In 2025 and beyond, semiconductor sales—along with employment opportunities for engineers in the dynamic chip industry—are expected to rise precipitously.

Semiconductor sales are projected to hit nearly US$700 billion in 2025, grow to US$1 trillion by 2030, and potentially reach US$2 trillion by 2040, according to a Deloitte Insights report.

A number of trends are driving the semiconductor industry forward. First, post-pandemic sales of computers, tablets, smartphones, and other wireless and wired communications devices—which collectively accounted for nearly 60% of global semiconductor sales as of 2023-2024—are forecasted to experience strong growth during the next five to ten years. Additionally, demand for high-tech “generative AI chips” is on the rise. These chips enable computers’ central processing units (CPUs) to execute machine learning algorithms for everything from facial recognition applications to customer service-related chatbots, language processing for voice assistants, and more. 

On the design side, growth of the semiconductor market is supported by an increasingly popular chip manufacturing strategy known as “shift left,” which enables tasks that were once performed sequentially to be done concurrently for greater efficiency and cost savings.

Working to Meet Demand

To keep pace with projected growth, manufacturers are expanding capacity worldwide:

For example, after investing US$65 billion into chip fabrication facilities in Phoenix, Arizona in 2020, industry leader Taiwan Semiconductor Manufacturing Company (TSMC) recently announced additional investment of US$100 billion in order to double that location’s manufacturing capacity. Supported by almost US$8 billion in funding from the U.S. CHIPS (“Creating Helpful Incentives to Produce Semiconductors”) and Science Act of August 2022, key player Intel recently announced its plans to invest US$100 billion to expand its U.S-based domestic chip manufacturing capacity and capabilities in Arizona and Ohio. 

Elsewhere around the world, STMicroelectronics recently announced its intention to build a new, high-volume manufacturing facility in France. Semiconductor Manufacturing International Corporation (SMIC) is working to expand three of its existing Chinese facilities in Shanghai, Beijing, and Tianjin. Manufacturers Nvidia, AMD, and Micron have all announced plans to establish new operations in India.

A Skills Gap Persists

While worldwide sales of semiconductors, as well as manufacturing capacity to meet demand, are all on the uptick, one major challenge stands to potentially derail production: a global shortage of skilled workers.

“Because semiconductors are foundational to virtually all critical technologies of today and the future,” the SIA study confirmed, “closing the talent gap in the chip industry will be central to the promotion of growth and innovation throughout the economy.”

Experts from Deloitte agreed, noting that the semiconductor field will need “electrical engineers to design chips and the tools that make the chips,” while “digital skills, such as cloud, AI, and analytics, are needed in design and manufacturing more than ever.”

Positioning Engineers for Success in Semiconductors and AI

To support workforce development, IEEE offers online learning programs that equip semiconductor professionals with cutting-edge AI and chip design skills. These include:

• Artificial Intelligence and Machine Learning in Chip Design:
  Offered by IEEE Educational Activities in partnership with IEEE Future Directions and IEEE Global Semiconductors, this course program discusses the significance of artificial intelligence and machine learning. It provides an overview of how these technologies are shaping the future of chip design as well as key applications in design automation, relevant technologies, deployment considerations, and future prospects.
• Integrating Edge AI and Advanced Nanotechnology in Semiconductor Applications:
  This five-course program created in partnership with the IEEE Computer Society helps learners understand the intersection of artificial intelligence, edge computing, and nanotechnology with real-life applications and future trends.
  
• Semiconductor Manufacturing: Impact and Effectiveness of AI
  This course offers a comprehensive introduction to the evolving landscape of semiconductor manufacturing with special emphasis on the integration of artificial intelligence into this critical industry.

Upon successfully completing the programs, participants earn professional development credits, including Professional Development Hours (PDHs) and Continuing Education Units (CEUs). They’ll also receive a digital badge highlighting their proficiency in the technology area which can be showcased on social media.

For institutional access, contact an IEEE Content Specialist. Individuals can explore and enroll directly via the IEEE Learning Network.

 

Recent advances in edge computing and edge artificial intelligence (AI) are revolutionizing a broad range of industries and enabling a new age in predictive analysis and operational performance—so what exactly is edge AI and how is it changing the way businesses operate?

Edge AI refers to AI computations that are performed near the user at the “edge” of a network and close to where the data is located—which could be a retail store, a workplace, or an actual device such as a phone or a traffic light—rather than long distances away in a central cloud computing facility or private data center. Recent advances in machine learning and high-speed computing, along with the ongoing worldwide adoption of Internet of Things (IoT) devices that continue to deliver faster and more reliable connectivity, have led to the growing deployment of AI models at the edge.

Ultimately, one of the reasons why AI has been so successful when paired with edge computing is because modern-day AI algorithms have become increasingly sensitive to real-world issues and conditions. From the field of healthcare to agriculture and everything in between, AI has become more capable than ever of recognizing patterns and trends within the wide range of different circumstances that are present in real life. As a result, artificial intelligence is highly effective in edge applications and would be far less feasible, and, in some cases, even impossible to deploy in a centralized cloud or private data center. This is due to issues related to latency (delays in network communication), bandwidth (the amount of data that can be transmitted over a network in a specified amount of time), and privacy (the ability to control how personal data is collected, stored, and used).

Because edge technology performs analyses on data locally through decentralized capabilities, it can respond to user needs much quicker while also significantly reducing networking costs for an organization because it requires less internet bandwidth. Furthermore, the processing of data isn’t reliant on internet access, so mission-critical and time-sensitive AI applications can enjoy greater access and reliability. These edge computing benefits combined with the expanding flexibility and “intelligence” of AI neural networks are allowing organizations to capitalize on real-time insights at a lower cost and with greater security and privacy.

Edge AI Use Cases

Edge AI is being recognized as a pivotal technology that will continue to have a major impact on new product development, the streamlining of processes, and the user experience across a broad range of industries.

In the utility industry, for example, edge AI models are combining historical data, weather patterns, and other inputs to more efficiently generate and distribute energy to customers. 

In manufacturing, sensor data analyzed by edge AI technology is helping to predict when machines will fail and help factories avoid costly downtime.

Edge AI-enabled surgical tools in the healthcare field are helping doctors make real-time assessments in the operating room that improve surgical outcomes.

In the retail world, edge AI is working to enhance customer service by enabling the convenience of voice-based ordering by customers via smart speakers or other intelligent devices.

In the transportation sector, where real-time decisions can be the difference between life and death, edge AI is being used to adjust traffic lights to regulate traffic flow and reduce congestion.

And in the field of security across numerous organizations, edge AI’s real-time analysis of video footage can identify unwarranted activity and immediately inform authorities.

The Power of Edge AI and Nanotechnology in Semiconductor Applications

According to the authors of Artificial Intelligence in Nanotechnology, an academic white paper on the significant role AI can play in the development of nanotechnology, the incorporation of AI into nanotechnology—defined as the study and control of materials at the nano (molecular, atomic, or subatomic) level to create new, stronger, and more conductive materials and devices—has led to an exciting new vein of research and development called “AI-nanotechnology.”

Thanks to the big data that AI is able to analyze, semiconductors—made up of a wealth of nanoparticles—are immediately benefiting from the combination of edge AI and nanotechnology to design more efficient chips and bring them to market sooner.

Semiconductors, or chips, are components used to conduct or block electric current. They drive a bevy of modern-age devices, including mobile phones, computers, TVs, washing machines, LED bulbs, medical equipment, and more.

The use of edge AI is enabling semiconductor manufacturers to optimize their product’s power, performance, and area (or “PPA,” the three goals of chip design). It benefits PPA by helping engineers to design advanced new chips as well as to efficiently and cheaply overhaul and shrink many older-technology chip designs without needing to update fabrication equipment. By further integrating nanotechnology into this process and being able to design with new and existing materials at nano scales, manufacturers can cost-effectively create more robust semiconductors with improved functionality.

While both of these cutting-edge fields currently face a range of hurdles—ethics, privacy, and bias are issues for artificial intelligence, while nanotechnology struggles with regulatory, environmental, and safety concerns—experts contend that the integration of edge AI and nanotechnology “have the potential to work in concert to spur innovation and solve difficult problems….and [they] hold immense promise for revolutionizing various aspects of science, technology, and everyday life.”

Stay on the Cutting Edge of Continuing Education

A new five-course course program from IEEE, Integrating Edge AI and Advanced Nanotechnology in Semiconductor Applications, explores the intersection of artificial intelligence, edge computing, and nanotechnology through real-life applications and future trends. From the fundamentals of AI nanoinformatics to the specifics of semiconductor design, learners who complete the program will acquire a broad skill set enabling them to navigate the complexities of modern computing.

To learn more about accessing these courses for your organization, contact an IEEE Content Specialist today.

Interested in the course program for yourself? Visit the IEEE Learning Network.

 

Resources

Yeung, Tiffany. (17 February 2022). What is Edge AI and How Does It Work? NVIDIA.

(16 November 2023). Bringing AI to the Edge: How Edge AI is Revolutionizing Industries. Sintrones.

Agrawal, Radheyshree, Tilak Paras, Devand, Aryan, Bhatnagar, Archana, and Gupta, Piyush. (17 March 2024). Artificial Intelligence in Nanotechnology. Springer Nature.

Nanotechnology. National Geographic.

Brode, Bernie. (21 March 2022). AI and Nanotechnology are Working Together to Solve Real-World Problems. Stack Overflow Blog.

2023 Edge AI Technology Report. Chapter I: Overview of Industries & Application Use Cases. Wevolver.

The COVID-19 pandemic is forcing organizations all over the world to digitally transform their operations as more employees work from home. As remote work becomes the new normal, many organizations are transitioning data storage not only to the cloud, but to the “edge” in a major shift towards digital transformation. Edge computing, a form of cloud computing where data is stored along the “edge” of the cloud, brings data closest to where it’s produced and consumed, and as a result, reduces latency while boosting speed. Digital transformation through edge computing is allowing organizations around the globe to operate faster and more efficiently, while reducing costs.

Two-Thirds of Organizations in Global Survey Are Adopting Edge Computing

According to a recent global survey from the International Data Corporation (IDC), two-thirds of IT leaders who participated in the survey have begun to adopt edge computing, with 40% planning to adopt new edge technology in under a year. Motivating factors include edge computing’s improved bandwidth and reduced latency and costs. 

“Enterprises around the world are being confronted by a basic law of physics—distance neutralizes speed, causing latency or a delay between an action and an application’s response,” survey sponsor Lumen Technologies stated in a blog post about the survey. “Controlling latency has never been more important, whether data flows to a distributed workforce or a multitude of smart gadgets that make up the Internet of Things.”

How Organizations Will Use Edge Computing this Year

According to a recent TechRepublic survey, 70% of organizations surveyed transitioned to edge computing to deliver enhanced experience for customers and 46% said they use or intend to use the technology to minimize operational costs. 

Among the main applications for which organizations are currently using or intend to use edge computing include laptops and mobile devices (54%), remote networks and servers (50%), locally deployed software and systems (37%), monitoring of remote assets (27%), virtual mobile networks (12%), other IoT applications (8%), and autonomous vehicles (5%). When asked what edge computing technologies they want to roll out over 6 months, remote servers and networks, as well as laptops and remote mobile devices, ranked equally at 42%. Locally deployed software and systems, ranked at 33%, followed.  

How Digital Transformation for Edge Computing Will Accelerate The Internet of Things

The digital transformation to edge computing technology will also give organizations a greater ability to embrace the Internet of Things. This will empower them to solve problems in revolutionary ways. For example, edge computing combined with Internet of Things technology, such as sensors, will allow businesses to roll out super-efficient “smart factories.” Featuring highly connected equipment, employees will be able to quickly spot and fix problems in production lines more easily.

“The industry will continue to move toward more decentralized compute environments, and the edge will add significant value to digital transformation initiatives,” writes Keith Higgins in RFID Journal.  

Digital transformation will continue well beyond 2021, and there’s little doubt that edge computing will continue to play a major role. 

Bring Your Organization to the Edge

Many organizations don’t fully understand edge computing and the impact it can have on their business. From providing real-time data analysis to reducing system malfunctions, edge computing can be customized to meet an organization’s specific needs.

Prepare your organization for edge computing integration. Designed to train your entire team to support edge computing, IEEE Introduction to Edge Computing is an online five-course program. To learn more about getting access to these courses for your organization, connect with an IEEE Content Specialist today.

Contact an IEEE Content Specialist to learn more about how this program can benefit your organization.

Interested in getting access for yourself? Visit the IEEE Learning Network (ILN) today!

Resources

Vigilarolo, Brandon. (29 January 2021). Business leaders want low latency, not speed, study finds. TechRepublic.

(28 January 2021). Global Business Leaders Rate Latency Higher Priority Than Speed. Multivu.com. 

Higgins, Keith.  (10 January 2021). Trendspotting: Industrial Digital Transformation Matures. RFID Journal.

Edge computing adoption to increase through 2026; organizations cautious about adding 5G to the mix. Tech Republic.

Edge computing is a decentralized alternative to cloud computing that uses a number of smart devices around the “edge” of a network to store data. With the rise of 5G and the Internet of Things (IoT), edge computing is expected to provide numerous benefits to organizations. Such benefits include shorter latencies, improved security, more affordable costs, and responsive data collection. According to a recent report from the research and consulting firm Frost & Sullivan, 90% of industrial enterprises will be using edge computing by 2022.

“To remain competitive in the post-cloud era, innovative companies are adopting edge computing due to its endless breakthrough capabilities that are not available at the core,” David Williams, managing principal at AHEAD, told the Enterprisers Project.“Such benefits include unparalleled local interactivity, reduced impact from service interruptions, improved privacy and security, and reduced latency.”

The Benefits of Edge Computing

Of all the benefits that edge computing can provide to organizations, lightning fast speed and reduced latency will be the most transformative. Moving large amounts of data across a network is time consuming. Edge computing brings computation closer to the user, making data transfer speeds much faster and less cumbersome.

“With edge computing, data is scrutinized and analysed at the site of production, with only relevant data being sent to the cloud for storage. This means much less data is being sent to the cloud, reducing bandwidth use, privacy and security breaches are more likely at the site of the device making ‘hacking’ a device much harder, and the speed of interaction with data increases dramatically,” writes Mark Seddon, CEO of Pact Global, in Information Age.

How will Edge Computing Transform Industries?

Edge computing is expected to pave the way for a number of technological revolutions, such as virtual and augmented reality for smartphone users, and smart cities with interconnected roadways and autonomous vehicles. Edge computing can also transform the industrial sector. Use cases include preventing equipment malfunction and reducing energy expenditure. Another potential application is “smart farming,” in which large sectors of agricultural production can be automated. This in turn could support farmers in boosting crop yields and reducing waste.

The film and gaming industries may be the first to be transformed by edge computing. Film producers must be able to transfer huge video files shot in high resolution. This process is often impossible to do over the internet. In fact, video files are so massive that most are still delivered by vehicle after shoots, rather than digitally. Slow speeds also make computer animation and rendering for film and games difficult.

To help solve this, Amazon Web Services is developing edge computing infrastructure in Los Angeles—a city home to numerous film and gaming companies. There, the tech giant has established the first of what it calls “AWS Local Zones,” an edge computing initiative that delivers low-latency access to Amazon Web Services, the company’s cloud computing platform, in “colocation centers,” rather than solely in Amazon’s vast cloud. These “local zones” provide distributed infrastructure that delivers edge computing and low-latency applications to clients. In each AWS Local Zone is an “AWS Outpost,” a rack that contains AWS cloud infrastructure. So far, Amazon has set up two Local Zones in Los Angeles, and aims to ease operations for the film and gaming industries.

Get Close to the Edge

Many organizations don’t fully understand edge computing and the impact it can have on their business. From providing real-time data analysis to reducing system malfunctions, edge computing can be customized to meet an organization’s specific needs.

Prepare your organization for edge computing integration. Designed to train your entire team to support edge computing, IEEE Introduction to Edge Computing is an online five-course program. To learn more about getting access to these courses for your organization, connect with an IEEE Content Specialist today.

Contact an IEEE Content Specialist to learn more about how this program can benefit your organization.

Interested in getting access for yourself? Visit the IEEE Learning Network (ILN) today!

Resources

Hughes, Matthew. (10 September 2020). What Is Edge Computing, and Why Does It Matter? How To Geek.

Miller, Rich. (4 September 2020). How AWS Cloud Customers Are Using Local Zones for Edge Computing. Data Center Frontier.

Seddon, Mark.(26 August 2020). How the edge and the cloud tackle latency, security and bandwidth issues. Information Age.

Edge computing for business can increase the speed of data processing and analysis. The Internet of Things (IoT) is expected to grow significantly, predicted to reach about $1.6 trillion USD by 2025. Edge technology can help process the copious amounts of data that this surge in IoT-enabled devices will produce.

Because edge computing processes data at the location where the data is being generated, it stores, processes, analyzes and informs actions of users instantaneously. The benefits of edge computing over cloud computing is the speed at which data is analyzed and acted on. See a few ways it can transform a business in the next year.

Real-Time Data Analysis

Data is normally sent to one central location so that it can be analyzed in order to take proper action. However, edge computing allows for the data analysis to take place near the area where it is created.  With edge technology, the data can be kept close to its origin point, which is optimal for nearly real-time decision making.

Augmented Reality

Edge computing has the chance to improve augmented reality. Users will gain a more vivid and realistic augmented reality (AR) experience. By taking advantage of this technology early on, technology firms can be one of the first to provide this upgraded experience to their customers.

Smart Manufacturing

Manufacturing companies can improve their production floors with edge technology. With almost real-time data analysis, it helps improve efficiency and margins. Companies can help avoid line shutdowns by identifying problems while edge computing allows analyzes the collected data.

Security Systems

Large organizations need fast and accurate security systems to help keep their information and buildings safe. Edge computing makes security systems more efficient when operating at a lower bandwidth. Data from security cameras are frequently collected and stored in the cloud through a signal. Edge computing allows each device to have an internal computer that is able to transfer footage to the cloud when it is needed.

Lowered Operational Costs

Because edge computing helps collect data, it does not require a central server to determine what action should be taken. This helps reduce operational costs by needing less storage to hold the information.

Get Close to the Edge with Customized Solutions

Not many organizations know what edge computing means or what impact it can have on their business. For one company, it could mean installing on-site servers that are capable of nearly real-time IoT data analysis. For another company, it could mean reducing organizational costs by using smaller deployments. One key benefit to edge computing it that is can be customized to meet the company’s needs.

Prepare your organization for edge computing integration. Designed to train your entire team to support edge computing, IEEE Introduction to Edge Computing is an online five-course program. The on-demand courses included in this program are:

• Overview of Edge Computing
• Practical Applications of Edge Computing
• Research Challenges in Edge Computing
• Designing Security Solutions for Edge, Cloud, and IoT
• Tools and Software for Edge Computing Applications

To learn more about getting access to these courses for your organization, connect with an IEEE Content Specialist today.

Interested in the course for yourself? Visit the IEEE Learning Network (ILN) to learn more.

 

 

Resources

(23 December 2019). 13 Ways Edge Computing Can Benefit Businesses. Forbes.

Lital, Marom. (13 December 2019.) Enter A New Era Of Edge Computing. Forbes.

While it may be too early to know exactly how 5G will benefit edge computing, the technology will have some sort of impact on consumers and businesses. The growth of edge computing and 5G are mutually dependent. In order for 5G to provide accelerated network speeds, it requires on low-latency and high interconnection that can be delivered through edge computing.

The evolution of 5G networks will affect more than smartphone speeds. While the ability to stream and download files on your mobile device faster will be convenient, it is only a fraction of the potential 5G has in advancing technology. By providing the ability to process large quantities of small data points in a short period of time, 5G is likely to significantly impact sectors such as transport, autonomous vehicles, smart cities, and the Internet of Things (IoT). In these fields, applications that currently use large sets of data and information are likely to benefit from the ability to send the desired information in almost real-time.

Benefits to Utilizing Edge Computing with 5G

By 2025, up to 20% of data might be processed in real-time. The combination of 5G and edge computing will bring consumers and organizations improved data processing, local caching and sharing of computing power, energy efficiency at both network and device level, resilience and security, and optimal work allocation.

• Edge computing allows 5G networks to function at the needed reduced network latency for real-time operations. Together, they can enhance augmented and virtual reality for events, video and speech analytics, video security monitoring, and more.
• 5G combines edge computing into wireless networks with open source initiatives and standards to distribute data across the network, from radio access and transport to new core-enabling capabilities such as network slicing.
• Edge computing applies artificial intelligence (AI) and machine learning technologies to enhance data management across networks.

5G and Edge Security

Edge computing will play a critical role in changing the security of the network. The faster connections and increased interconnection that come with 5G also mean improved connections for cyber criminals.

John Maddison, an executive at Fortinet, Inc., mentions that “The security then needs to be deployed in a different way. And whether it’s deployed in the car itself, in the application, the IoT devices—it’ll be security deployed in the edge compute.”

Getting Ready for Edge Computing and 5G

Prepare your organization for the advancement of edge computing integration. Designed to train your entire team to support edge computing, IEEE Introduction to Edge Computing is an online five-course program. The on-demand courses included in this program are:

• Overview of Edge Computing
• Practical Applications of Edge Computing
• Research Challenges in Edge Computing
• Designing Security Solutions for Edge, Cloud, and IoT
• Tools and Software for Edge Computing Applications

To learn more about getting access to these courses for your organization, connect with an IEEE Content Specialist today.

Interested in the course for yourself? Visit the IEEE Learning Network (ILN) to learn more.

 

Resources

(9 October 2019). 5G Americas: Edge Computing Not a One-Size-Fits-All for 5G. Global Newswire.

(15 October 2019). Edge, 5G And Data Centres: The Beginning Of The End Or The End Of The Beginning?. Data Economy.

Matthews, Kayla. (17 October 2019). How edge computing will benefit from 5G technology. Information Age.

Tripathi, Sunay. (23 October 2019). 5G And Enterprise Edge: Developments Toward A Device-Centric View Of The Cloud. Forbes.

Aten, Jason. (25 October 2019). Everyone Wants a 5G iPhone, but Here Are 5 Industries That Will Actually Be Revolutionized When Ultra-Fast Wireless Finally Arrives. Inc.

Edge computing improves the way businesses collect and analyze their data by processing information near the source as opposed to in the cloud. It provides real-time information, which allows companies to make data-driven decisions. Analyst predict that by 2024, the global edge computing market will rise to $9 billion USD. However, only 56% of networking professionals currently have plans to integrate this form of decentralized computing into their organizations, according to the IDG 2018 State of the Network.

As the technology improves, more companies are exploring edge computing capabilities. So how can your organization get a head start on the integration process?

Steps to Integration

Some helpful steps for organizations looking into edge computing include:

Step 1: Virtualize
Updating your infrastructure with virtualized machines can improve reliability, manageability, and create a solid foundation for edge integration. Besides these immediate benefits, transferring workloads to virtual machines should help simplify a future edge integration.

Step 2: Operational Technology (OT) and Information Technology  (IT)
Many companies with separate Integrating Operational Technology and Information Technology are now seeking to bridge the gap. Because they possess dual skill sets, Hybrid OT and Industrial IT specialists may provide greater performance, productivity, agility, and cost-efficiency.

Step 3: Choose a vendor
The total cost of ownership, deployment, management, downtime risk, and operational efficiency are all key factors when selecting an edge computing solution. Be sure to do your research. Before selecting a vendor that works well with your organization, you should consider where the platform will be installed. The physical environment as well as the distance between the location and where the data is collected will likely impact your decision.

Step 4: IIOTint
Industrial Internet of Things (IIOT) devices use smart sensors to collect and analyze data instantaneously. This data allows industrial devices to make decisions and act on them, which optimizes quality, workforce, and engagement.

Step 5: Security
Increased interconnectivity also increases security vulnerabilities. Security risks include software hacks and system manipulation— both of which can cause breaches in customer data and bring operations to a standstill. Investing in cybersecurity and IIOT systems that provide regular monitoring and detection in the event of malware infection is crucial to keeping your information safe.

Benefits of Edge Computing

Staying up and running: Edge computing can benefit many industries, especially those that operate remotely. Because retail companies generally have more than one location, edge computing works well from both point of sale and security perspectives. Like retail companies, financial institutions, including banks, also have multiple branches and can benefit from edge computing.

Quick processing: The Internet of Things provides massive amounts of data. Because the data generally needs to be analyzed instantly in cloud applications, communication must be fast in order to be efficient.

Cost savings: Edge computing can reduce organizational costs by using smaller deployments. This helps businesses avoid building infrastructure at every site.

Getting Up to Speed

Prepare your organization for edge computing integration. Designed to train your entire team to support edge computing, IEEE Introduction to Edge Computing is an online five-course program. The on-demand courses included in this program are:

• Overview of Edge Computing
• Practical Applications of Edge Computing
• Research Challenges in Edge Computing
• Designing Security Solutions for Edge, Cloud, and IoT
• Tools and Software for Edge Computing Applications

To learn more about getting access to these courses for your organization, connect with an IEEE Content Specialist today.

Interested in the course for yourself? Visit the IEEE Learning Network (ILN) to learn more.

 

Resources

(23 August 2019). What Is Edge Computing? Forbes.

(16 September 2019). The analyst projects the global edge computing market to grow from USD 2.8 billion in 2019 to USD 9.0 billion by 2024, at a Compound Annual Growth Rate (CAGR) of 26.5%.Yahoo! Finance. 

Conboy, Alan. (17 September 2019). What’s next for the Internet of Things? Going to the edge. IoT News

(16 September 2019). Five steps to successful edge integration. It Web.

Depending on how many of the 30 billion Internet of Things (IoT) devices forecast for global deployment by 2020 rely on the cloud, managing the deluge of IoT-generated data makes proper processing seem near impossible. Traditional cloud computing has serious disadvantages, including data security threats, performance issues, and growing operational costs. Because most data saved in the cloud has little significance and is rarely used, it becomes a waste of resources and storage space.

In many instances, it would be incredibly beneficial to handle data on the device where it’s generated. That’s where edge computing comes in. Edge computing helps decentralize data processing and lower dependence on the cloud.

Edge computing has several advantages, such as:

• Increasing data security and privacy
• Better, more responsive and robust application performance
• Reducing operational costs
• Improving business efficiency and reliability
• Unlimited scalability
• Conserving network and computing resources
• Reducing latency

 

Edge Computing Use Cases

Prime use cases, which take full advantage of edge technology, include:

Autonomous Vehicles: The decision to stop for a pedestrian crossing in front of an autonomous vehicle (AV) must be made immediately. Relying on a remote server to handle this decision is not reasonable. Additionally, vehicles that utilize edge technology can interact more efficiently because they can communicate with each other first as opposed to sending data on accidents, weather conditions, traffic, or detours to a remote server first. Edge computing can help.

Healthcare Devices: Health monitors and other wearable healthcare devices can keep an eye on chronic conditions for patients. It can save lives by instantly alerting caregivers when help is required. Additionally, robots assisting in surgery must be able to quickly analyze data in order to assist safely, quickly, and accurately. If these devices rely on transmitting data to the cloud before making decisions, the results could be fatal.

Security Solutions: Because it’s necessary to respond to threats within seconds, security surveillance systems can also benefit from edge computing technology. Security systems can identify potential threats and alert users to unusual activity in real-time.

Retail Advertising: Targeted ads and information for retail organizations are based on key parameters, such as demographic information, set on field devices. In this use case, edge computing can help protect user privacy. It can encrypt the data and keep the source rather than sending unprotected information to the cloud.

Smart Speakers: Smart speakers can gain the ability to interpret voice instructions locally in order to run basic commands. Turning lights on or off, or adjusting thermostat settings, even if internet connectivity fails would be possible.

Video Conferencing: Poor video quality, voice delays, frozen screens— a slow link to the cloud can cause many video conferencing frustrations. By placing the server-side of video conferencing software closer to participants, quality problems can be reduced.

Further Enhanced Security

Although edge computing is a sensible alternative to cloud computing in many instances, there’s always room for improvement. According to “Reconfigurable Security: Edge Computing-Based Framework for IoT”, a paper published by IEEE Network, existing IoT security protocols need improvement.

A possible solution to better secure IoT-generated data is an IoT management element called the Security Agent. This new piece would use routers and other near-edge boxes to manage the computing the IoT device could not take on. In addition to being more secure, it’ll simplify the management of keys. The Security Agent box has the capability of running copious sensors that are difficult to access. The researchers’ state that if the needed authentification is not completed quickly, IoT applications will fail.

Getting Up to Speed

Designed for organizations investing heavily in this critical technology, IEEE Introduction to Edge Computing is a five-course program designed to train your entire team to support edge computing. The online, on-demand courses included in this program are:

• Overview of Edge Computing
• Practical Applications of Edge Computing
• Research Challenges in Edge Computing
• Designing Security Solutions for Edge, Cloud, and IoT
• Tools and Software for Edge Computing Applications

To learn more about getting access to these courses for your organization, connect with an IEEE Content Specialist today.

 

Resources

Aleksandrova, Mary. (1 Feb 2019). The Impact of Edge Computing on IoT: The Main Benefits and Real-Life Use Cases. Eastern Peak.

Nelson, Patrick. (10 Jan 2019). How edge computing can help secure the IoT. Network World.

Caulfield, Matt. (23 Oct 2018). Edge Computing: 9 Killer Use Cases for Now & the Future. Medium.

Talluri, Raj. (24 Oct 2017). Why edge computing is critical for the IoT. Network World.

 

With the constant growth of connected devices, as well as persistent phone and tablet use, traditional centralized networks may soon be overwhelmed with traffic. Gartner predicts that 25 billion connected devices will generate unprecedented amounts of raw data by 2021. This problem will demand next-level responsiveness and reliability— and it’s just two years away.

Edge computing promises to address the impending data surge with a distributed IT architecture that moves data center resources toward the network periphery.

Meeting Needs

Edge computing topology can reduce latency for time-sensitive applications, support IoT performance in low bandwidth environments, and ease overall network congestion.

• Latency: By virtue of physical proximity, time-to-action drops when data analysis occurs locally rather than at a remote data center or cloud. Because data processing and storage will occur at or near edge devices, IoT and mobile endpoints can react to critical information in near real-time.
• Congestion: Edge computing can also ease the growing pressure on the wide-area network. This can improve efficiency and keep bandwidth requirements in check This is a significant challenge in the age of mobile computing and IoT. Instead of overwhelming the network with a constant flood of relatively insignificant raw data, edge devices can analyze, filter, and compress data locally.
• Bandwidth: Edge computing topology can support IoT devices in environments with unreliable network connectivity. Such environments include cruise ships, offshore oil platforms, rural agricultural plants, remote military outposts, and ecological research sites. Even with a hit-or-miss connection to the cloud, local compute and storage resources can enable continuous operation.

Edge Challenges

The more intelligent an edge device, the more intensive its configuration, deployment, and maintenance requirements. Organizations will need to decide on a case-by-case basis if distributed computing benefits (like cheaper WAN connectivity) justify the increased overhead at the network’s periphery. Gartner Research Director Santhosh Rao cautions that the costs associated with deploying and operating edge computing technology can pile up quickly. Although edge computing comes with many benefits, IT leaders will have to make sure a they outweigh its costs.

Security is also a major concern associated with edge computing. Some IT professionals worry that a decentralized computing architecture will make a network more vulnerable to attack by creating excess backdoor entry points. However, other people argue that placing an edge-computing gateway between network endpoints and the internet can actually improve security. Because more data will be processed and stored locally, travel to and from the cloud will be reduced.

Despite uncertainties, analysts expect organizations will increasingly rely on edge computing technology in the years to come. According to Rao, just 10% of enterprise data was created and processed outside of a centralized data center/cloud in 2018. He predicts that number will climb to 75% by 2025.

Introduction to Edge

Prepare your organization for the future by training your entire team to support edge technology now. IEEE Introduction to Edge Computing is a new five-course program designed for organizations investing heavily in edge. Courses include:

• Overview of Edge Computing
• Practical Applications of Edge Computing
• Research Challenges in Edge Computing
• Designing Security Solutions for Edge, Cloud, and IoT
• Tools and Software for Edge Computing Applications

Connect with an IEEE Content Specialist for access today.

 

Resources

Irei, Alissa. (Apr 2019). Understand why edge computing technology matters. SearchNetworking.

Jones, Nick. (Sept 2018). Top Strategic IoT Trends and Technologies Through 2023. Gartner.