent infrastructure (CI) solution, was introduced by Cisco in collaboration with NetApp, Inc. (American computer storage and data management firm).. Key drivers for this market are: Cloud Adoption Scalability and Flexibility Hybrid and Multi-Cloud Adoption. Potential restraints include: Network Security and Data Privacy Concerns Integration Complexity Performance Issues. Notable trends are: Edge Computing Integration Software-Defined Networking (SDN) and Network Function Virtualization (NFV).

On April 13-14, 2020, the Large Scale Networking Interagency Working Group of the Networking and Information Technology Research and Development Program held a workshop to explore new paradigms to address the challenges and requirements of huge data science and engineering research. The workshop brought together domain scientists, network and systems researchers, and infrastructure providers to address the problems associated with processing, storing, and transferring huge data. This document summarizes the workshop discussions.

The global market for jumper wiring in data center networks is experiencing robust growth, driven by the increasing demand for high-speed, reliable data transmission and the proliferation of cloud computing and big data applications. The market size in 2025 is estimated at $826 million. While the provided CAGR is missing, considering the rapid advancements in data center technologies and the consistent need for improved connectivity, a conservative estimate for the CAGR over the forecast period (2025-2033) would be around 7%. This implies significant expansion, potentially reaching over $1.6 billion by 2033. Key drivers include the rising adoption of high-density server deployments, the increasing complexity of data center networks requiring more intricate wiring solutions, and the growing emphasis on minimizing latency and maximizing bandwidth. Furthermore, trends toward software-defined networking (SDN) and network function virtualization (NFV) are indirectly boosting demand, as these technologies often require more sophisticated and flexible wiring architectures. However, the market also faces certain restraints. These include the rising costs of materials and skilled labor, the increasing complexity of cabling management within data centers, and the potential for standardization issues across diverse vendor ecosystems. Nevertheless, the overall market outlook remains positive, with significant opportunities for growth in segments like high-speed interconnects and specialized jumper cables designed for specific data center applications. Major players like 3M, Molex, and others are constantly innovating to meet the evolving needs of data center operators, contributing to the competitive landscape. Segmentation by type (female-to-female, male-to-male, male-to-female) and application (network switches, servers) reflects the varied requirements within data centers and presents opportunities for tailored product development. The regional distribution of the market is expected to be heavily influenced by the geographic concentration of data centers, with North America and Asia-Pacific likely dominating in terms of market share.

Ethernet Optical Transceiver Market Outlook

The Ethernet Optical Transceiver market size was valued at approximately USD 4.2 billion in 2023 and is projected to reach around USD 10.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 10.8% during the forecast period. The growth in this market is primarily driven by the increasing demand for high-speed internet and the proliferation of data centers, which are essential for supporting the ever-growing data traffic and ensuring seamless connectivity across various sectors.

One of the significant growth factors in the Ethernet Optical Transceiver market is the rapid expansion of data centers worldwide. With the surge in cloud computing, big data analytics, and the Internet of Things (IoT), the need for high-speed and reliable data transmission has never been more critical. Data centers are the backbone of the digital economy, and the deployment of advanced optical transceivers is essential for managing massive volumes of data efficiently. Furthermore, the transition towards 5G networks is fueling the demand for high-capacity and low-latency optical transceivers, which are integral to supporting the high-speed data requirements of 5G infrastructure.

Another driving factor is the increasing adoption of Ethernet Optical Transceivers in the telecommunications sector. Telecommunications companies are striving to upgrade their networks to accommodate the growing demand for high-bandwidth applications such as video streaming, online gaming, and virtual reality. Optical transceivers offer the advantage of high data transfer rates, low power consumption, and long-distance communication, making them an ideal choice for modern telecommunications infrastructure. Additionally, the rising trend of network function virtualization (NFV) and software-defined networking (SDN) is further accelerating the adoption of optical transceivers in the telecom industry.

The enterprise sector is also a major contributor to the market growth of Ethernet Optical Transceivers. Enterprises are increasingly relying on high-speed networks to support their business operations, ensure data security, and enhance communication within and outside the organization. The adoption of advanced technologies such as artificial intelligence (AI), machine learning, and edge computing is driving the need for robust and reliable network infrastructure. Optical transceivers play a crucial role in enabling high-speed data transfer and ensuring efficient network performance, thereby supporting the digital transformation initiatives of enterprises across various industries.

Regionally, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. The rapid industrialization, increasing investments in telecommunications infrastructure, and the rising number of data centers in countries such as China, India, and Japan are major factors contributing to market growth in this region. North America and Europe are also significant markets for Ethernet Optical Transceivers, driven by the high adoption of advanced technologies, robust IT infrastructure, and the presence of major market players. The Middle East & Africa and Latin America are anticipated to show moderate growth, supported by increasing investments in telecommunications and data center infrastructure.

Form Factor Analysis

The form factor segment of the Ethernet Optical Transceiver market includes various types such as SFP, SFP+, QSFP, QSFP+, CFP, CFP2, CFP4, and others. The Small Form-factor Pluggable (SFP) transceivers are widely adopted due to their compact size and ability to support a range of data rates from 100 Mbps to 4 Gbps. These transceivers are often used in switches, routers, and other networking equipment, making them a popular choice in enterprise and telecommunication applications. The increasing demand for high-speed connectivity and the need for scalable network solutions are driving the adoption of SFP transceivers in various sectors.

SFP+ transceivers, an enhanced version of SFP, offer higher data rates up to 16 Gbps and are commonly used in data centers and enterprise networks. The ability to support higher bandwidth and longer reach makes SFP+ transceivers suitable for applications requiring high-speed data transfer and reliable performance. As data centers continue to expand and upgrade their infrastructure to handle growing data traffic, the demand for SFP+ transceivers is expected to rise significantly.

The Quad

Layer 2 Managed Switches Market Outlook

In 2023, the global Layer 2 Managed Switches market size was valued at approximately USD 9.5 billion. With a compound annual growth rate (CAGR) of 6.2%, this market is projected to reach around USD 16.0 billion by 2032. Key growth factors driving this market include the increasing demand for high-speed internet, the proliferation of smart devices, and the growing need for reliable and efficient network management solutions.

The surge in internet usage and the widespread adoption of IoT devices have significantly contributed to the growth of the Layer 2 Managed Switches market. As more devices become interconnected, the need for stable and high-speed network infrastructure becomes paramount. These switches play a crucial role in ensuring network stability and performance, which is essential for both residential and commercial users. Additionally, the growth of cloud computing and data centers has further fueled the demand for advanced networking solutions, making Layer 2 Managed Switches indispensable in modern network architectures.

Another significant growth factor is the increasing emphasis on network security and management. With cyber threats becoming more sophisticated, organizations are prioritizing robust network management solutions that can offer enhanced security features. Layer 2 Managed Switches provide advanced functionalities such as VLANs, QoS, and SNMP, which are crucial for maintaining network security and efficiency. The ability to segment networks and manage traffic effectively helps in minimizing risks and ensuring smooth network operations, thereby driving the market growth.

Moreover, the digital transformation across various industries is propelling the demand for Layer 2 Managed Switches. Sectors such as healthcare, BFSI, and manufacturing are increasingly adopting advanced network solutions to support their digital initiatives. The need for reliable and high-performance networks to handle large volumes of data and ensure seamless connectivity is pushing organizations to invest in Layer 2 Managed Switches. This trend is expected to continue as more industries embrace digital technologies to enhance their operations and service delivery.

Regionally, the Asia Pacific market is anticipated to witness substantial growth, driven by the rapid urbanization, expanding IT infrastructure, and increasing investments in smart city projects. Countries like China, India, and Japan are leading this growth due to their significant advancements in technology and infrastructure development. Additionally, favorable government policies and initiatives to promote digitalization are further boosting the market in this region.

Product Type Analysis

The Layer 2 Managed Switches market can be segmented based on product type into Gigabit Ethernet, Fast Ethernet, and 10 Gigabit Ethernet switches. Gigabit Ethernet switches are currently the most widely adopted due to their ability to provide high-speed data transfer rates up to 1 Gbps. These switches are exceptionally suitable for small to medium-sized enterprises (SMEs) that require efficient network solutions without compromising on speed. The growing demand for faster internet connectivity and higher data throughput has significantly increased the adoption of Gigabit Ethernet switches, making them a dominant segment in this market.

Fast Ethernet switches, offering data transfer rates of 100 Mbps, are also a crucial part of the market, particularly in cost-sensitive environments. These switches are often utilized in applications where network traffic is relatively low, such as in certain residential and small office settings. While they may not offer the same speed as their Gigabit counterparts, their affordability and sufficient performance for basic network requirements make them a viable option for specific use cases.

On the other hand, 10 Gigabit Ethernet switches are gaining traction in environments where extremely high data transfer rates are necessary, such as data centers and enterprise networks. These switches provide speeds of up to 10 Gbps, making them ideal for handling large volumes of data and supporting high-bandwidth applications. As businesses continue to expand their digital infrastructure and the volume of data traffic increases, the demand for 10 Gigabit Ethernet switches is expected to grow, contributing significantly to the market's overall expansion.

Furthermore, advancements in switch technology, such as the integration of Power over Ethernet (PoE) features in Gigabi

The USDA Agricultural Research Service (ARS) recently established SCINet , which consists of a shared high performance computing resource, Ceres, and the dedicated high-speed Internet2 network used to access Ceres. Current and potential SCINet users are using and generating very large datasets so SCINet needs to be provisioned with adequate data storage for their active computing. It is not designed to hold data beyond active research phases. At the same time, the National Agricultural Library has been developing the Ag Data Commons, a research data catalog and repository designed for public data release and professional data curation. Ag Data Commons needs to anticipate the size and nature of data it will be tasked with handling. The ARS Web-enabled Databases Working Group, organized under the SCINet initiative, conducted a study to establish baseline data storage needs and practices, and to make projections that could inform future infrastructure design, purchases, and policies. The SCINet Web-enabled Databases Working Group helped develop the survey which is the basis for an internal report. While the report was for internal use, the survey and resulting data may be generally useful and are being released publicly. From October 24 to November 8, 2016 we administered a 17-question survey (Appendix A) by emailing a Survey Monkey link to all ARS Research Leaders, intending to cover data storage needs of all 1,675 SY (Category 1 and Category 4) scientists. We designed the survey to accommodate either individual researcher responses or group responses. Research Leaders could decide, based on their unit's practices or their management preferences, whether to delegate response to a data management expert in their unit, to all members of their unit, or to themselves collate responses from their unit before reporting in the survey. Larger storage ranges cover vastly different amounts of data so the implications here could be significant depending on whether the true amount is at the lower or higher end of the range. Therefore, we requested more detail from "Big Data users," those 47 respondents who indicated they had more than 10 to 100 TB or over 100 TB total current data (Q5). All other respondents are called "Small Data users." Because not all of these follow-up requests were successful, we used actual follow-up responses to estimate likely responses for those who did not respond. We defined active data as data that would be used within the next six months. All other data would be considered inactive, or archival. To calculate per person storage needs we used the high end of the reported range divided by 1 for an individual response, or by G, the number of individuals in a group response. For Big Data users we used the actual reported values or estimated likely values. Resources in this dataset:Resource Title: Appendix A: ARS data storage survey questions. File Name: Appendix A.pdfResource Description: The full list of questions asked with the possible responses. The survey was not administered using this PDF but the PDF was generated directly from the administered survey using the Print option under Design Survey. Asterisked questions were required. A list of Research Units and their associated codes was provided in a drop down not shown here. Resource Software Recommended: Adobe Acrobat,url: https://get.adobe.com/reader/ Resource Title: CSV of Responses from ARS Researcher Data Storage Survey. File Name: Machine-readable survey response data.csvResource Description: CSV file includes raw responses from the administered survey, as downloaded unfiltered from Survey Monkey, including incomplete responses. Also includes additional classification and calculations to support analysis. Individual email addresses and IP addresses have been removed. This information is that same data as in the Excel spreadsheet (also provided).Resource Title: Responses from ARS Researcher Data Storage Survey. File Name: Data Storage Survey Data for public release.xlsxResource Description: MS Excel worksheet that Includes raw responses from the administered survey, as downloaded unfiltered from Survey Monkey, including incomplete responses. Also includes additional classification and calculations to support analysis. Individual email addresses and IP addresses have been removed.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel

The Dense Wavelength Division Multiplexing (DWDM) equipment market is experiencing robust growth, driven by the increasing demand for high-bandwidth, long-haul communication networks. The market is projected to reach a significant size, estimated at $5 billion in 2025, demonstrating a Compound Annual Growth Rate (CAGR) of approximately 12% from 2019 to 2033. This expansion is fueled by several key factors. The proliferation of cloud computing and data centers necessitates high-capacity transmission solutions, driving demand for DWDM equipment. Furthermore, the growth of 5G networks, with their significantly higher bandwidth requirements compared to previous generations, is a major catalyst. The increasing adoption of fiber optic cables, providing the underlying infrastructure for DWDM systems, is another contributing factor. Finally, the ongoing deployment of next-generation network technologies like SDN (Software-Defined Networking) and NFV (Network Function Virtualization) is enhancing the efficiency and scalability of DWDM systems, further driving market growth. Segment-wise, the Network Design & Optimization segment holds a significant share, followed by Network Maintenance & Support. In terms of application, Communication Service Providers and Network Operators dominate the market, followed by the Enterprise and Government sectors. While geographic expansion is widespread, North America and Asia Pacific currently represent the largest market segments, driven by high levels of technological adoption and significant investments in infrastructure development. However, emerging economies in regions such as the Middle East & Africa and South America are demonstrating substantial growth potential, presenting significant opportunities for market players. Restraints to market growth include the high initial investment costs associated with DWDM equipment implementation, as well as the need for specialized technical expertise for installation and maintenance. This report provides a detailed analysis of the global Dense Wavelength Division Multiplexing (DWDM) equipment market, projecting significant growth driven by the increasing demand for high-bandwidth, long-haul optical communication networks. We delve into market concentration, key trends, dominant regions and segments, product insights, and future growth catalysts. The report leverages extensive market research and industry expertise to provide actionable intelligence for stakeholders across the communication service provider, enterprise, and government sectors.

Snapshot img

Wireless Access Point Market Size 2025-2029

The wireless access point market size is forecast to increase by USD 8.14 billion at a CAGR of 6% between 2024 and 2029.

The market is experiencing significant growth due to several key trends. The increase in the development of smart cities is driving market growth as these cities require advanced wireless connectivity solutions to support various IoT devices and applications. The demand for wireless network connectivity is driving innovation, with the emergence of 5G technology and Wi-Fi 6 and Wi-Fi 6e standards. Furthermore, the rise in 5G investments is expected to revolutionize the market by offering faster data transfer rates and lower latency. 
However, the market faces challenges such as the limitation of WLAN to cyber attacks, which can compromise network security and data privacy. To mitigate these risks, market participants are focusing on developing advanced security features and solutions to ensure secure wireless connectivity. Overall, the market is poised for strong growth in the coming years, driven by these trends and the increasing demand for reliable and secure wireless connectivity.

What will be the Wireless Access Point Market Size During the Forecast Period?

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The market is experiencing significant growth as the number of connected devices continues to proliferate in offices, homes, and public places. With the increasing reliance on wireless networking for internet access, businesses and consumers alike are seeking solutions that offer superior technical expertise and extended range. Transceivers and routers play a crucial role in providing wireless connectivity, enabling seamless communication between various gadgets and IoT devices. Wi-fi technology has become an essential component of digital initiatives in residences, public areas, educational institutions, and various industries. These advanced technologies offer improved speed, reliability, and security, addressing the growing needs of consumers and businesses.
However, with the increasing adoption of wireless networking, security threats have become a major concern. Ensuring the security of wireless networks is crucial to prevent unauthorized access and data breaches. Technical expertise and strong security measures are essential to mitigate these risks and maintain the integrity of wireless networks. Range extenders, Power over Ethernet Plus (PoE+), and other wireless networking solutions are also gaining popularity as they help to expand the reach of wireless networks and provide more reliable connectivity in larger spaces. The integration of wireless networking into various digital solutions is transforming industries, from healthcare and education to smart homes and IoT applications. With the advancement of Wi-Fi 6, Wi-Fi 6e, and 5G technologies, businesses and consumers can expect faster, more reliable, and more secure wireless networking solutions.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Enterprises
  Consumers


Product

  Gateways or routers
  Dependent AP
  Independent AP


Type

  Indoor
  Outdoor


Geography

  North America

    Canada
    US


  APAC

    China
    India
    Japan


  Europe

    Germany
    UK
    France
    Italy


  South America

    Brazil


  Middle East and Africa

By End-user Insights

The enterprises segment is estimated to witness significant growth during the forecast period.

The enterprise segment dominates the market, accounting for a significant share in 2024. The increasing adoption of cloud services such as Microsoft Office 365, Google apps, and SAP by large enterprises and IT professionals has led to increased bandwidth demand and network requirements. According to predictions, there will be a substantial increase in bandwidth demand due to the growing preference for cloud services during the forecast period.

Additionally, this trend is expected to boost the deployment of 802.11ac and 802.11ax WLAN devices. Wi-Fi 6 (802.11ax) and Wi-Fi 6E are the latest Wi-Fi technologies that offer higher data rates, increased capacity, and improved performance. These advancements are anticipated to further fuel the growth of the market. Wi-Fi technology continues to be the preferred choice for wireless connectivity, with wireless hotspots and wireless infrastructure becoming increasingly essential for businesses and consumers alike.

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The enterprises segment was valued at USD 9.8 billion in 2019 and showed a gradual increase during the fo

Big Data and Society - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

As of March 2024, there were a reported 5,381 data centers in the United States, the most of any country worldwide. A further 521 were located in Germany, while 514 were located in the United Kingdom. What is a data center? A data center is a network of computing and storage resources that enables the delivery of shared software applications and data. These centers can house large amounts of critical and important data, and therefore are vital to the daily functions of companies and consumers alike. As a result, whether it is a cloud, colocation, or managed service, data center real estate will have increasing importance worldwide. Hyperscale data centers In the past, data centers were highly controlled physical infrastructures, but the cloud has since changed that model. A cloud data service is a remote version of a data center – located somewhere away from a company's physical premises. Cloud IT infrastructure spending has grown and is forecast to rise further in the coming years. The evolution of technology, along with the rapid growth in demand for data across the globe, is largely driven by the leading hyperscale data center providers.

In this work we are concerned with the conceptual design of large-scale diagnostic and health management systems that use Bayesian networks. While they are potentially powerful, improperly designed Bayesian networks can result in too high memory requirements or too long inference times, to they point where they may not be acceptable for real-time diagnosis and health management in resource-bounded systems such as NASA's aerospace vehicles. We investigate the clique tree clustering approach to Bayesian network inference, where increasing the size and connectivity of a Bayesian network typically also increases clique tree size. This paper combines techniques for analytically characterizing clique tree growth with bounds on clique tree size imposed by resource constraints, thereby aiding the design and optimization of large-scale Bayesian networks in resource-bounded systems. We provide both theoretical and experimental results, and illustrate our approach using a NASA case study. Reference: O. J. Mengshoel, “Designing Resource-Bounded Reasoners using Bayesian Networks: System Health Monitoring and Diagnosis”, In Proc. of the 18th International Workshop on Principles of Diagnosis (DX-07), Nashville, TN, May 2007. BibTex Reference: @inproceedings{mengshoel07designing, author = "Mengshoel, O. J.", title = "Designing Resource-Bounded Reasoners using {Bayesian} Networks: System Health Monitoring and Diagnosis", booktitle = {Proceedings of the 18th International Workshop on Principles of Diagnosis (DX-07)}, year = {2007}, pages = {330--337}, address = {Nashville, TN}, }

CompanyKG is a heterogeneous graph consisting of 1,169,931 nodes and 50,815,503 undirected edges, with each node representing a real-world company and each edge signifying a relationship between the connected pair of companies.

Edges: We model 15 different inter-company relations as undirected edges, each of which corresponds to a unique edge type. These edge types capture various forms of similarity between connected company pairs. Associated with each edge of a certain type, we calculate a real-numbered weight as an approximation of the similarity level of that type. It is important to note that the constructed edges do not represent an exhaustive list of all possible edges due to incomplete information. Consequently, this leads to a sparse and occasionally skewed distribution of edges for individual relation/edge types. Such characteristics pose additional challenges for downstream learning tasks. Please refer to our paper for a detailed definition of edge types and weight calculations.

Nodes: The graph includes all companies connected by edges defined previously. Each node represents a company and is associated with a descriptive text, such as "Klarna is a fintech company that provides support for direct and post-purchase payments ...". To comply with privacy and confidentiality requirements, we encoded the text into numerical embeddings using four different pre-trained text embedding models: mSBERT (multilingual Sentence BERT), ADA2, SimCSE (fine-tuned on the raw company descriptions) and PAUSE.

Evaluation Tasks. The primary goal of CompanyKG is to develop algorithms and models for quantifying the similarity between pairs of companies. In order to evaluate the effectiveness of these methods, we have carefully curated three evaluation tasks:

Similarity Prediction (SP). To assess the accuracy of pairwise company similarity, we constructed the SP evaluation set comprising 3,219 pairs of companies that are labeled either as positive (similar, denoted by "1") or negative (dissimilar, denoted by "0"). Of these pairs, 1,522 are positive and 1,697 are negative.

Competitor Retrieval (CR). Each sample contains one target company and one of its direct competitors. It contains 76 distinct target companies, each of which has 5.3 competitors annotated in average. For a given target company A with N direct competitors in this CR evaluation set, we expect a competent method to retrieve all N competitors when searching for similar companies to A.

Similarity Ranking (SR) is designed to assess the ability of any method to rank candidate companies (numbered 0 and 1) based on their similarity to a query company. Paid human annotators, with backgrounds in engineering, science, and investment, were tasked with determining which candidate company is more similar to the query company. It resulted in an evaluation set comprising 1,856 rigorously labeled ranking questions. We retained 20% (368 samples) of this set as a validation set for model development.

Edge Prediction (EP) evaluates a model's ability to predict future or missing relationships between companies, providing forward-looking insights for investment professionals. The EP dataset, derived (and sampled) from new edges collected between April 6, 2023, and May 25, 2024, includes 40,000 samples, with edges not present in the pre-existing CompanyKG (a snapshot up until April 5, 2023).

Background and Motivation

In the investment industry, it is often essential to identify similar companies for a variety of purposes, such as market/competitor mapping and Mergers & Acquisitions (M&A). Identifying comparable companies is a critical task, as it can inform investment decisions, help identify potential synergies, and reveal areas for growth and improvement. The accurate quantification of inter-company similarity, also referred to as company similarity quantification, is the cornerstone to successfully executing such tasks. However, company similarity quantification is often a challenging and time-consuming process, given the vast amount of data available on each company, and the complex and diversified relationships among them.

While there is no universally agreed definition of company similarity, researchers and practitioners in PE industry have adopted various criteria to measure similarity, typically reflecting the companies' operations and relationships. These criteria can embody one or more dimensions such as industry sectors, employee profiles, keywords/tags, customers' review, financial performance, co-appearance in news, and so on. Investment professionals usually begin with a limited number of companies of interest (a.k.a. seed companies) and require an algorithmic approach to expand their search to a larger list of companies for potential investment.

In recent years, transformer-based Language Models (LMs) have become the preferred method for encoding textual company descriptions into vector-space embeddings. Then companies that are similar to the seed companies can be searched in the embedding space using distance metrics like cosine similarity. The rapid advancements in Large LMs (LLMs), such as GPT-3/4 and LLaMA, have significantly enhanced the performance of general-purpose conversational models. These models, such as ChatGPT, can be employed to answer questions related to similar company discovery and quantification in a Q&A format.

However, graph is still the most natural choice for representing and learning diverse company relations due to its ability to model complex relationships between a large number of entities. By representing companies as nodes and their relationships as edges, we can form a Knowledge Graph (KG). Utilizing this KG allows us to efficiently capture and analyze the network structure of the business landscape. Moreover, KG-based approaches allow us to leverage powerful tools from network science, graph theory, and graph-based machine learning, such as Graph Neural Networks (GNNs), to extract insights and patterns to facilitate similar company analysis. While there are various company datasets (mostly commercial/proprietary and non-relational) and graph datasets available (mostly for single link/node/graph-level predictions), there is a scarcity of datasets and benchmarks that combine both to create a large-scale KG dataset expressing rich pairwise company relations.

Source Code and Tutorial:https://github.com/llcresearch/CompanyKG2

Paper: to be published

The Network Access Control (NAC) market is experiencing robust growth, driven by the increasing adoption of cloud-based solutions and the rising need for enhanced cybersecurity in both large enterprises and SMEs. The market's expansion is fueled by the escalating threat landscape, necessitating robust security measures to control access to sensitive data and network resources. The shift towards remote work models has further accelerated the demand for effective NAC solutions, as organizations seek to secure their networks against unauthorized access from various locations. While the initial investment in NAC can be significant, the long-term benefits of reduced security breaches, improved compliance, and enhanced operational efficiency outweigh the costs. We estimate the 2025 market size to be approximately $2.5 billion, based on typical growth rates observed in the cybersecurity sector and considering the accelerating adoption of cloud-based and web-based NAC solutions. This represents a substantial increase from previous years, and we project a compound annual growth rate (CAGR) of 15% throughout the forecast period (2025-2033). The market segmentation reveals strong growth potential in both cloud-based and web-based NAC solutions, with cloud-based solutions gaining traction due to their scalability and flexibility. Large enterprises are leading the adoption, driven by their complex network infrastructure and stringent security requirements. However, the SME segment is also showing significant growth potential as awareness of cybersecurity threats increases and budget constraints lessen. Key players in the market, including Aruba, Cisco, Pulse Secure, and others, are constantly innovating and expanding their product offerings to meet the evolving needs of their customers. Factors such as increasing data breaches and stringent regulatory compliance requirements are acting as major growth stimulants. However, the market faces certain restraints, including the complexity of implementation for some NAC solutions and the potential for integration challenges with existing IT infrastructure. Despite these challenges, the long-term outlook for the NAC market remains positive, driven by continued innovation and the increasing importance of network security.

The size of the Data Center Switch Market was valued at USD XXX XXX in 2023 and is projected to reach USD 0.00 XXX by 2032, with an expected CAGR of 5.80% during the forecast period. The market for a data center switch is growing due to the acceptance of cloud computing, artificial intelligence, and big data analytics. Data center switches are an essential component of a network that route data traffic properly with high speeds and minimal latencies in enterprises and hyperscale data centers. The switches enable multiple architectures in spine-leaf and multi-tier networking to allow greater scalability and performance. The major growth drivers for the market include high-bandwidth applications, the shift towards SDN, and hyperscale data center growth. There's now growing demand for 400G and beyond toward increasing data traffic, 5G, edge computing, and Internet of Things. Great leaders in technology are upscaling and inculcating efficiency in switching, security, and especially automation in meeting the evolving industry's demands. Despite good growth prospects, the market has high infrastructure costs, power consumption issues, and complex network management. Cybersecurity risks and evolving data privacy regulations demand strong security measures to ensure safe and reliable data transmission. Emerging trends will include the adoption of AI-driven network optimization, energy-efficient switch designs, and open networking solutions for interoperability flexibility. It is expected to be a key enabler of the burgeoning demand for digital transformation in the coming years by the organizations. Recent developments include: September 2021 The QFX5700 Series Switch, a new Juniper Networks device, was launched. It is a versatile midsize platform that supports a variety of use cases by allowing the combination of line cards with a selection of interface options from 10G to 400G.. Notable trends are: Rising demand for simplified data center management and automation system is driving the market growth.

The global market for Packet Optical Networking Equipment (PONE) is experiencing robust growth, driven by the increasing demand for high-bandwidth, low-latency network connectivity across various sectors. The surge in data consumption fueled by cloud computing, 5G deployments, and the proliferation of connected devices is a primary catalyst. Furthermore, the ongoing digital transformation initiatives across industries like media and entertainment, IT and telecoms, and data centers are significantly contributing to market expansion. The market is segmented by power supply capacity (1-10W, 11-20W, 21-50W, 50-100W), reflecting the diverse power requirements of different network devices. Key players like Cisco, Huawei, and Ciena are at the forefront of innovation, constantly developing advanced PON solutions to cater to evolving network demands. Geographic growth is particularly strong in the Asia-Pacific region, driven by significant investments in infrastructure development and the expanding digital economies of countries like China and India. While challenges like the high initial investment costs associated with PON deployment and the potential for supply chain disruptions exist, the long-term growth prospects for the PONE market remain highly promising. Growth in the PONE market is expected to continue, fueled by the ongoing expansion of 5G networks, the rise of cloud-based services, and the growing need for high-capacity data transmission. The increasing adoption of software-defined networking (SDN) and network function virtualization (NFV) is also expected to drive demand for flexible and scalable PON solutions. Competitive pressures among major vendors are leading to continuous innovation in terms of cost-effectiveness, efficiency, and performance. The market is likely to witness a shift towards more energy-efficient and environmentally friendly PON technologies in line with global sustainability goals. Regional variations in market growth are expected to persist, with developed economies showing a steady growth rate and emerging markets experiencing more dynamic expansion. The overall outlook for the PONE market suggests sustained and substantial growth throughout the forecast period, driven by technological advancements and the ever-increasing global demand for high-speed connectivity.

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Cloud Analytics Market Size 2024-2028

The cloud analytics market size is forecast to increase by USD 74.08 billion at a CAGR of 24.4% between 2023 and 2028.

The market is experiencing significant growth due to several key trends. The adoption of hybrid and multi-cloud setups is on the rise, as these configurations enhance data connectivity and flexibility. Another trend driving market growth is the increasing use of cloud security applications to safeguard sensitive data.
However, concerns regarding confidential data security and privacy remain a challenge for market growth. Organizations must ensure robust security measures are in place to mitigate risks and maintain trust with their customers. Overall, the market is poised for continued expansion as businesses seek to leverage the benefits of cloud technologies for data processing and data analytics.

What will be the Size of the Cloud Analytics Market During the Forecast Period?

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The market is experiencing significant growth due to the increasing volume of data generated by businesses and the demand for advanced analytics solutions. Cloud-based analytics enables organizations to process and analyze large datasets from various data sources, including unstructured data, in real-time. This is crucial for businesses looking to make data-driven decisions and gain valuable insights to optimize their operations and meet customer requirements. Key industries such as sales and marketing, customer service, and finance are adopting cloud analytics to improve key performance indicators and gain a competitive edge. Both Small and Medium-sized Enterprises (SMEs) and large enterprises are embracing cloud analytics, with solutions available on private, public, and multi-cloud platforms.
Big data technology, such as machine learning and artificial intelligence, are integral to cloud analytics, enabling advanced data analytics and business intelligence. Cloud analytics provides businesses with the flexibility to store and process data In the cloud, reducing the need for expensive on-premises data storage and computation. Hybrid environments are also gaining popularity, allowing businesses to leverage the benefits of both private and public clouds. Overall, the market is poised for continued growth as businesses increasingly rely on data-driven insights to inform their decision-making processes.

How is this Cloud Analytics Industry segmented and which is the largest segment?

The cloud analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2017-2022 for the following segments.

Solution

  Hosted data warehouse solutions
  Cloud BI tools
  Complex event processing
  Others


Deployment

  Public cloud
  Hybrid cloud
  Private cloud


Geography

  North America

    US


  Europe

    Germany
    UK


  APAC

    China
    Japan


  Middle East and Africa



  South America

By Solution Insights

The hosted data warehouse solutions segment is estimated to witness significant growth during the forecast period.

Hosted data warehouses enable organizations to centralize and analyze large datasets from multiple sources, facilitating advanced analytics solutions and real-time insights. By utilizing cloud-based infrastructure, businesses can reduce operational costs through eliminating licensing expenses, hardware investments, and maintenance fees. Additionally, cloud solutions offer network security measures, such as Software Defined Networking and Network integration, ensuring data protection. Cloud analytics caters to diverse industries, including SMEs and large enterprises, addressing requirements for sales and marketing, customer service, and key performance indicators. Advanced analytics capabilities, including predictive analytics, automated decision making, and fraud prevention, are essential for data-driven decision making and business optimization.

Furthermore, cloud platforms provide access to specialized talent, big data technology, and AI, enhancing customer experiences and digital business opportunities. Data connectivity and data processing in real-time are crucial for network agility and application performance. Hosted data warehouses offer computational power and storage capabilities, ensuring efficient data utilization and enterprise information management. Cloud service providers offer various cloud environments, including private, public, multi-cloud, and hybrid, catering to diverse business needs. Compliance and security concerns are addressed through cybersecurity frameworks and data security measures, ensuring data breaches and thefts are minimized.

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The Hosted data warehouse soluti