Enterprise Mobility, Mobile Infrastructure
Article | June 16, 2023
Advancements inconnectivity have fueled the rapid progress in digitalization. From 1G in the 1980s to 4G in the last decade, wireless connectivity has constantly contributed to the transformation of businesses and the global economy. Today's 5G and Wi-Fi 6 technologies provide exciting features that are critical to increasing corporate productivity and improving people's digital experiences.
When we refer to the 5G and Wi-Fi 6 revolutions, we're not talking about undisturbed movie streaming or faster downloads; we're talking about making sci-fi movie fiction a reality. Things you used to only see in movies, like robots doing chores, autonomous vehicles, smart cities, virtual reality gaming experiences, remote surgeries, telemedicine, automated assembly line production, augmented reality marketing strategies, and the way you shop, travel, work, and get medical consultations, will undergo a transformation beyond imagination, and 5G will make it happen.
5G VS Wi-Fi 6
5G and Wi-Fi 6 Carving the Future of Businesses Together
When it comes to addressing particular needs, both 5G and Wi-Fi 6 are competitive depending on the industry vertical business environment, operation, devices, and applications. While Wi-Fi will be the dominant technology for indoor operations, as well as non-critical applications and the usage of unlicensed spectrum, 5G cellular networks will be used for outdoor coverage, mission-critical applications, highly guarded settings, and the anticipation of various QoS features.
According to a survey conducted by Deloitte, the priorities of companies were 5G and Wi-Fi 6, the importance of which isonly anticipated to grow in the future years.
Adoption of Wi-Fi 6 and 5G is regarded as a strategic requirement, leading businesses into a new era of wireless connectivity. With the convergence of Wi-Fi and 5G, organizations can do business everywhere while being highly productive and providing the greatest user experience.
Businesses will attain the following primary goals by transitioning to this enhanced wireless 5G technology:
increased effectiveness
enhanced security
Taking advantage of the benefits of these two forces,
such as big data analytics, AI, and edge computing.
The overall objective of leveraging this deadly mix is to unlock the possibilities of other emerging technologies such as IoT, cloud, Edge computing, big data analytics, VR, AR, robots, and others. Together, 5G and Wi-Fi 6 operate as a revolutionary multiplier.
Closing Note
5G and Wi-Fi 6 are two separate technologies that can work in tandem. They share the following characteristics: low latency, faster data rates, increased capacity, and excellent performance. Even though 5G and Wi-Fi 6 complement each other's capabilities, the environment, sensitivity of the application, and business use cases will determine which is the best match.
A holistic approach of Wi-Fi 6 and 5G is the optimum method for developing a smart city that is entirely networked or offering powerful Internet connectivity for families and businesses. Both technologies are critical in today's world, and every breakthrough in connection, whether it's 5G or Wi-Fi 6, contributes to our society's overall growth and innovation.
Read More
Network Infrastructure, Network Management
Article | July 10, 2023
Discover network intrusion monitoring with top network monitoring books. Explore insights, best practices, and tools to secure network visibility and processes used in monitoring network performance.
Observing networks for performance and security anomalies is crucial for businesses that rely on their business network. Network monitoring solutions monitor performance metrics across an entire network to guarantee that your systems operate properly. From monitoring network performance to ensuring comprehensive visibility, the books listed below will offer a wealth of knowledge and expertise to empower professionals in the networking industry.
10 Network Monitoring Books to Effectively Monitor Performance
1 Zabbix Network Monitoring
Author: Rihards Olups
Zabbix Network Monitoring book is an indispensable resource for networking professionals seeking to enhance their network visibility and improve network performance monitoring. This comprehensive guide offers an approach to effectively monitor network devices and applications using Zabbix 3.0. One of the network monitoring books, Zabbix Network Monitoring covers essential topics such as data collection, native Zabbix agents, and SNMP devices. It also delves into monitoring Java application servers, VMware, notifications, permission management, system maintenance, and troubleshooting. It empowers readers to build a robust network monitoring solution to gather data from various systems. By exploring the intricacies of Zabbix, this book ensures that network monitoring becomes an efficient and effortless task, ultimately enhancing network visibility and performance for all stakeholders.
2 The Practice of Network Security Monitoring
Author: Richard Bejtlich
An essential book for networking professionals, The Practice of Network Security Monitoring: Understanding Incident Detection and Response, helps to enhance network visibility and strengthen network security. The book's author, Richard, guides readers through implementing network security monitoring (NSM) as a proactive defense strategy. The book emphasizes integrating NSM into security measures to effectively detect and respond to intrusions. It also provides practical insights on deploying, building and operating an NSM operation using open-source software and vendor-neutral tools. With a focus on proactive incident response, this book equips readers with the knowledge and techniques to establish a robust security net that detects, contains and controls attacks. By implementing the practices outlined in this book, organizations can better safeguard their networks and prevent the loss of sensitive data.
3 Internet and Network Architecture
Author: Sang Hinch
Internet and Network Architecture: Analyzing Performance with Network Monitoring Tools is a must-read for professionals in the networking industry seeking to enhance network visibility and optimize network performance monitoring. This comprehensive guide offers a thorough introduction to TCP/IP, FTP, IP addresses, ports, and web page retrieval, providing a solid foundation in internet and network architecture. The book explores the complex workings of routers, data transmission, network configuration, and architecture, enabling readers to build efficient and secure networks. Focusing on practicality, it emphasizes using network monitoring tools to analyze performance and troubleshoot issues effectively. By mastering the fundamentals presented in this book, readers will gain the knowledge and confidence to navigate the World Wide Web, understand network protocols, and make informed decisions for network optimization.
4 Zabbix 4 Network Monitoring
Author: Patrik Uytterhoeven & Rihards Olups
Zabbix 4 Network Monitoring: Monitor the performance of your network devices and applications using the all-new Zabbix 4.0, 3rd Edition is a comprehensive and highly valuable resource for professionals in the networking industry. This book serves as an essential guide to effectively monitor the performance of network devices and applications using Zabbix 4.0. Written for both beginners and experienced users, the book offers a step-by-step approach to help readers quickly grasp the installation process and explore the new features of network monitoring. From understanding native Zabbix agents and SNMP devices to harnessing Zabbix's integrated functionality for monitoring Java application servers and VMware, readers will gain comprehensive knowledge. With insights into optimizing performance, automating configurations, and troubleshooting network issues, it will develop advanced skills to ensure a healthy and efficient network.
5 Applied Network Security Monitoring
Author: Chris Sanders & Jason Smith
An indispensable book for professionals in the networking industry Applied Network Security Monitoring: Collection, Detection, and Analysis offers a comprehensive guide to become a proficient NSM analyst. Focusing on NSM's collection, detection, and analysis stages, this book equips readers with essential concepts through real-world examples and practical scenarios. Recognizing that prevention is not foolproof, the book emphasizes the critical role of detection and response in minimizing the impact of network intrusions. With insights from experienced NSM professionals and access to sample data, readers gain valuable knowledge to analyze network security incidents effectively. From data collection methods to in-depth coverage of tools like Snort, Suricata, Bro-IDS, SiLK, and Argus, this monitoring book provides hands-on experience and practical examples using real PCAP files. By leveraging Security Onion for lab examples, readers can develop and enhance their analytic techniques.
6 Practical Network Security Monitoring: Using Free Software
Author: Elizabeth Graham
Practical Network Security Monitoring: Using Free Software offers guidance on utilizing free software to collect, monitor, and analyze network traffic, thereby detecting and identifying potential threats. With a focus on providing practical exercises, this book equips beginner to intermediate users with the necessary knowledge to detect and defend cyber threats. Step-by-step instructions enable readers to install, configure, and effectively use free tools, allowing hands-on experience in analyzing network traffic and identifying malicious activity. This book edition covers Security Onion, introducing significant changes to the platform. The updated content includes new intrusions, malware, PCAP examples, and an introduction to web-based PCAP analysis tools. A bonus chapter challenges readers to test their knowledge through self-assessment.
7 Efficient Body Sensor Networks for Patient Monitoring
Author: Jawaid Iqbal
Efficient Body Sensor Networks for Patient Monitoring is a book for professionals in the networking and healthcare industry, focusing on the challenges, Body Sensor Networks (BSNs) face in continuously monitoring patient vital signs. BSNs operate in constrained environments and encounter issues such as patient information privacy, secure data transmission over public networks, high overhead, and energy constraints. Being one of the prominent network monitoring books, it presents five efficient and secure attribute-based schemes designed explicitly for BSNs. These schemes address the mentioned challenges comprehensively, providing practical solutions to enhance network monitoring performance in patient monitoring scenarios. By proposing novel approaches, this book contributes to the advancement of efficient and secure patient monitoring within BSNs.
8 Mastering Python Networking
Author: Eric Chou
A comprehensive guide created for professionals in the networking industry seeking to leverage Python for network automation, monitoring, and management, Mastering Python Networking: Utilize Python packages and frameworks for network automation, monitoring, cloud, and management, focuses on the latest Python libraries and frameworks and equips readers with the necessary skills to tackle common & complex network challenges effectively. From interacting with network devices to implementing advanced features using Python 3, the book covers a wide range of topics, including Docker containers, network data analysis, cloud networking, and DevOps practices. With practical examples and insights into tools like GitLab & ELK, network engineers, developers, and SREs will gain valuable knowledge to enhance their network performance monitoring and visibility.
9 AWS Security Cookbook
Author: Heartin Kanikathottu
Focusing on securing Amazon Web Services (AWS) infrastructure, AWS Security Cookbook: Practical solutions for managing security policies, monitoring, auditing, and compliance with AWS is written. Being one of the network monitoring books that provide professionals with valuable insights related to network visibility and network performance management in the networking industry, this book offers practical solutions to address common security challenges, including permission policies, key management, network security, and cloud security best practices. Industry professionals can explore various AWS services and features that enhance security, including IAM, S3, CloudWatch, CloudTrail, Config, GuardDuty, and Macie. In addition, the book also covers compliance requirements and demonstrates how to maintain security and compliance using AWS security services.
10 The Best of TaoSecurity Blog, Volume 2
Author: Richard Bejtlich
The Best of TaoSecurity Blog, Volume 2: Network Security Monitoring, Technical Notes, Research, and China and the Advanced Persistent Threat, guides professionals in the networking industry, particularly those interested in network security monitoring. Written by Richard Bejtlich, a renowned cybersecurity expert, he curates the best entries from his 17 years of writing on the TaoSecurity Blog. The book explores various intervention detection and response aspects, leveraging threat intelligence sources, network data, application and infrastructure data, and endpoint data. Additionally, it provides insights into Chinese hacking activities over the past two decades, offering a unique perspective from a defender on the front lines. With new analysis accompanying each post, readers can gain valuable knowledge on the evolution of the security industry, defensive methodologies, and strategies for enhancing national security.
Conclusion
In conclusion, the recommended books discussed in this article provide valuable insights and guidance for networking experts in the B2B sector. These resources cover various aspects of monitoring network performance, enhancing network visibility, and addressing security concerns. By delving into these monitoring books, professionals can gain a deeper understanding of effective network performance monitoring techniques, ensuring optimal visibility across their infrastructure. With the ever-evolving networking landscape, staying up-to-date with the latest trends and best practices, it is crucial for maintaining a high-performing network. These books offer industry-relevant knowledge and empower networking experts to make informed decisions, ultimately leading to a robust and efficient network infrastructure.
Read More
Unified Communications, Network Security
Article | July 10, 2023
Without a robust 5G network, carriers will not be able to take full advantage of new business opportunities surrounding augmented reality (AR). This was the bottom-line message from Huawei’s recent Better World Summit (BWS), which turned the spotlight on “5G+AR.”
How the network is designed is another key consideration. If AR headsets are to become lighter and cheaper, offloading compute processing to the network edge and cloud — over stable and low-latency 5G connections — is essential. It is why Huawei advocates a partnership approach, spanning AR collaboration in all three areas: 5G networks, devices, and content.
The prize of getting these sorts of partnerships ‘right’ is huge. According to Huawei, working in tandem with a third-party research institute, the AR market will reach a hefty $300 billion with 1.2 billion users by 2025.
Read More
Network Management
Article | November 22, 2021
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?
Consider investment costs, data availability, feasibility, and scalability.
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [{
"@type": "Question",
"name": "How Can ML Help in Making Networking Smarter?",
"acceptedAnswer": {
"@type": "Answer",
"text": "ML can streamline the network by automation, threat detection, and improving its performance."
}
},{
"@type": "Question",
"name": "How Complex Is Integrating ML into Networking?",
"acceptedAnswer": {
"@type": "Answer",
"text": "The complexity depends on the type of network you are integrating it into."
}
},{
"@type": "Question",
"name": "What to Keep in Mind Before Using Ml in Networking?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Consider investment costs, data availability, feasibility, and scalability."
}
}]
}
Read More