5G health risks to be considered by City Council

JIM REDDEN | March 10, 2019

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The City Council will consider requesting additional federal studies of the potential harmful health impacts of 5G wireless communication technologies on Wednesday. The resolution introduced by Mayor Ted Wheeler and Commissioner Chloe Eudaly says some studies have suggested 5G technology could increase cancers in those exposed to it — which would be almost everyone in cities because of the large number of closely spaced "small-cell" antennas required. "There is evidence to suggest that exposure to radio frequency emissions generated by wireless technologies could contribute to adverse health conditions such as cancer. Wireless companies in the U.S. say they'll have to install about 300,000 new antennas, close to the total number of cell towers built over the past three decades. This substantial increase in cell towers deployed in communities means greater contact with them," reads the resolution to be considered March 13.

Spotlight

Qualcomm

At Qualcomm, they invent breakthrough technologies that transform how the world connects, computes, and communicates. They interact with products and technologies made possible by Qualcomm every day—5G-enabled smartphones that double as pro-level cameras and gaming devices, connectivity solutions that keep people connected even in remote areas, 5G that makes cities safer with smart infrastructure, and the technology that powers the smart, connected factories that manufactured people's latest purchase. Their work is behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.

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5G

Impact of Widespread Implementation of 5G on Cloud Computing

Article | November 25, 2021

Introduction 5G is predicted to have a significant impact on how cloud computing operates in the future. It will undoubtedly revolutionize the communication and networking industry. In addition, it will have a significant impact on all other industries. Transmission speeds will be 10 times faster in 5G than in 4G. Apart from networking and communication industries, it will also revolutionize other healthcare, automotive, and many more. Commercial 5G smartphones are already in the market. A study report by Ericsson Mobility predicts that there will be one billion 5G subscriptions by 2023. It will account for about 20% of the mobile data traffic. 5G, with its features such as low latency performance and high speed, has all the capabilities of developing cloud computing and take to the next level. As a result, there will be an unpredictable positive impact of 5G on cloud computing, especially in the industries and sectors that use the latest technologies such as the Internet of Things, machine learning, and AI. It has already started redefining business networks. It is also expected to make tremendous, unpredictable progress and changes in how cloud computing and networks perform in storing, moving, and accessing data. It will be possible as 5G brings more technological applications to make digital transformations faster and more efficient for businesses. 5G Network- Advantages As said in the introduction, there are many advantages to 5G network. Some of them can be: Greater transmission speed Lower latency Higher capacity Compared to 4G, 5G has increased bandwidth. These features will change the way people work, live, and play in the future once the 5G network comes into play widely. How Will 5G Impact Cloud Computing? Undoubtedly 5G has the potential to redefine the future of cloud computing. It will transform edge computing. Let us look in detail at what impact 5G will bring in cloud computing. Mobile Cloud Applications to Become More Efficient and Widely Used Undoubtedly 5G has the potential to redefine the future of cloud computing. It will transform edge computing. Let us look in detail at what impact 5G will bring in cloud computing. Mobile Cloud Applications to Become More Efficient and Widely Used Organizations today widely use cloud-enabled applications for customer services as well as for their different operations. Once the widespread use of the 5G network starts, the mobile application will become more efficient and widely used. It will be reflected more in the industries such as healthcare and banking. Enabling Cloud Service Providers to Reach Customers Reliably and Easily 5G will make a machine to machine communication and larger computing possible. This will make accessing virtual machines via phones a common practice. Mobile users will get more features and options from cloud computing enterprises. Remote workers will access cloud services as hotspots will become faster and uninterrupted. Complete Transformation of Edge Computing The emergence of edge computing has solved the issues of unnecessary traffic on the cloud and latency. The need for edge computing became strong when internet penetration and IoT came into existence. Now, G5 will make edge computing grow, making it an essential thing. G5 will transform edge computing entirely and increase the demand for it. As a result, edge and 5G are becoming mutually reinforcing phenomena. 5G will work on edge computing to provide quick real-time data. This is because edge computing has the potential to provide low latency and higher bandwidth. Faster Streaming 5G network will surprise companies and entities with its fast data transfer capabilities. It will be ten times faster than the 4G network. It will facilitate storage and faster real-time streaming and thus productivity at its best. “If everything you touch has to go to a data center and back before you see the animation, you're going to notice. Working at the 5G Lab in a mobile edge cloud, all of a sudden, what we thought would be impossible can happen because the 5G network is so fast.” - Ian McLoughlin, LiquidSky Software founder, and CEO Work from any Location As 5G is ten times faster than 4G in transferring data due to its better connectivity, employees can work from any location. It will make remote work possible anywhere. Better Security Systems As technology is ever-evolving, hackers and online frauds come with advanced techniques to steal data. They hold the sensitive information of organizations and do unimaginable damage. Once 5G is rolled out widely, administrators will recognize such frauds in advance and prepare to mitigate such cyber-attacks. Summing up Cloud computing is undoubtedly going to have an impact on cloud computing. The connectivity of 5G is ten times faster than 4G. IT will help people connect to their workplaces from any location. Remote work will make it easier. Cloud mobile applications will become more efficient and reliable. The service providers will have a good relationship with customers as they will be providing prompt and reliable service in terms of connectivity. Joining together with other technologies such as edge computing, AI, ML, technology is expected to get into another level with the wide roll-out of 5G. Frequently Asked Questions How will 5G affect cloud computing? Cloud computing will have a complete transformation and improvement when 5G is rolled out widely. The 5G connectivity has the features such as cloud virtualization, Ultra-reliable low-latency communication, better latency, increased bandwidth, and more flexible cloud-based management. How is 5G going to impact lives? 5G is capable of controlling services remotely. In addition, 5G will enhance autonomous driving, personal communication, IoT, AI, and augmented reality. It will also change the way companies store, access, share and protect data. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How will 5G affect cloud computing?", "acceptedAnswer": { "@type": "Answer", "text": "Cloud computing will have a complete transformation and improvement when 5G is rolled out widely. The 5G connectivity has the features such as cloud virtualization, Ultra-reliable low-latency communication, better latency, increased bandwidth, and more flexible cloud-based management." } },{ "@type": "Question", "name": "How is 5G going to impact lives?", "acceptedAnswer": { "@type": "Answer", "text": "5G is capable of controlling services remotely. In addition, 5G will enhance autonomous driving, personal communication, IoT, AI, and augmented reality. It will also change the way companies store, access, share and protect data." } }] }

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NETWORK MANAGEMENT

How Can Machine Learning Streamline Networking?

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? 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Ericsson’s 5G platform adds unique core and business communication capabilities

Article | February 13, 2020

To leverage the full benefits of 5G and cloud native investments, orchestration and automation are now a critical matter of business. Ericsson’s 5G platform is now being strengthened with new solutions that enable smarter business. David Bjore, Head of R&D and Portfolio, Business Area Digital Services, Ericsson, says: “Through our core networks, service providers can get to market faster and can capitalize on new services, through leading consumer and enterprise communication and monetization solutions, enabling them to stay ahead in the race for 5G business, today and tomorrow.”

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Ericsson researchers top 4.3Gbps downlink on 5G millimeter wave

Article | February 12, 2020

With a technical specification comprising 8 component carriers (8CC) aggregating 800MHz of millimeter wave spectrum, Ericsson engineers achieved delivery rates of 4.3Gbps – the fastest 5G speed to date. Ericsson Radio System Street Macro 6701 delivered data with downlink speeds of 4.3Gbps over-the-air to an industry partner test device during interoperability testing. The commercial solution, including network and terminal support, will be available to 5G consumers during 2020.

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Spotlight

Qualcomm

At Qualcomm, they invent breakthrough technologies that transform how the world connects, computes, and communicates. They interact with products and technologies made possible by Qualcomm every day—5G-enabled smartphones that double as pro-level cameras and gaming devices, connectivity solutions that keep people connected even in remote areas, 5G that makes cities safer with smart infrastructure, and the technology that powers the smart, connected factories that manufactured people's latest purchase. Their work is behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.

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