Migrating Fixed Access to 5G Core

Unified Communications, Network Security

Article | July 10, 2023

When you're immersed in ultra-fast 5G amazing services, 600 million people around the world are still blocked from accessing mobile networks. When you experience seamless online shopping and online education, 3.4 billion people worldwide have not experienced mobile Internet services. On the road where connections are not connected, no one will be left behind. We can feel the life changes by RuralStar deployment.

5G

Article | September 28, 2023

Uncover the future of network monitoring at computer networking conferences. Explore insights, collaborations, and growth opportunities to harness the power of secured network infrastructures. Network monitoring is a critical aspect of the ever-evolving networking industry; helping ensure efficient and secure operation. It involves the continuous surveillance, analysis, and management of network infrastructure, performance, and security. To stay abreast of the latest developments and advancements in this field, industry executives and managers must attend the upcoming network monitoring conferences scheduled between June and September 2023. The events provide a crucial platform for professionals to gain in-depth insights into emerging trends, innovative technologies, and best practices in network monitoring. The computer network monitoring conferences aims to address challenges businesses face with IT infrastructure, operations and cloud. The conferences are broken up into several tracks, each with a different area of focus. The agenda and key speakers offer more opportunities to learn and discover knowledge and improve the network monitoring operations. Top 7 Network Monitoring Conferences of 2023 1.TMA Conference 2023 June 26-30, 2023 | Naples (Italy) The 7th edition of Network Traffic Measurement and Analysis Conference will offer a significant opportunity for leaders in the networking industry. Organized by the prestigious University of Naples Federico II, the TMA Conference 2023 provides a platform for presenting cutting-edge research and controversial work in network measurements. One of the Technical Program Committee (TPC) chairs for this year's conference is Johanna Ullrich, a renowned researcher at SBA Research and the Head of the Networks and Critical Infrastructures Security Research Group. With her expertise and insights, Ullrich will share insights with a compelling keynote speech that will offer valuable knowledge to attendees. Moreover, the event boasts technical sponsorship from reputable organizations such as IFIP, IFIP TC6-WG6.6, IEEE, and IEEE ComSoc, further solidifying its significance in the networking industry. 2.IEEE International Black Sea Conference on Communications and Networking July 4-7, 2023 | Istanbul (Turkey) A significant event for networking industry leaders, IEEE BlackSeaCom 2023, offers grants to participants who have registered and co-authored accepted papers, fostering engagement and recognition within the conference networks. The special session on machine learning and intelligent algorithms for emerging wireless communications brings forth groundbreaking research. Esteemed speakers like Henning Schulzrinne, Melike Erol-Kantarci, Bülent Kaytaz, and BASIL MANOUSSOS to offer valuable insights about network monitoring in the event. Attending this network monitoring conference will allow industry leaders to network, collaborate, and stay updated on the latest advancements in event monitoring and network monitoring events. 3.IEEE International Symposium on Local and Metropolitan Area Networks July 10-11, 2023 | London (UK) IEEE LANMAN 2023 provides a robust platform for industry leaders by bringing together experts to discuss the latest technical advances in local and metropolitan area networking. With a focus on theory and experimentation, LANMAN 2023 invites advanced papers pushing network monitoring events' boundaries. The keynote speakers, including Tommaso Melodia and William Lincoln Smith, are to delve into topics like open RAN systems, edge computing, routing, and network functions. Attending LANMAN 2023 allows industry leaders to expand their conference networks, gain valuable insights, and stay at the forefront of network events and management, empowering them to drive innovation and enhance their network monitoring strategies. 4.International Conference on Computer Communications and Networks (ICCCN 2023) July 24-26 2024 | Hawaii (US) A must-attend event for computer communications and network industry leaders serves as a platform for presenting innovative ideas and fundamental advancements in computer communications and networks. The conference facilitates communication and collaboration among researchers and practitioners, driving scientific and technological innovation to enhance communications and networking. Keynote speakers including, Ness B. Shroff, Puneet Sharma, and Dr. Gene Tsudik will address designing future XG networks, complexities of edge-to-cloud platforms, and compromise/malware detection for low-end devices. Attending ICCCN will help expand network through conferences, gain a deeper understanding, and advance their network monitoring techniques with shared expertise and knowledge. 5.SmartNets 2023 July 25-27, 2023| Istanbul (Turkey) SmartNets 2023 is a pivotal networking conference aiming to bridge the gap between the physical world and cyberspace by connecting everything. The event will bring together experts and researchers from academia to discuss the challenges and solutions in areas like embedded equipment design, resource-constrained media communications, security, data analysis, and services. The conference will be focusing on future scientific issues, covering topics such as Industry 4.0, smart cities, healthcare systems, big data analytics, edge computing, next-generation networks, and more. SmartNets 2023 will enable leaders to gain access to the latest research findings, address digital transformation challenges, explore wireless communication technologies, and exchange experiences on implementing secure and reliable communication services. 6.IEEE International Mediterranean Conference on Communications and Networking September 4-7, 2023 | Dubrovnik (Croatia) IEEE MeditCom is a highly anticipated networking conference that brings together worldwide visionaries from academia, research labs, and industry. The event will focus on addressing the challenges in communications and networking. It will provide a platform for researchers to present their work on various topics, including theoretical and systems research and vertical technologies. By attending IEEE MeditCom, industry leaders in the networking industry will be able to discover the latest advancements and research findings. Furthermore, the conference will offer an opportunity to engage with local IEEE Sections, ComSoc Chapters, and Sister Societies from the Mediterranean region. The presence of distinguished keynote speakers like Gerhard P. Fettweis, Petar Popovski, Jean-Claude Belfiore, Mohamed-Slim Alouini, and Antonia M. Tulino will further enhance the value of this event. 7.Cyber Security Training at SANS Network Security Las Vegas 2023 September 6-11, 2023 | Las Vegas (US) SANS Network Security 2023 offers industry leaders in the network industry the opportunity to learn valuable real-world cybersecurity skills from experts. The event, both live online and in Las Vegas, will provide interactive training with hands-on labs and the chance to participate in NetWars Tournaments. Attending SANS Network Security will allow professionals to enhance their knowledge, network with peers in real-time, and stay up-to-date with industry trends. With courses aligned with GIAC certifications, attendees can validate their expertise in specialized InfoSec, network monitoring domains and job-specific roles. Jon Gorenflo, a prominent figure in the field, is a keynote speaker at the event, and will be sharing his expertise and on-field experience. Conclusion The event listing showcases numerous opportunities for networking businesses to gain a competitive edge. By experiencing these upcoming conferences, industry leaders can tap into the latest research, emerging technologies, and best methods in network monitoring. This invaluable knowledge equips them to make informed decisions, develop innovative solutions, and optimize processes. The conferences allow to connect and enable businesses to explore new avenues, forge strategic alliances, and unlock potential growth opportunities. Ultimately, the comprehensive insights gained from these conferences empower networking businesses to adapt to evolving market dynamics, enhance their capabilities, and thrive in an innovative environment.

Wireless, 5G

Article | May 18, 2023

Applications of AI/ML Modern businesses are adopting Artificial Intelligence (AI) that encompasses disciplines like machine learning (ML), natural language processing (NLP), evolutionary computation, etc., to increase their productivity and management capabilities. Companies like Qualcomm are using AI and machine learning to improve their customer experience. “Across many industries, we are currently experiencing the creation of intelligent machines that is using AI to simulate smart behavior.” -Dr. Vinesh Sukumar, Senior Director- Head of AI/ML Product Management at Qualcomm, ( in an interview with Media7) The application of machine learning in networking is swiftly taking shape. However, as the problems in modern computer networks are getting tedious to handle, AI tools are being introduced to hard-carry their smooth functioning. Let’s take a look at how network complexity impacts businesses: Difference in Network Parameters Different client devices like laptops, smartphones, CCTV cameras, etc., are connected to a single network. However, their requirements and parameters are different. Therefore, the IT team of the business needs to meet them without compromising the functionality and security of the network. Users Prefer Wireless Networks Wireless networks are more complex than wired ones. They perform dynamically depending on the number of users, applications, and other variables. Impact of Cloud Computing Most applications are now cloud-based, and such a network has multiple data entry points and requires more support. User Experience Deciphering root cause analysis, finding correlation and solutions becomes tedious without an AI/ML model. Complex patterns remain unanalyzed, and this creates a vacuum between the customer and the business. What Does ML Bring to the Table? Machine learning applications in networking correlate to solving four types of network problems: clustering, extraction, regression, and classification. For classification and regression, ML clusters similar data and creates a gap between data groups. It then successfully maps a new set of data to a pre-set continuously valued output. As for extraction, it easily establishes a statistical relationship between the data it analyzes. Machine learning applications in networking encompass the following: Automation and Cognitive Computing ML enables automation in data processing by eliminating the human error factor and constantly improving with time. It analyzes data, improves the productivity, security, and health of the network. Cognitive computing allows processing diverse data sets, detecting and finding root causes and common traits within the system. Network Monitoring & Security Network monitoring is used to solve problems in a large dataset by deciphering the hidden pattern in the data. It then predicts the outcome for clustered data, malware attacks, or impending network failure. It recognizes impending threats in time and sends out warnings. ML uses anomaly-based intrusion, misuse-based intrusion, or hybrid intrusion to prevent misuse, modification, unauthorized access, or malfunction. Traffic Prediction, Classification, and Routing Network traffic prediction is important to handle any mishaps proactively. Network analysis in machine learning is done by using Time Series Forecasting (TSF). By using a regression model solution, TSF finds a correlation between the traffic volume in the future and the traffic previously observed. Traffic classification ensures Quality of Service (QoS), planning ahead for capacity, security, performance analysis, etc. It helps with proper resource utilization by pinpointing unnecessary traffic in a critical application. Factors like cost-effectiveness, link utilization, operational capabilities, and policies are also considered by the ML model. Congestion Control ML models control the number of packets that enter a network to ensure that the network is stable, fairly utilize resources, and follow queue management employed for congestion control. Efficiently Managing Resources ML efficiently manages network resources like the CPU, frequency, switches, memory, routers, etc., by using analytical decision-making. ML Learning Curve ML models learn in the following ways: Pitfalls Like any other technology, machine learning application in networking comes with pitfalls and limitations. Here are a few: Data Quality The efficiency of an ML model is based on the quality, quantity, and diversity of data it processes so it can deduce patterns or identify root causes. Most ML models use simplistic synthetic data for training, validation, and performance. The same cannot be said about practical settings because the data comes from different applications and services and is more complex. Feasibility There are scalability and feasibility issues because each network and application is different. Moreover, there are no set standards for uniformity for implementation which makes it hard to set benchmarks or best practices. Control over autonomic networks is distributed and remains limited based on the vendor’s specific devices. Predictive Analysis and Its Cost Network analysis and machine learning prediction require additional accurate and effective monitoring investments. Moreover, fault management may have some potholes as there may be a scarcity of normal fault data. High FPR (False Positive Rates) Anomaly detection by ML in networking has not created enough buzz in the industry because it generates high FPRs during operations. Also, no detailed anomaly report is generated, so no anomaly history log can be maintained. Striking a Balance ML requires time to learn and mitigate issues. It is difficult to identify, in advance, how complex the ML’s approach will be. Striking a balance between the performance and computational cost is difficult. Deciphering comprehensive evaluation metrics is also a tedious task. No Theoretical Model There is no theoretical model, in turn, a unified theory, for ML in networking, so each network may have to be learned separately. The current machine learning applications in networking are made keeping in mind certain applications. Over time, more research to tailor ML for certain networks needs to be done. Cross-domain experts who understand both ML and networking are also rare. Solutions Software Defined Networking (SDN) CISCO helped PwC Italy set up a secure network at their new twenty-eight-floor tower with the help of their SD-Access product. PwC wanted a secure, robust network with increased Wi-Fi and wired connectivity for their 3000 employees by streamlining network operations. “We needed a robust and highly reliable wireless network infrastructure that’s as advanced as the tower itself.” -Simone Demaria,Network Architect and Infrastructure Manager at PwC Italy By applying Software Defined Network (SDN), IT personnel can remotely govern network policies in real-time through open interfaces, so traffic engineering is easily possible. SDN also contributes to network virtualization. SDN supports the upcoming 5G ecosystem. When combined with NFV and VNF, SDN can revolutionize networking. Going Beyond Traffic Volume & Prediction To tackle the limitations that TSF-based traffic prediction models have, leveraging features beyond traffic prediction and concentrating on traffic interpolation and sampling could be viable. Research is ongoing on this possibility. Summing It Up As the influx of data keeps on increasing, the complexity of networks will increase in tandem. For successfully implementing ML for streamlining networking, the ML approaches we are aware of today need to be upgraded to accommodate multi-layer networks and multi-tenancy so autonomic networking can be a reality. FAQs How Can ML Help in Making Networking Smarter? ML can streamline the network by automation, threat detection, and improving its performance. How Complex Is Integrating ML into Networking? The complexity depends on the type of network you are integrating it into. What to Keep in Mind Before Using Ml in Networking? 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Article | May 20, 2021

I’m a new-ish remote worker and, although I love 99% of everything associated with it, lately, after every virtual meeting I have, I’m feeling exhausted and drained. And not in the normal, everyday work exhausted and drained kind of way. It’s a peculiar combination of eye strain, headaches, and general malaise that I really only experience after a long day of virtual meetings. I was curious if others were feeling the same so I did a completely non-scientific study of my remote work friends to see how they’ve been feeling. Turns out, I’m not alone. Workers everywhere are going through a huge transition as the work from anywhere model has accelerated at breakneck speed since the pandemic. Although some parts of the world are slowly returning to a new normal, many employers, including Tangoe, have made the decision to keep the work from anywhere model while some organizations are electing to use a hybrid model of partly remote, partly in-office.