Edge Computing Sustainability
Sustainability

Edge Computing: Key to a Sustainable Future

Data centers require plenty of electricity, which typically comes from a fossil fuel source that unleashes carbon emissions into the air. However, now there is growing attention on how to make big data more sustainable and less harmful to the environment. Here’s a look at how edge computing can contribute to both environmental and economic sustainability.

First off, however, let’s take a quick look at the difference between edge and cloud as there can be some confusion between the two.


Edge vs. Cloud

With edge computing, you mainly need devices that are powerful enough to process and store data. Cloud computing differs in the sense that all the data is processed and stored at a large data center, instead of on multiple connected devices.

Devices themselves do not define whether they are categorized as part of edge or cloud computing. What defines an edge network is how devices access and distribute data. While cloud computing is centralized at a data center, edge computing is decentralized and occurs throughout the network on edges that connect with smartphones and other devices. In this sense, edge computing is more of a topography than a technology.

Ultimately, you should not have to decide between either the edge or the cloud. Each type of data delivery method has its pros and cons, so think of them more as options than rivals. It’s possible to use a hybrid infrastructure that utilizes both cloud and edge computing. The cloud is where to store more frequently needed data while the edge is useful for quicker access.

Autonomous vehicles are useful as a hybrid solution. They contain local data processing components and can be used with the cloud for remote monitoring or remote control purposes. Self-driving cars are equipped with video cameras and radar that collect data, which can be stored within the vehicle components.

Meanwhile, edge computing devices are being used alongside highways to monitor traffic. The data is sent to a nearby facility that houses the data. The facility then can alert local authorities when hazardous objects or debris are detected in the roadway. It can also send alerts to electronic signs on the highway, warning drivers of roadway conditions ahead.

Now that you have a better understanding of edge computing and the cloud, let’s dive into how edge computing impacts environmental and economic sustainability.


More Sustainable IoT Projects

The expansion of networks and devices on the internet raises various questions about efficient transmission and storage of data. It doesn’t make sense to send all data to the cloud because there’s a vast amount of data that isn’t worth storing or takes up too much server space that could be better allocated.

Data centers tend to be large buildings that take up an entire block to handle a wealth of data. These large facilities generated about 2 percent of global CO2 emissions, which is similar to the aviation industry. A more efficient solution for data storage is edge computing, which keeps data close to its source.

Now that businesses are increasingly relying on big data to streamline their operations, the need for edge computing is growing. Edge computing is also a sustainable solution because it reduces clutter on a network by moving data directly from one node to another rather than making a much longer trip to the cloud.


Reducing Distance and Traffic

Edge computing reduces the distance between nodes that communicate data. It also reduces the amount of traffic that travels across the network, which allows you to conserve bandwidth or use it for other purposes. The less you need to send data to the cloud, the more you can cut costs and reduce energy consumption.

Since resources on edge devices are restricted, each device should be optimized for efficiency to save on energy while still having sufficient processing power. Here are a few key ways in which the efficiency advantages of edge computing contribute to sustainability:

  • Remote work – Both edge and cloud computing allow for data exchange capabilities to be useful for remote work. At the moment, the cloud has facilitated remote work, which has helped cut carbon emissions in terms of reducing physical commutes that cause the release of tons of CO2 due to traffic congestion.
  • Air quality – IoT data can help improve indoor air quality and reduce harmful emissions to the outdoor environment. Edge devices have also been instrumental in cutting energy and other operational costs.
  • Smart city development – The placement of IoT devices throughout a smart city infrastructure is reducing traffic congestion, emissions, and idle wait times. Smart parking meters have also allowed people to plan trips more efficiently with less driving around and wasting gas searching for places to park.
  • Faster response times – The combination of sensors, satellites and drones equipped with edge computing capabilities is helping utilities respond faster to energy disruption issues. Additionally, the expansion of software-based detection systems integrated with AI technology is helping analysts detect natural disasters, like wildfires, more rapidly.
  • Reversing climate change – Collecting digital intelligence at network edges can play a major role in reversing climate change. Decision-makers can be alerted about environmental harm via two-way smart grids. Utilities can already automatically shift to renewable energy sources when dropouts occur in the main grid.

An edge database is also particularly useful for specific purposes, such as independent operations that don’t rely on an internet connection. It’s also helpful for facilitating high-frequency data or accessing historical data. Additional edge devices can be used for a system that lacks the capacity for data storage. The devices might also contain machine learning software that can analyze vast amounts of data.


Shift to the Edge

Prior to the rise of edge computing in recent years, about 90 percent of enterprise data moved through the cloud. According to technology researcher Gartner, only about 25 percent of business data will be cloud-based in the coming years. Gartner projects that most data will be stored on the device of its origin, which points to the definition of edge computing.

Edge computing needs the same but scaled-down resources as a cloud-based data center. That means the device that creates and stores data needs an operating system, database, network layer and cybersecurity. The core component of edge computing is an edge database, which requires fast local data availability and decentralized data flows.

A major reason for many companies adopting edge computing is that by 2025 over 30 billion IoT devices are expected to populate the internet. These devices will account for the generation of 4.6 trillion GB of data per day. The combination of bandwidth limitations and exponential data expansion will make cloud computing less practical for big data organizations.

Up until recently, most users of edge computing were large manufacturing factories and utilities. The best example of an edge computing device is a car equipped with modern sensors. The car draws data from multiple sensors that must be synchronized. Cars are not dependent on the cloud but can integrate with the cloud for certain functions.

A GPS device used in cars for geolocation essentially involves edge computing that exchanges data between a satellite and the car. Another example of edge computing is when a wearable medical device at a patient’s home communicates directly with a hospital.


Future of Edge Computing’s Role in Environmental Sustainability

Businesses should expect edge computing to become more prominent the deeper society dives into big data. The tech sector is already on the radar of environmental activist groups to do something about data centers contributing to carbon pollution. This is because both the population and energy consumption levels are expected to grow enormously over the next few decades.

Technology providers are becoming more aware of the environmental issues surrounding mass data transmission. One way technology providers can address and help overcome these upcoming challenges is to encourage widespread adoption of edge computing.


Conclusion

Interest is growing in the sustainability qualities of edge computing, particularly for companies that generate and transmit a high volume of data. While the cloud serves important purposes, it doesn’t need to be the hub for all data. You can conserve bandwidth by using data collection devices that handle processing and storage, which is the essence of edge computing.

Read More
Edge Computing Security Concerns
Information Technology

How to Deal with Edge Computing Security Concerns

The rise of edge computing, particularly in smart cities and large facilities, has led to new approaches to securing networks and devices. The rapid digitization of industrial machinery in recent years such as in self-driving cars has opened up concerns about machines getting hacked. Here are ways security is improving for edge computing.


Security for Edge Computing

Due to the increasing trend toward big data collection in a smart infrastructure, it's important for organizations to move away from traditional blanket models of data protection in favor of securing every device. Demand is growing among large operations for data to be processed at network edges rather than cloud-based data centers.

More and more IoT devices that store data are populating networks as a solution to avoid network latency. But with more devices spread across a network, there's a growing need for more robust security.

Sending large data to the cloud can eat up plenty of bandwidth even as many companies embrace the faster and wider distribution benefits of 5G. Edge computing has been a solution to reduce network congestion as the data is processed at or near the IoT device. Since many devices are interconnected, a hacker can spread malware throughout a system by penetrating one IoT device.

Encryption is a major cybersecurity layer that should be considered for all devices on an edge network. Conducting a network audit including a review of configurations helps pinpoint vulnerabilities that require immediate attention. Once devices are activated, they need to be updated with software patches on a regular basis. Other ways to protect edge networks and devices involve certificates and multi-factor authentication.

blank

Want to learn more about edge computing? Watch the replay of our Living on the Edge webinar where our speakers break down the complexities of edge computing and provide strategies for successfully deploying edge solutions.

Watch Now


Using the SASE Strategy

Adopting secure access service edge (SASE) infrastructure helps strengthen network security for users of wide-area networking (WAN) to access the cloud. SASE gives organizations a greater degree of control over complex networking, particularly with the help of automating various tasks in the background. It also provides network monitoring capabilities. Although less than 1 percent of organizations used SASE strategies in 2018, Gartner has forecasted a jump to 40 percent by 2024.

Some effective SASE strategies include cyber threat detection software, network segmentation and defense-in-depth (DiD) network design. Detecting threats and intrusions is a crucial step in countering a cyberattack and is the most commonly adopted form of edge computing security. Segmentation involves dividing a network into segments that are independent of each other, making a network-wide breach more improbable. DiD network sets up zones within an edge network based on trust levels.


Securing Edge Computing Devices

Edge devices with limited computing capacity pose security risks. Without a certain level of computing power, edge devices may not be reliable for collecting data accurately or securely. Placing too much stress on edge devices raises security risks. Setting up firewalls at the network edge is one way to secure edge devices, allowing for faster detection of suspicious activity.

The DiD approach to traditional network security provides multi-layered security controls to protect data hidden at the back-end. The concept of backup security layers allows a network to be more resilient against an attack. But edge computing requires more dynamic security controls. Gartner has advocated SASE as a stronger security solution for edge networks.


Turning to Standardization

Many businesses are embracing edge computing out of necessity due to the growth of big data, which has raised the bar on competition in the global marketplace. This shift toward big data as an integral part of a business model is causing businesses to redefine their business models and infrastructure designs.

One way to deal with the challenges that edge computing presents involving network complexity is to adopt standardization of security protocols and processes. You'll be able to respond to networking issues quicker. Standardizing security on your cloud platform is easier to manage and allows for faster data transmission.


Industries Focused on Securing Edge Computing

Key industries that are venturing into edge computing are smart cities, utilities, manufacturing, healthcare, automotive and telecommunications. These industries were also the first to embrace smart technology, which helped escalate the rise of IoT devices. Meanwhile, supply chains using 5G have less to worry about as far as network security.

Any operation that involves a vast number of IoT devices for data collection is potentially raising security risks. The key to protecting such networks is using high-quality threat intelligence, detection and response capabilities.

Edge networks should also embrace a zero-trust architecture, in which each device that's allowed on the network has limited access to just necessary resources for the specific user. This approach ensures that one vulnerable device doesn't cause the whole network to become infected with malware since employee error is a leading cause of breaches.

Large entities using edge computing must adopt distributed resiliency plans to counter network disruptions. That means creating redundancy that replicates data from all devices across the edge network. Distributed resiliency allows an edge network to switch to backup resources when the primary network experiences interference or downtime.


Data Encryption for Edge Devices

Some people might believe that the more complex a network is, the harder it is for hackers to penetrate. In reality, the more sensors you load on a network, the more opportunities cybercriminals have to hack the devices. That's why it's crucial that each device has its own encryption capabilities.

One of the strongest forms of edge computing security is to encrypt sensitive data as it's processed. The data is then decrypted when it's accessed by an allowed device. A system called trusted execution environments (TEE) helps overcome the vulnerabilities of data exposure before, during, and after data processing.

In the future, large organizations are expected to use blockchain technology as a cybersecurity layer. Blockchain already utilizes encryption as its base for security, so it's likely to become more prominent in the coming years for factories and other facilities relying on edge networks.


Conclusion

While not all businesses need to consider edge computing, larger entities that generate vast data should embrace it. Any organization adopting edge computing should also use digital security methods that are suited for edge environments rather than traditional cybersecurity approaches. Encryption plays a huge role in protecting data on edge devices as well as the devices themselves.

Read More
Cutting Commercial Waste
Sustainability

Why Businesses Need to Adopt Green Tech Solutions

The concept of environmental protection is no longer reserved for a niche group of scientists, professors and activists. The demand for green tech solutions has expanded on both a local and global level due to awareness of climate change and how pollution impacts health. Here's a look at what green technology is and how it contributes to a stronger business model.


Evolution of Green Technology

Green technology comprises systems and equipment that help reduce greenhouse gases in the environment. The earliest signs of green technology appeared in the early nineteenth century as the industrial revolution was changing the world. During the rise of factories, scientists began to study the negative effects of coal-burning plants on the environment.

In the late nineteenth century, an environmental movement developed among people who loved the great outdoors and sought to preserve nature. From this movement led by John Muir, co-founder of the Sierra Club, emerged views on wilderness preservation and conservation of natural resources.

By the 1960s, America had coast-to-coast highways full of traffic fueled by the oil industry. During this time scientists became more aware of dangers related to CO2 pollution caused by the burning of fossil fuels. Rachel Carson's book Silent Spring woke up many politicians that chemical pesticides used in agriculture were linked to cancer and other illnesses.

In the decade that followed, the Environmental Protection Agency (EPA) was created to study pollution and propose solutions for a healthier environment. The EPA set goals on reducing toxins and waste while aiming for cleaner air and water. In the 90s, there was a growing demand for EVs but oil interests fought the development until the emergence of Tesla in the 2000s. Now EV-charging stations are expanding across the United States.

Green tech is more than a trend, it's part of the paradigm that's taking over. Every business faces financial challenges that include energy costs. Keeping costs under control is now what many investors want to see, as sustainability is becoming a central theme in business. As environmental awareness grows, so does the demand for green tech solutions.

The shift to earth-4 0

Check out the recording of our webinar "The Shift to Earth 4.0", where our panel of experts shared their knowledge and perspectives on the state of the environment and how Industry 4.0 will impact the earth.

Watch Now


Core Green Tech Industries

At the core of green tech development are green energy producers, manufacturers and recyclers. Here are the main green tech solutions blossoming in the 2020s:

  • Renewable Energy: Solar and wind are the leading forms of renewable energy. Utility companies have embraced these clean energy solutions for backup resources and cost-cutting.
  • Electric Vehicles (EVs): Only a small percentage of Americans drive electric cars in the 2020s, but the number is expected to grow exponentially in the next decade. EVs are emissions-free and can go 300 miles on a single charge, which can be powered by solar panels.
  • Sustainable Farming: The organic food market has grown significantly in the last few decades as consumers want less exposure to toxic pesticides. Organic farming is part of sustainable agriculture, which includes reducing water waste and maximizing eco-friendly solutions.
  • Recycling: Almost all materials used for making consumer products, including e-waste, can be recycled by a recycling center. Metals, plastics, wood and glass are commonly reused to make new products. Recycling can be a solution to supply shortages as well as a strategy to reduce waste in landfills.

Other new sustainable solutions are emerging, such as carbon capture technologies that remove greenhouse gases from the environment. Digital transformation and the proliferation of IoT devices has allowed professionals to monitor environmental activity with the goal of reducing harmful pollutants.


Escalating Use of Green Tech

Green tech, also known as clean tech, is gaining in adoption among many different types of businesses. Part of this push toward green tech comes from local, state and federal governments with incentives to go green and stricter laws on pollution. California has mandated an end to selling new gas-powered vehicles in the state next decade, which has forced several automakers to develop EVs.

The supply chain crisis during the pandemic caused many businesses to rethink their logistics and seek more sustainable solutions in warehousing and transportation. Businesses are widely embracing the notion of well-being as a necessary component of the workplace, which means reducing indoor air pollution with modern HVAC systems.


Why Solar Energy is Here to Stay

Solar energy is now the least expensive form of alternative energy, as reported by the International Energy Agency in a 2020 report. Furthermore, solar power is now the cheapest form of electricity in history. The reason it's safe to say solar is here to stay is because the sun is expected to keep shining for millions of years. Continuous improvements in cost efficiency and energy efficiency make solar impossible to ignore as all businesses look to cut energy costs.


Investing in Green Energy

Environmental, social, governance (ESG) scores are now on the radar of the investment community. While definitive standards are still needed for ESG scores, the point is that an increasing number of investors are concerned by how companies use resources. Companies that create massive pollution often face massive lawsuits, while those going green get better press.


Conclusion

Green tech is more than a trend, it's part of the paradigm that's taking over. Every business faces financial challenges that include energy costs. Keeping costs under control is now what many investors want to see, as sustainability is becoming a central theme in business. As environmental awareness grows, so does the demand for green tech solutions.

Read More
Edge Computing in 2022
Information Technology

Edge Computing in 2022: Trends, Potentials, & Challenges

What’s the big deal about edge computing? Does it have an advantage over cloud computing? Can it offer anything that the cloud can’t? What’s the point of having an edge when you already have a cloud? These are just some of the questions we will answer in this article.

Related: Why Edge Computing Is Gaining Adoption Among Big Data Companies

Edge Computing Goes Mainstream in 2022

Edge computing is gaining traction as a powerful addition to cloud computing. Unlike cloud computing, where all data processing takes place in centralized servers, usually in a different location from where the application is being used or accessed, edge computing brings all processing closer to users.

It can be applicable in several different use cases. Still, its main advantage is that it allows users to process data closer to the source without being dependent on the cloud.

Everything from IoT devices to self-driving cars uses edge computing to identify and respond quickly to certain events.


What Is Edge Computing?

The term “edge” refers to any location outside traditional data centers in which data processing occurs. It features low latency, closer proximity to users and devices, and local processing capabilities for IoT applications.

Edge computing environments can be on-premise or smaller regional data centers located nearer to end-users. They can process data in real-time without relying on centralized cloud platforms for resources.

As per Gartner’s prediction, “75% of enterprise-generated data will be processed outside the cloud or traditional data centers by 2025.” This means enterprises should prepare for a decentralized IT environment with distributed computing power across multiple locations.

Keep reading: The Differences Between Cloud and Edge Computing

Top Edge Computing Trends That Will Dominate in 2022

Data Explosion

The amount of data generated worldwide is growing exponentially. The IDC predicts that within the next few years, there will be 175 zettabytes (175 trillion gigabytes) of data created every year. This growth is driven by the rise of IoT devices, providing businesses with more data and insights than ever before. This data helps organizations improve their processes and customer experiences.

While cloud computing has helped companies benefit from the power of this data, it’s not enough. According to NVIDIA, sending all this data to the cloud takes too much time — up to a tenth of a second. A tenth of a second might not seem like much, but autonomous vehicles need to make decisions within milliseconds if they want to avoid crashes. That’s why edge computing is growing in popularity: It enables businesses to quickly access data from IoT devices without relying on cloud computing alone.

blank

Want to learn more about edge computing? Watch the replay of our Living on the Edge webinar where our speakers break down the complexities of edge computing and provide strategies for successfully deploying edge solutions.

Watch Now


Expanding IoT

The Internet of Things (IoT) has been the defining trend of the last decade. Gartner predicts that by 2025, there will be 75 billion connected devices in use worldwide. This effectively means that everything from our streetlights to our cars to even our fridges will soon be connected to the internet.

The edge computing market is the best way to handle this massive expansion of connected devices. Edge computing allows for data processing at the source, reducing bandwidth requirements and ensuring faster network speeds for billions of users. This is especially important as more and more devices are added to the IoT networks every year.

5G and Edge Computing

With every new generation of mobile technology, data speeds increase exponentially. According to Nokia, 5G networks are 100 times faster than 4G LTE networks and can simultaneously support ten times more devices. In a nutshell, 5G will connect everyone on the planet and make lightning-fast data transmission possible for all devices.

Suffice it to say, edge computing will be instrumental in making this a reality. With more users connecting at once, it’s going to be essential that we have distributed cloud platforms available for processing data at the source.

Autonomous Vehicles

Edge computing is already seeing massive growth in the automotive industry. The tech will fuel the rise of autonomous vehicles (AVs).
The reason for this lies in AVs’ need for a low latency connection. They will also require real-time insights into their surroundings. These include road conditions and other vehicles on the road. All of this can only be achievable with edge computing.

As a result, edge computing will help make AVs a reality by 2022. It will ensure that the vehicles are safe and efficient on the road.

Read more: The Shift to Digital-First Retail

How Can Edge Help Businesses?

Edge computing is the future of data centers. It enables real-time analytics, increases speed, and reduces latency. The technology is already in use across several industries, such as retail, healthcare, and finance.

For example, it can help retailers in the following ways:

Real-time analysis – Edge computing allows stores to capture customer data and analyze it on the go. This information can serve to improve product selection and inventory management.

Speed – Edge computing allows retailers to process data faster than ever before. This helps them streamline their operations and offer customers a better shopping experience.

Latency reduction – Edge computing reduces latency by routing traffic from central servers to local ones or even directly through the cloud. This ensures that customers have access to the information they need when they need it without delays or interruptions due to congestion on the network (which helps reduce costs).


Challenges to Edge Computing

Here are the top challenges of edge computing and how your organization can overcome them:

Security

Edge computing requires a greater focus on security than most organizations are used to. The more places you have data, applications, and hardware, the more potential points of vulnerability there are to hackers. In other words, security becomes even more important with edge computing than before. Organizations need to prioritize security at every step when implementing edge computing, including in their vendor contracts.

Connectivity

For some applications, network latency — the delay between sending and receiving data — doesn’t matter much. For others, it’s critical. Suppose an application will be used at the edge of a network. In that case, it’s important to understand how that application will be affected by inevitable delays in transmitting data over long distances.

Some applications that work well on the cloud might not work as well at the edge because of latency issues. Until 5G equipment becomes available for everyone, this will be an ongoing problem for any organization attempting to create applications for the edge of networks.


Takeaway

Edge computing is going mainstream, and discussed above are the top trends, opportunities, and challenges to watch out for in 2022.

Read More
Edge Computing Gaining Adoption
Information Technology

Reasons Why Big Data Companies Are Turning to Edge Computing

The one thing technology experts can accurately predict in the coming years is the continued growth of big data via IoT devices. These data-generating sensors have become the key for operational optimization, as they can detect system vulnerabilities in real time. Here are reasons why certain businesses are choosing edge computing.


What Is Edge Computing?

Edge computing means data processing takes place at or near the data source instead of taking a long journey to the cloud before it's processed. When data has to travel far, packets can get scrambled, which causes latency. When data doesn't have to travel far, it's quicker and easier to access. Edge computing gets its name from facilitating computing at the network edge, which includes endpoints such as smartphones, desktops, notebooks, etc.

So instead of data moving from a sensor to a data center then to the end user, it bypasses the data center and goes directly to the endpoint. Any device that has its own computing capacity can play a role in edge computing.


Main Benefits of Edge Computing

With edge computing, you'll be closer to the data, making latency less likely. Ultimately, it allows you to respond to real-time data with agility. Aside from speed and efficiency, such as real-time data access, major benefits of edge computing include privacy and reliability. By keeping data processing at the network edge instead of transmitting it to the cloud, there's less chance the data will be intercepted by nefarious invaders.

An edge platform gives you potentially higher data computing performance than a cloud-based system. It also provides greater security if each device is configured properly, and its data storage is segmented. The reason edge computing provides better privacy is because you're in control of the data instead of an off-site data center where data can be monitored by unknown individuals.

Edge computing is also particularly useful for companies that need data instantly. Even delays of a few seconds via the cloud can be troublesome to certain companies. They can further be empowered by the concept of an "edge cloud" in which several remote data centers are located near the sources of data generation. Since there are no rules about where to place edge devices on a network as long as they're close to the source, there's room for network flexible configurations.


Industries Using Edge Computing

While various industries have embraced edge computing in recent years, some common purposes exist that attract big data companies. Many large firms within the below sectors have gravitated toward real-time edge devices as part of their digital transformation and support for the IoT revolution.

  • Automotive - Most new cars contain several dozen computing devices that monitor vehicle performance. Autonomous vehicles particularly are equipped with sensors that have computing capabilities. Automated machinery can be used to transport physical items in a factory or monitor street activity to collect data on traffic conditions.
  • Energy and Utilities - Power plants need edge computing due to the massive amount of data they monitor. IoT sensors placed at network edges allow for faster adjustments to improve production processes. Both energy and utility companies have been leaders in adopting smart infrastructures and edge computing.
  • Manufacturing - Assembly machines that make parts may include cameras that track quality assurance analytics. IoT devices can monitor performance for different phases in manufacturing. The data can be monitored at endpoints and sent to the cloud. Adding machine learning software to the equation provides analysts with a wealth of valuable reports at their fingertips.
  • Logistics - Both warehouses and transportation companies have utilized edge computing while integrating it with their cloud models. Warehouses can use edge computing to locate specific products quickly among vast inventories. Trucks and other delivery vehicles are equipped with sensors that monitor vehicle performance and driver behavior. The data can be sent to a database via wireless transmission while triggering alerts to drivers.
  • Agriculture - Farms can now be populated with IoT devices to measure various outdoor growing conditions. They can collect data on temperature, moisture, and soil nutrients without sending it to the cloud. Edge analytics via 5G networks can help farmers more efficiently monitor and predict crop development.
  • Retail - Consumers are learning about the effects of edge computing via virtual experiences and augmented reality at physical stores. Retailers benefit from touchless checkout terminals, for example, that make shopping more convenient. Some retailers have also already started using robots that assist customers with store navigation.
blank

Want to learn more about edge computing? Watch the replay of our Living on the Edge webinar where our speakers break down the complexities of edge computing and provide strategies for successfully deploying edge solutions.

Watch Now


5G Will Enhance Edge Computing

The introduction of 5G helps strengthen edge computing in numerous ways. Have you heard of 5G network slicing? It involves segmenting a shared network for different groups of users, hardware, and software. Essentially, one group's network slice does not affect another slice. Network slicing can be used for various reasons, such as separating different organizational departments.

The wider bandwidth of 5G allows for the expansion of big data and is an important key to a hybrid model that combines cloud and edge computing. This model can potentially turn a local business into a global operation overnight since 5G provides broader data transmission across longer distances.

In a retail store, for instance, different network slices can be used to support different environments. For example, one slice might be for customer experiences with augmented reality while another can be for internal office purposes. Each slice is self-contained and has no impact on other slices. So, if a hacker penetrates a slice, it doesn't mean they can access other slices.


Outlook for Edge Computing

Since edge computing is a viable solution for reducing big data congestion, it will likely be embraced by large entities for years to come. The more IoT devices expand across a business network, the more an organization should consider edge computing. Security can be an issue when selecting edge devices, but with 5G network slicing, you'll have very robust data protection.

Additionally, even though the cloud is a cost-cutting phenomenon, costs can still add up the more data you store in the cloud. In that sense, edge computing provides cost efficiency for big data companies. Non-critical data does not need to be stored on a cloud server. The more non-critical data you keep on edge devices, the more money you can save on cloud storage.

Placing a company's workload near the network edge where data is created has many benefits that save time and money. Data tends to originate from remote equipment rather than the cloud, although the cloud is still very useful for storage and computing. Overall, edge computing is becoming more in-demand by businesses that need to utilize real-time data.

Read More
Cloud and Edge Computing Differences
Information Technology

Cloud and Edge Computing: What Are Their Differences and Similarities?

The concept of data transmission efficiency is growing in importance now that big data has become a big issue, thanks to the spread of IoT devices. Many companies are deciding between cloud computing and edge computing as a path to future sustainability. Here's a look at the differences between these two popular types of data management.


Cloud vs. Edge

IT industry analysts project that 75 percent of enterprise data will involve edge computing by 2025. Cloud computing, in which data is computed at a private or third-party data center, is the older method, while edge computing is newer and involves computing at network edges. The key difference is physical distance between the data source and its endpoint device.


Cluttered Bandwidth Issues

Bandwidth challenges are at the forefront of the emerging business technology landscape. In many ways, 5G will be the solution for larger organizations to transmit vast endless data from point A to point B. But a large percentage of businesses will try to delay 5G adoption to cut costs while monitoring its development.

Even with 5G, there's still a need to make data transmission as efficient as possible. Edge computing contributes to greater bandwidth efficiency by reducing the distance data must travel to be processed. In this sense, the ideal location for computing is within the device itself, but that requires more processing power. By narrowing the gap in which data must travel from storage to devices, there will likely be fewer latency problems.


Anytime, Anywhere Data Access

The strength of cloud computing is that it allows users to access data from any location in the world on any device. The computing is conducted at a centralized place either on a local or remote machine rather than the source that feeds the data to the server. As data began to blossom wildly in the cloud, the concept of edge computing emerged as an alternative.


Weighing Cloud vs. Edge Computing Differences

Both cloud and edge computing serve valuable purposes. Online payment processing was made possible by the cloud's centralized data storage. Cloud services also redefined the roles of tech giants such as Microsoft, Amazon, and Google. Additionally, many cloud software companies began offering their applications through cloud subscriptions to replace hardcopy media such as CDs and DVDs. With so many different applications, cloud services are now at the heart of many online businesses.


Cloud Advantages

Deciding between cloud and edge computing comes down to your business operations and goals. If your office space is limited to the point of restricting the number of nodes for doing business, the cloud can offer an efficient solution. Cloud platforms such as Amazon Web Services and Microsoft Azure, for instance, have made it easier for companies to allow remote work opportunities for their employees without requiring a software license for every computer.

Because the cloud has also led to cost-savings on multi-user software licensing, it was designed to serve many users at once at an affordable cost. A business can now exist completely in the cloud, meaning you don't have to store data on your own computers. Through various cloud services, you can cut upfront hardware and software costs, which is the massive appeal of cloud computing.

Moreover, through the cloud, you can access endless Software-as-a-Service (SaaS) platforms, which would otherwise take up massive space on hard drives. This solution makes robust industry software scalable and affordable. The cloud also reduces the need for an in-house IT team since security and network management are handled by offsite data centers, with exception for local private clouds.


Edge Advantages

Manufacturers, warehouses, and utilities benefit from edge computing due to the vast amount of space these facilities occupy. Imagine stepping into a giant warehouse and being asked to locate a specific product within a large inventory catalog. With edge computing, you can easily do so by using a scanning device that connects with the RFID chip in the product or with a video camera. Edge computing allows you to locate any item in seconds.

Edge computing relies on neither the cloud nor data centers. This model of using connected devices that comprise data processing also saves time and money. The strength of edge computing is that it's more agile than the cloud, allowing for quicker access to data. The cloud can have latency issues if the servers are busy or if the network gets too congested. Problems associated with edge computing, by contrast, are easier to troubleshoot.

Another advantage to edge computing is privacy. While there typically aren't privacy issues with third-party data centers, you still don't know if someone who works there might ever get tired of their job and wants to secretly sell information to cybercriminals. When your company is generating a wealth of valuable data, you don't want the information to get into the wrong hands. In that sense, edge computing reduces privacy risks.


Local Storage Limitations

When edge computing is combined with IoT technology, it allows you to conserve bandwidth on your network. It gives you better control of resource allocation. On the other hand, if your office space has physical limitations, you are better off storing data in the cloud. Certain hardcopy documents may need to be retained but aiming toward paperless solutions via the cloud reduces the need for physical space. Ultimately, the cloud has helped to reduce paper waste via online faxing and several other traditional office functions that have been digitized.


Access to Real-time Data

If you need to store a high volume of data on local servers, consider edge computing. This solution is viable if you expect to deploy hundreds of IoT devices on your network to monitor processes in real time. You'll have much more network visibility and transparency when you are in control of all your own hardware and software.


Collaboration Capabilities

The cloud is a viable solution for seamless online collaboration between multiple team members in different remote locations. The cloud is the answer if you want to build a global company with team members from various parts of the world.


What About Fog Computing?

Fog computing is a hybrid model of edge and cloud computing blended together. It allows for IoT data to be accessed easier in real time as the cloud is stretched to the network edge. This hybrid model, which is ideal for smart cities, allows for connecting with different digital environments without concerns surrounding local storage.


Why It Matters

The future of computing is already active to anyone who runs a network. There are already over 50 billion devices connected to wireless networks. So, imagine how exponentially more the internet will be populated with IoT devices a decade from now. Self-driving cars and robots, for example, will generate a tremendous amount of data just in one hour. Video monitoring systems that collect enormous amounts of data are also expected to proliferate.

The more businesses go digital, the more managers must decide between cloud and edge computing. Each has its pros and cons and can streamline an operation. Your decision will be based on who needs to access data, how fast they need it and the amount of physical space your organization occupies. The future is clear: sensors will be everywhere, and businesses need to plan how to use them efficiently.

Read More
Edge Computing
Information Technology

Here’s Why Smart Cities Should Adopt Edge Computing

The future of smart cities will be built on edge computing infrastructures to maximize data processing. Edge computing is increasingly becoming the solution for managing big data and remote work in smart cities.

As smart cities evolve, a growing amount of attention is being placed on ways to reduce network clutter and latency. Many smart applications require fast or instant response time, such as sprinklers going off when sensors detect fire.

Related: Edge Networking Trends in 2022 and Beyond

Gathering and processing data at the same location is one solution to overcoming the complexity and challenges of big data transmission. By keeping computing at network edges, there’s less chance of latency due to shorter data transmission distance. Instead of sending data to the cloud, data is processed near its source, although it requires a certain amount of processing power to be self-reliant.

Self-driving cars generate enormous data when you consider their numerous cameras. These vehicles typically generate up to 1-5 terabytes of data per hour. That’s why they shouldn’t rely on the cloud, which might have 99 percent uptime, but that doesn’t guarantee it will always be on. Edge computing makes autonomous vehicles much safer than if they relied on data transmission to and from the cloud. The longer the distance data must travel to reach its endpoint, the more chances it can slow down from network congestion. Keeping data transmission as lean as possible is the essence of edge computing for smart cities.

Another advantage to edge computing is that it allows you to respond immediately when situations call for quick decision-making. Smart cities are set up for managers and analysts to review data in real time so that swift decisions can be made on issues such as cybersecurity or resource allocation.

Edge computing allows you to perform analytics at the device that’s gathering data. It’s a more convenient solution for systems that generate large volumes of continuous data, such as video surveillance cameras.


Edge Computing Services

Industries that benefit from edge computing services include law enforcement, military, and aerospace. Any IoT device that generates terabytes of data on an hourly basis may be more efficient in an edge computing infrastructure. Here are some of the many services suited for edge computing:

Sensor tracking – Analysts can monitor sensors locally and restrict interaction with the central server to selected applications.

Employee messaging – Edge networking facilitates an alternative to a web connection when integrated with high bandwidth that allows for employee messaging.

LED Streetlights – Not only do LEDs last longer, they use energy more efficiently and cut costs. Due to this level of sustainability, there’s less need to monitor and transmit large amounts of data long distances.


Independent Sensors

The more you use IoT sensors for automated functions, the more potential to limit heavy data transmission. Sensors that have self-regulating capabilities typically provide greater privacy and security benefits. As long as these sensors have adequate computing power, they won’t be affected by network downtime. Eventually, more and more businesses will adopt 5G, which will contribute to more efficient data transmission when large data loads are necessary.

Keep reading: Understanding the New Direction of Edge Security

Edge networks are particularly important for machine learning capabilities. Ideally, the machines themselves contain a wealth of data, but they can also be connected to the internet for access to data from other resources. All IoT sensors need connectivity for updating and potential data sharing. Smart cities will rely more on artificial intelligence as time goes on, which is more powerful the more it draws from diverse sources.


Always On Requirements

In order for smart cities to live up to their name, they must subscribe to an always on policy. Traffic lights, for example, must always be working to ensure public safety. Much of the data generated by traffic lights can be categorized as surplus data that doesn’t require immediate attention. By deploying edge computing, you are freeing up your network while reducing large loads of data transmission.


How Smart Cities are Evolving

Smart cities have grown out of models established by utilities, manufacturers, logistics firms, and local governments. The need to conserve bandwidth has been a top concern, although 5G will provide plenty more room for mass data transmission. Here are some of the key recent developments that have significantly improved smart cities:

  • Edge computing with powerful processing is now used for roadways and parking lots.
  • Higher quality connectivity with 5G allows for exponentially more IoT devices and data sharing on a network.
  • Containerized microservices can now be distributed across multiple clouds.
  • Applications are developed at a faster rate via DevSecOps, which has built-in automated security.

Another development embraced by emerging smart cities is the hybrid cloud solution. Red Hat, which was recently acquired by IBM, has collaborated with NVIDIA on a hybrid cloud model that combines edge processing and cloud processing. The NVIDIA EGX platform is useful for both edge computing and transmitting data-intensive content such as graphics.

Red Hat provides open source technologies that allow for blending private and public cloud solutions. It can be used to connect a data center with edge sensors placed in buildings, roads and transit stations.

Red Hat’s suite of customized solutions are practical for facilities that have built infrastructures with multiple clouds and a wealth of edge sites. The developer’s OpenShift software allows smart cities to build useful applications. Red Hat Enterprise Linux allows for customization of edge orientation. Meanwhile, IBM Edge Application Manager allows you to manage workloads that interface with up to 10,000 edge devices.

Read more: How Brands use NFTs and AR/VR to Expand and Enhance the Retail Experience

Businesses are empowered by Red Hat solutions because they are able to deploy various IoT sensors for different vendors then transmit to other edge devices within close proximity. A rules engine at the sensor determines which data is processed locally and which data is transmitted to the cloud.


Conclusion

Edge computing continues to evolve in the direction of making big data simple for smart cities. User-friendly administrative dashboards and simple seamless ways to collect or process data are helping drive edge computing to the forefront of modern business.

Read More
Edge Security Detection
Cybersecurity

Understanding the New Direction of Edge Security

The proliferation of smartphones and IoT devices has created a need for edge security, which protects hardware and software associated with a network. It’s specifically used for edge computing, in which computing occurs at a network’s outer edge via the cloud. Here’s a look at how edge technology protects business networks.

Related: Edge Networking Trends in 2022 and Beyond

Cutting Distance to Devices

Edge computing is used by retail chains, bank branches, and other industries that require broad networking based from a local data center or the cloud. The resources can include private, public and hybrid clouds. The massive growth of big data and IoT devices creates bandwidth issues that potentially strain networks, resulting in data latency. This condition calls for shorter distances between the network hub and connected devices. The advent of 5G, which allows for faster and broader data transmission, is part of edge computing.


Explanation of Edge Security

The concept of edge security encompasses various layers such as securing the network’s perimeter to function as a gatekeeper for access to resources. It adds a layer of security via encryption, firewalls, and access control. Another edge security layer involves securing applications that require protection beyond the network layer.

Early threat detection is an important aspect of edge security because it alerts your cybersecurity team to prepare for and impede a surprise cyberattack. It’s imperative to take preventive measures such as identifying specific cyberthreats and defense strategies as early as possible.

Another aspect of edge security is automated patching, which ensures devices are automatically updated when they need to be. The more you keep devices current on security software, the less chance of a sudden devastating cyberattack. Overall, edge security is about identifying and managing vulnerabilities that may exist throughout your edge network, particularly at the endpoints.

blank

Want to learn more about edge computing? Watch the replay of our Living on the Edge webinar where our speakers break down the complexities of edge computing and provide strategies for successfully deploying edge solutions.

Watch Now


What is SASE?

Secure Access Service Edge (SASE) is a term coined by internet researcher Gartner in 2019. It’s an edge security category reflecting the hardware and services needed for edge security. SASE combines comprehensive WAN capabilities with network security functions that allow secure access. It’s essentially a cloud-based solution that combines networking and security efficiency at an affordable cost. In other words, it’s a solution that reflects principles of sustainability.

Keep reading: The Growing Potential of Edge Computing to Transform the Manufacturing Industry

Zero Trust Network Access

Another emerging innovation for IT managers that fits into the edge security puzzle is Zero Trust Network Access (ZTNA), also known as software-defined perimeter (SDP). ZTNA, which grew out of SASE, is a new way to securely access applications and services both locally and in the cloud. It provides a strong defense by denying access to everyone at all network edges except a specific list of devices identified by IP addresses or other identifiers.

SASE bundles ZTNA and other security services with networking solutions such as SD-WAN into a cloud platform. It’s a user-friendly solution for powerful networking and security. The SASE/ZTNA approach has multiple advantages for businesses, which include the following:

  • Easier scalability for companies of all sizes
  • Access based on predetermined IP addresses
  • Increased security by strictly accounting for all network edges
  • More agile and reliable data delivery
  • Cloud-native model has less resource limitations

ZTNA can also restrict access at the application level and limit damage caused by an attacker that penetrates the network. Once a ZTNA service verifies a user, it grants them access to the network via an encrypted tunnel, but only to approved resources for the individual. SASE provides a solid baseline for normal network behavior, making suspicious network activity easier to track. The main concern when using ZTNA solutions is that an unhappy insider might use their access to betray the company. Otherwise, SASE/ZTNA is a solid innovation that deserves consideration.


Keys for Edge Security to Work

Edge security has empowering features, but strategies must be implemented appropriately by the right people. Administrators must be able to see the whole network through a portal. Data encryption needs to happen in storage and while transmitted. Automated monitoring tools are necessary to effectively manage the network. Additionally, access to controls for adjusting data must be restricted.

Various orientations of edge security exist, depending on whether the data is centralized at a local data center, a microdata center or a third-party data center. Limiting access must be viewed by management as crucial to reduce the threat of a cyberattack. The list of approved devices must be updated when an employee is terminated or a third-party is granted temporary access.

The expansion of IoT potentially leads a company to build a complex infrastructure that’s cumbersome to manage. But centralizing data at a local or cloud-based data center allows for seamless edge computing. When managers and analysts are able to view the entire network, it’s possible to identify unusual activity quickly. Decision makers can act accordingly to prevent inefficiencies, vulnerabilities, and slowdowns from growing into bigger problems.

Read more: Earth 4.0: How IoT Contributes to Sustainability

Awareness and Future of SASE

Many businesses still must learn the differences between SASE and SD-WAN. The terms are not synonyms, nor is cloud-based security alone considered SASE. Another misconception is that SASE is the same as virtual appliances on edge devices. The key components that define SASE are protection for all edges, identity-based security and cloud-native software on a globally distributed cloud platform.

Gartner predicted 60 percent of businesses will phase out VPNs and adopt SASE by 2023. While SASE is still in its infancy, it’s important to distinguish high quality from low-quality SASE vendors. The low-quality vendors either aren’t keeping up with the technology or aren’t really concerned about cybersecurity. High-quality vendors stay on the cutting edge of new technology and help bring clients up instead of down.

The unstoppable growth of IoT devices is a major driver to the growth of edge networks. Due to the security risks relating to networks heavily populated with IoT devices, businesses are increasingly turning to edge computing.


Conclusion

The nature of edge security is that it gives you the best of several IT fundamentals, delivering a more efficient form of networking and security. It takes into account the need for all network edges such as smartphones, notebooks, and routers to be secure. Since it’s easy to control and saves money, edge security is poised to become more prominent in the coming years.

Read More
Edge Networking Trends
Information Technology

Edge Computing Trends in 2022 and Beyond

You probably know already, but just so we're all on the same page, edge computing refers to IT architecture of a distributed nature. Data processing of a given client's network is processed at said network's edge, right near where the data came from. So, a sensor array that collects information can simultaneously help process that data on an edge network.

The "edge" utilizes IoT to make this possible. Think of it as a sort of miniature cloud on your business campus. As a cloud networks servers together to compound data processing capability, edge networks use multiple devices locally for the same purpose. Another way of looking at it is: edge computing filters useless data from useful data.

There's a flood of information out there, and information is a currency in the modern world; you can do a lot with it. So, what does this mean for your business? Well, that depends on how prevalent edge computing gets. In 2022, it's expected to advance across several key industries, and in several specific ways. We'll explore these edge computing trends here specifically:

Data Filtration via Edge Tech Will Optimize Operations Ahead of Competitors

So, the edge makes data at the source of its composition more accessible, and filters out the "noise", as it were, from data you can use. Now you can operate more optimally and get more done with greater cost-effectiveness.

You can identify redundancies you didn't know were there, maximize equipment utility, put processes in place that will increase the ROI of your operational spending, and the list goes on. Businesses that leverage edge computing toward more optimal functionality now will have an "edge" (pun intended) on competitors.

Eventually, this will be standard practice; right now, people are finding their "rhythm", as it were, in this new tech. Ultimately, there's a competitive window for edge computing trends in 2022, and savvy businesses are definitely going to take it.

As 5G Expands, IoT, AI, ML, and Automation on Edge Networks Does Too

IoT tech facilitates edge computing, and 5G optimizes IoT. Collaterally, Artificial Intelligence and Machine Learning are also developing at break-neck speed. Many AI and ML breakthroughs crossover with IoT. Ultimately, 5G tech is going to act like a rising tide lifting all ships.

In this analogy, the "ships" are AI, ML, and similar software innovations. Edge computing utilizing IoT, AI, and ML on a 5G network will reveal more data, and more quickly. You'll get real-time insights impossible before. Multiple industries have the capability of optimizing with such information toward increasingly efficient automation.

Automation can even initiate failover protections as regards operational redundancies in the event of emergency. All devices can be monitored, and algorithms can be put in place to identify features of tech functionality that could indicate an issue.

Now, as of 2022, few industrial campuses have production floors so automated only one or two people are necessary to manage them, but the technology is already here. The trick is applying such tech infrastructurally. Businesses that get ahead of the pack will, as pointed out earlier, have a definite competitive edge.

Operational Capability Locally Regardless of External Internet Availability

This is something that's already been around for a while, edge computing is just a new innovation. Big campuses with lots of techs have on-site server arrays that already form their own "intranet", which is a sort of on-site internet separate from the "real" internet.

Much of localized "intranet" networks are actually accessible via the dark web, but if all contact with external web options were ceased, said localized intranet would remain. Well, with edge computing the same potentiality exists. If a connection to the cloud or an external internet provider is lost, an edge network keeps functioning.

It's Going to Be Everywhere; Even in Agricultural Communities

Owing to the associated advantages of edge computing, it's to be expected such innovations will transition beyond the tech sector. IoT tech used on agricultural equipment can save time and money for farmers, helping them be more productive and increase their profit.

Agriculture tends to produce marginal annual returns, the wealth being in the land or the livestock (or both). As an example: a $1,000,000 profit for the year might have $960,000 in expenses, leaving the family that farms only $40k in profit.

With edge computing utilizing IoT to help initiate automation, that margin may jump from $40k to $100k or more, allowing farmers to branch out and optimize even further.

The Edge Is Getting Foggy and Will Continue to in 2022

Here's how fog computing works: there's a "compute layer" between the edge and the cloud. Basically, "foggy" edge computing is the "edge" of the "edge" network. Basically, managed fog computing solutions receive information from an edge network before it gets to the cloud--it's a sort of middleman, if you will, that gains access to useful data your business can leverage toward optimization.

The right fog network can parse between data sets to separate out that which is useful from that which isn't. What's relevant will stay on the cloud, what isn't will disappear--unless, of course, there's a reason for a business to keep that non-relevant data.

So, what does this look like in practice? Say there's a temperature sensor in your network that continuously collects temperature data. That data is sent to the cloud, and it's monitored for spikes. Well, fog computing would determine if there were any data relevant enough to send to the cloud, saving time and complication in operations when nothing remarkable is recorded.

Foggy edge IT pros would determine what constituted relevant data, and voila: things like bandwidth and latency evaporate. The bigger the business, the more speed a properly managed foggy edge network brings. It's going to be negligible for smaller operations, but the bandwidth saved is ultimately going to reduce operational costs collaterally over time.

An Expansion of Edge Tech in Retail

Think of local department stores, the security cameras they use, the devices at entrances and exits, self-checkout equipment, lighting, HVAC, shipping, receiving, and all the other little departments such stores must manage.

There's a high potential for edge computing. Now imagine that spread out across hundreds of stores nationwide. That's a big "edge". Expect to see retail stores advance accordingly.

Edge Tech in the Energy Industry

Agriculture and retail aren't the only places where edge computing is useful. Pipelines often stretch thousands of miles. Fitting the whole line with IoT requisite to facilitate edge computing is good for oil companies and the environment collaterally--spills can be anticipated and intervention can be applied prior to an incident. Furthermore, with massive pipelines, manpower just isn't available regardless of edge options.

This kind of tech will actually take the oil industry into new territory. Instead of flying planes down the pipe, data can be gathered and transmitted using edge and foggy edge tech, being managed remotely with greater cost-effectiveness and convenience. Pressure anomalies can be quickly identified, diagnosed, and either rectified or left, depending on the situation. If valves need to be shut down, this can be done remotely.

An Expansion in Edge Workloads

Naturally, advantages of more data collection and filtration toward optimal use will increase the workloads demanded of edge networks, which subsequently will yield breakthroughs in the IT sector for that area. So, the edge itself will become sharper--foggy edge applications are a good indicator of that.

AI Computing on the Edge With IoT-Enabled Vehicles

Computers have been central to automobile functionality for decades now. It was a natural step to extend that computational capability to IoT applications and, ultimately, edge computing. Your vehicle's computer saves mechanics and manufacturers time in diagnosing operational issues with the engine or other functional components of the car.

With IoT applied to vehicular functionality, as the car passes into and out of coverage zones, it can send automatic updates to the manufacturers. Essentially, now each vehicle that is IoT-enabled functions as a sort of case study in the longevity of certain vehicular components. How long will the factory water pump last? What about the transmission? At what point do the majority of vehicles experience issues in component functionality, and what does that look like?

Already, careful data has been kept on things like this related to automotive functionality. For example, there's an older RV made by Volkswagen and Winnebago called the Winnebago Rialta; it's really just a glorified camper van. At any rate, the run of these vehicles went from the mid-nineties to the early aughts.

Computational data and driver reports helped manufacturers realize there was an issue with this particular vehicle's transmission. At about the 100,000-mile mark, most of these vehicles had serious transmission problems. If the vehicle made it past the 100k mark, however, the transmission tended to last to 200k miles. So, there was a manufacturer issue which was noted in the literature well before cloud computing, IoT, or edge computing even existed.

Now that manufacturers and mechanics have access to such data, it becomes possible to anticipate issues and correct them before a driver is left without an option, with a broken-down car by the side of the road.

In a big city with thousands of drivers making moves which produce data via IoT, an edge network develops that can act as a sort of digital "cradle" for drivers, allowing for computational navigation anticipation, expanding safety and security for drivers even in congested areas. So, the advantage to vehicles through IoT and edge computing is twofold: vehicular functionality can be enhanced, as can driver safety. Collaterally, things like road design will ultimately shift over time as data reveals better ways of handling cars.

How Edge Computing and AI Will Impact Autonomous Vehicles

For autonomous vehicles, edge computing may be the saving grace of the innovation. Many autonomous vehicle designs have been put into action as of 2022. By 2016, Uber had a few "driverless" cars in San Francisco, but there have been accidents which have limited the trend; still, as of February, 2022 the "Cruise" line of driverless cars has become a big player in the city; and that trend will only increase over time.

With millions of vehicles providing continuous IoT data to the edge network, now driverless cars can operate much more safely. Not only can trends be used to design safety features into such vehicles, but real-time data concerning traffic on a given route for such a vehicle can also be processed to help the software controlling the vehicle react properly when unexpected dangers on the road show up.

Modern cars contain hundreds of sensors even if they're not "autonomous", meaning the data they produce is available for exploration and can be leveraged toward greater safety by vehicles with savvy edge computing software designed for the processing and application of relevant data. As edge computing trends become more streamlined, the sort of data that is used for this purpose, its transmission to the cloud, and how it is used will necessarily become more streamlined. Through this method of qualifying information, data that isn't sensitive to individual drivers, or that contains other things which are private, can be automatically restricted from cloud data repositories. Doing so effectively will reduce the expense of transmitting data, as only that which is needed will be sent to cloud arrays designed to help manage autonomous vehicles.

As Tesla's market share increases, and more competitors develop, IoT information will form edge networks that are used to manage the battery life of varying electric options. Such networks can help inform drivers where charging centers are and when precisely they'll need to find one based on predictions from patterns in the data.

Furthermore, edge data can contribute to better traffic management. Autonomous vehicles can all "report in", helping computers automatically route traffic around congested areas. The same data can be sent as updates to non-autonomous vehicles, and in fact we are already seeing this a little bit with Google. If you're in Google Maps, and the little voice comes over your speakers advising you to take an alternate route with less traffic, cloud-based IoT and burgeoning edge networks are the foundation from which that informed suggestion came. As computational vehicular design, IoT, edge computing, and autonomous options become more integral, expect such edge-based data applications to increase substantially.

Where Edge Computing and Business Meet

Energy, agriculture, and retail are expected to increase edge utility in 2022, and edge computing generally is poised to expand. Edge computing trends will continue through the year and beyond, edge operations need not rely on the web solely, 5G is going to initiate increased edge automation, and businesses on the edge early will be more competitive than peers. Finally, in terms of vehicular development, expect advances for both driven and driverless vehicles that are specifically rooted in the edge, and which will likely become increasingly prevalent over time. You may well work with tech professionals to see where true benefits could help your business operate more efficiently via edge tech.

Read More