Edge Computing: The Future of Big Data Analytics

Edge computing is a computing strategy that takes computing power and storage closer to the source of the data instead of transferring the data to a far-off central server. Many businesses today rely on data as the lifeblood of their operations, and they are also facing the challenge of incremental volumes of data. Traditional cloud-based platforms are the standard route for computational data.

Edge computing could be the answer to most industrial data problems we face today. Not only that, but it could change the way we do city planning. Smart cities? Cloud gaming? That’s only the tip of the iceberg. Learn all about how this progressive tech can help your businesses and how it can shape the future of society as we know it.

What Is Edge Computing?

In today’s technology-saturated world, there are practically millions of devices that collect and share information via the internet. Most of this information is processed in large data storage centers. Most companies have cloud servers located in faraway locations, resulting in reduced efficiency. In these cases, you end up finding yourselves with an expensive and slow-moving data compute model. Luckily, someone invented edge computing. This technology can resolve the existing issues that companies have with the traditional cloud computing platform.

Instead of directing data all the way to and from centralized servers, edge computing transfers the data to the edge of the network. At this “edge,” the data is sorted, analyzed, and trimmed. Investing in this kind of technology will help improve business efficiency as well as cut unnecessary costs. It also reduces latency while improving the network’s resiliency.

Edge centers can complement existing infrastructure designed to monitor or produce data. A good example would be the internet of things (IoT) infrastructure. Edge centers and IoT are typically found together in large-scale industrial and technical operations. These large-scale business operations produce a steady stream of business data.

How Does Edge Computing Work?

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Edge computing works exactly as the name implies, on the edge. Instead of transmitting raw data to a data center for processing and analysis, everything takes place on the edge of the network where most of the data transfer takes place. Edge computing transfers storage and computes resources to a place that produces plenty of data. Different types of devices can execute data analysis near the edge. The choice of device practically depends on the application and implementation of the concept.

Edge computing is being viewed as a far more efficient alternative to cloud computing in terms of moving and processing large volumes of data in real time. Traditional cloud systems are able to process individual units of data quite efficiently. However, it can’t accommodate large volumes of data across data centers. Add to that the poor capacity of the central server to produce meaningful and timely results. To learn more about cloud computing, check out this guide explaining how the cloud infrastructure works.

Many applications depend on high-powered processing that produces time-bound and independent analysis. Consider smart speakers that run on Google Assistant as an example. These devices are often outfitted with a combination of edge computing and artificial intelligence (AI) capabilities. These make independent processing and analysis render almost instantaneous results. It also gives the devices the ability to run offline commands.

What Are the Potential Applications of Edge Computing?

At the very core of edge computing is the ability to capture meaningful business data without risking the system suffering from latency and network-related issues. And there are many ways industries across the board can benefit from this. In fact, a number of industries have already demonstrated their benefits to the world. Out of the thousand creative ways to apply edge computing, a few applications stand out from the crowd:

Internet of Things

Edge computing is known for its wide selection of applications. But the most prominent application would be in IoT. By definition, IoT refers to many smart devices that you see on the rise recently. These devices are called “smart” because they all share the ability to connect to a larger network of devices which can be controlled through a single device.

Many experts also view edge computing as the key driving force for IoT development within industrial and commercial settings. Its potential applications in IoT are endless. Proponents are also hoping that it would lead to the development of new technologies that can radically change the way industries manage data. Eventually, new industries exploring IoT will find additional use cases for edge computing within the context of IoT.

Business Applications

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Edge computing was designed to handle the massive amounts of data being produced across various industries. And its practical effects could be seen very clearly in the business sector. Depending on how a company operates, the technology can impact data management processes on a fundamental level.

Besides that, the technology also works best in the company of other technologies that help improve the efficiency and effectiveness of service delivery for businesses. Here are some of the major industries that can benefit from the edge computing infrastructure:

Oil and Gas Sector

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The majority of oil companies deliberately build their refineries in remote areas and away from major cities. They do so as a form of precaution since any failure in the facility could lead to potentially disastrous accidents. Their assets need 24/7 monitoring, which is impractical to achieve with manpower alone. Another issue with oil facilities is that they are known to generate vast amounts of data. But as you can imagine, their remote locations cause latency in data transfers. They also experience unscheduled downtimes every now and then.

These downtimes could be very expensive for the oil sector, but hese problems can be avoided with the deployment of edge computing infrastructure in conjunction with IoT infrastructure. The IoT infrastructure will allow for 24/7 remote monitoring of the assets. Meanwhile, edge computing will intercept data for real-time analysis. This way, oil companies can reduce their reliance on good quality connectivity to a centralized cloud.

Smart Cities

Smart cities are urban areas that deploy different technologies, and that includes IoT infrastructures. Smart city technologies often generate large volumes of data from mechanical sensors scattered across various infrastructure around the city. These systems collect information from major city infrastructures. These information streams are valuable to government entities and private entities in charge of managing the city’s resources.

The massive streams of data processed by smart city systems encompass smart systems that function on a city-wide scope. These include traffic control systems, power plants, transport systems, waste disposal, and water supply networks among others. These large-scale operations produce incremental amounts of data. These smart city technologies and IoT systems also require instant analytics for the data. These are two things that only edge computing can handle with ease.

Financial Services

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Banks deal with large amounts of highly confidential information all the time. And the fact that they handle money makes them a common target for hackers and cybercriminals. With edge computing, banks won’t have to send all of their customer’s information to the cloud server for processing and storage. This reduces the risk of cybercriminals stealing or corrupting the information while in transit. It would also reduce processing times since the data travels a shorter distance.

This in turn saves the bank from significant operational costs. An increase in speed processing the data will make the network more efficient. Banks are also increasingly reliant on IoT technologies in the form of bank apps and ATMs, among others. All of these technologies require data processing. And edge computing offers up a wide selection of possibilities for more IoT options with fewer data limits.

Cloud Gaming

Cloud gaming is a video game method where the gaming data is streamed to an app or browser from a remote data center. One benefit of doing this is that it eliminates the need to download and install games on a PC or console. However, cloud gaming is still a bandwidth-intensive experience. These problems are even more marked for multiplayer gaming experiences. Edge computing solves these latency and graphics issues. It’s able to accomplish this by distributing application processes at the edge of the network and as close to the user as possible.

In addition, edge computing will also allow users to move seamlessly between different devices across various locations. It might even eliminate the need for dedicated devices such as consoles or high-end personal computers. The combination of edge computing and cloud computing can also create an even more flexible platform for higher quality cloud gaming.

Manufacturing Services

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The potential applications of edge computing in the manufacturing sector are also of grave significance. Edge computing frameworks can radically simplify complex and interconnected systems, making it easier to collect and analyze data in real-time. It will also allow devices to gather information from remote manufacturing plants where internet connection is limited. Edge centers can gather data, analyze them quickly, and then transmit it back to the central network where connections are possible.

Most important of all, edge computing will act as a more efficient alternative to cloud-based applications in building smart factories where industrial machinery can make autonomous decisions and adjustments without human intervention. Other than that, edge computing’s always-on connectivity will help provide around-the-clock visibility into operations. It also reduces the likelihood of system downtimes, which hampers production and, more importantly, provides better flexibility for data management.

Healthcare

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Many people perceive the health industry as one that doesn’t exactly keep up with IT infrastructure. But edge computing technology should be the exception. One of the most practical ways edge computing can benefit the healthcare industry is by expanding access to online healthcare services to people from rural areas. This is particularly helpful for people who live far from hospitals and have no or limited access to the internet.

Portable and wearable IoT healthcare equipment developed with edge capabilities can gather, store, generate, and analyze patient data without having to be constantly connected to a network. The technology promises rapid data analytics. The same would allow doctors and health professionals to diagnose their patients quickly and effectively regardless of their location. Moreover, health workers get to receive crucial information within less time. Experts also believe that the technology will help decentralize health information globally. It would also make the information more readily accessible across various platforms.

Traffic Management

Smart transportation is another ideal application for edge computing technology. The idea behind smart transportation has to do with the integration of travel-related infrastructure. That includes infrastructure like traffic signals, toll booths, CCTV surveillance systems, among others. Most modern cities have their own intelligent transport system (ITS) that strings multiple monitoring equipment across city infrastructure. This network will generate data and respond autonomously and automatically to real-time events on the ground.

Public transportation agencies can deploy edge computing near physical traffic hardware (controllers, signals, and environmental sensors) to allow them to analyze data on the spot. This significantly reduces the amount of data forwarded to the central server. This in turn helps reduce operating and storage costs. Another crucial benefit would be the instant analysis of traffic-related data. This will help to ensure that the corresponding infrastructure can make decisions and respond to real-time incidents.

Augmented Reality

Augmented reality is an interactive experience that adds computer-generated elements into real-time video capture on smartphones and other digital devices. AR needs to respond quickly to user’s actions and update the digital environment instantaneously. These requirements take up large amounts of computational power to achieve. And like many other apps that take up high levels of bandwidth, the device running the AR app is bound to experience latency.

Edge computing can help resolve this issue by processing the data on cloudlet processors located close to the data source, which should help reduce network congestion and allow data from applications to deploy quickly. The same would also save the battery power of the device running the AR application. Because of these benefits, many industries working with AR use edge computing infrastructure to reduce consumption of system requirements, focusing on reducing latency.

Video Conferencing

Edge computing can benefit from edge computing in the same manner as AR. The industry is currently seeing an upsurge in demand as more people recognize the importance and sensibility of remote communication. Traditional models being used by video conferencing companies often are not optimized for a smooth digital experience and often lead to latency and broken footage. The cause has to do with the large physical distances between the central server and the user.

This often manifests as episodes of frozen screens, delayed responses, or complete shutdowns in the middle of video conferences. And the farther a user is from the central server, the higher the chances that they will experience these problems. Edge computing can get computing resources closer to the user, thereby reducing latency. Nevertheless, edge computing should not be viewed as a one-size-fits-all solution to video conferencing issues. There are still multiple factors that can contribute to latencies in video conferencing.

Artificial Intelligence

Artificial intelligence and cloud computing are both buzzwords in the IT community, and the two technologies perfectly complement each other. AI has traditionally lived inside data centers powered by cloud computing. But in time, the technology slowly made its way into the IoT sphere and the world of interconnected smart devices. This increase in demand more than doubled or tripled the data that companies have to deal with on a daily basis.

Technology companies realized that they need to upgrade their computing power and bring the data centers closer to the end-user to reduce latency and other network inefficiencies. This realization caused the industry to start combining AI and edge computing into their devices in the hopes of reducing latency while also minimizing bandwidth consumption and operational costs. In the future, more AI devices will make use of edge computing rather than cloud computing.

What Are the Advantages and Disadvantages of Edge Computing?

Cloud computing remains the powerhouse in the world of data analytics. But with the emergence of edge computing, the weaknesses of cloud computing have been placed in the spotlight. Industries who have previously found themselves at a loss about how to fix those issues are now presented with a much more efficient and cost-effective solution. Nevertheless, edge computing still has its weaknesses and will not work for every use case. Let’s dive into the advantages and disadvantages of the technology to help you figure out if it fits into your particular situation:

Advantages of Edge Computing

Edge computing has a wide variety of advantages in store for firms and individuals who cannot benefit from cloud computing due to the volume of data they have and the remote location of the facilities that host the data. Here are some of the advantages of edge computing that may make you want to consider deploying edge computing for your business:

Faster Processing

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The popular saying “time is money” rings true for the business environment today. Any downtimes or latency in internal processes and communications can cost firms thousands of dollars in losses. One of the key benefits of edge computing is that it can reduce the latency of data processing, which directly affects making the network more efficient. It accomplishes this by decreasing the distance the data has to travel. This is because the edge infrastructure can process the data either locally or within the nearby edge infrastructure instead of in the central server, as is the case with traditional computing.

The actual figures for reduced latencies vary across edge platforms, but generally speaking, the data transfer time should fall from milliseconds to just microseconds. It will increase the overall speed, quality, and responsiveness of the particular edge technology that pairs with the system.

Security

Cloud systems are quite serious about data security. They keep multiple copies of the data spread out across servers to keep it safe. However, the problem with this cloud system is that it still requires the transfer of data from the source to a central server, and the data is vulnerable to attacks while en route to the central server. Edge computing can help improve the security of the data by reducing the physical distance that it has to travel. With less time in transit, there will be less opportunity for hackers to steal the data.

The edge will also filter the data to retain only the most sensitive portions. And with more data on the edge, hackers will have a harder time stealing the data. To learn more about how cloud computing security protocols work, check out this article about the best cloud computing security practices.

Reliability

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Besides latencies, many companies also face unexpected downtimes. Downtimes can cost companies hundreds of thousands of dollars. The problem affects select industries more than others. Case in point, a single day of downtime can cost an oil company hundreds of thousands of dollars. Downtimes have different causes, but the most common one is system overload, which is simply the system’s inability to handle the amount of data fed to it.

Edge computing can lessen the chances of downtime by relying on specialized microchips that don’t necessarily require an internet connection or connection to the main network. This is why edge computing comes highly recommended for operations in remote areas where is there is no internet or insufficient internet. Edge computing offers a powerful and independent service that can withstand common errors associated with downtimes.

Scalability

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Another major benefit that edge computing offers to the network has to do with scalability. The distributed nature of the edge computing platform makes it entirely possible for organizations to expand the network as and when required. Edge computing functions on distributed fragments of technology. Each unit functions independently without affecting the rest of the network. With this in mind, organizations can increase the number of edge centers, data centers, and processors, and the entire network would still function efficiently across the distributed components simultaneously.

On the other hand, expanding a network that relies on a centralized server would most likely have the opposite effect. The system cannot handle the simultaneous processing of large volumes of data. Large-scale extensions of data would be cumbersome to the system and would most likely slow it down or even cause a system breakdown.

Cost-Effectiveness

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Computing workloads are increasing across the industry, beginning from the manufacturing plant producing car parts to the very popular IoT television service Netflix. As the networks for IoT continue to grow, companies can expect higher expenses in the way of data center infrastructure and operational costs. They can avoid these anticipated increases in operational and maintenance expenses by relying on the distributed edge computing. With more data on edge, central servers have less data to store and process.

This radically reduces operational and storage costs. Another benefit is related to the edge’s ability to function without high-speed internet connectivity, which significantly reduces internet costs. Other lesser-known cost-benefit stems from the edge network’s ability to enable interoperability between old and new devices within the network. It essentially converts the communications protocols to communicate older and newer devices, thereby eliminating the need to purchase new devices.

Disadvantages of Edge Computing

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Edge computing is becoming increasingly popular nowadays, but that doesn’t mean that the technology is perfect. It doesn’t apply to every possible use case. And in some cases, you would still be better off using cloud computing devices instead. Here are some of the disadvantages that you need to know about before making a considerable investment in the technology:

Incomplete Data

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One of the key disadvantages to edge computing is that only a subset of the data is guaranteed a place on the edge network. As we’ve discussed in passing, edge computing devices are designed to filter the data to only get the more sensitive and crucial data components. The edge device would then discard the remaining parts of the data which it deems unnecessary.

Meanwhile, the remaining data are forwarded to the central server for additional processing. Therefore, if a company is not careful about selecting the data they want to keep or fails to input the correct parameters for the sifting of the data, they could very well end up with an erroneous or incomplete picture of their business operations. This is why organizations need to determine which types of data they want to keep and which data they want to discard.

Storage Requirements

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Another potential weakness of edge computing has to do its inability to store data long-term. We already know that the edge device only retains the important sections of data. But the edge can only handle so much data, and the data it stores cannot stay there indefinitely. Eventually, the sensitive data would have to be transferred to the cloud.

This is because edge devices are primarily designed to process data and not store them for long periods of time. Another issue is that edge computing often takes up more space on devices that have them (i.e. smart speakers). Since storage devices embedded in IoT devices are shrinking in size over time, this may not be that big of a problem. Nevertheless, it is something worth considering when selecting an edge platform for your business.

Investment Costs

Like most amazing things, edge computing doesn’t come cheap. Companies who want the benefits of processing on edge would have to make a considerable investment in the technology. Case in point, the mid-level cost for a complete edge computing platform can set back a company up to USD 12,000 to USD 15,000. On the other hand, companies who want to go high-end will be facing a price range of anywhere between USD 40,000 to USD 50,000. These so-called packages already include additional services like security, full-stack monitoring, and customer service.

Some of the factors that come into play when it comes to the price include ease of use and installation, durability under varying temperatures and physical conditions, the presence of self-protective mechanisms, and intended use case. The bottom line is, if you want a great performing edge platform, then you’ll have to put your money where your requirements lie.

Maintenance Costs

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While edge computing can reduce long-term operational costs, it may come with higher maintenance costs. The reason for this is that, unlike cloud architectures that come in the form of refrigerator-like servers, edge computing works with smaller data centers spread out across the network. This translates to having more components to work with compared to the traditional cloud. Since it would most likely involve several devices in a single network, it is more difficult for engineers to monitor and update the software’s separate components.

Besides these considerations, the technology still hasn’t reached its peak development. The implication is that there is still plenty of room to improve in terms of how the technology is managed and maintained. In the meantime, adopters would have to stick with manual maintenance of the edge infrastructure, which could also mean higher labor costs.

Final Thoughts on Edge Computing: The Future of Big Data Analytics

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Edge computing is becoming increasingly in demand across different industries. The popularity of the computing platform is attributable to its instant data processing and resource-efficient features. What edge computing offers is almost the exact opposite of what cloud systems offer. But at the same time, what it offers appears to be the exact solution to the industry’s current problems. Besides offering a very practical set of features, edge computing also serves as a great complement to most technologies.

These technologies include IoT, artificial intelligence, and augmented reality. The emergence of the edge also comes at the perfect time, just as the cloud computing platform nears its market maturation. These factors, taken together, paint a very bright future for edge computing as it slowly and steadily overtakes cloud computing as the dominant distributed computing platform. For more information about alternative computing strategies, check out this article explaining the quantum computing platform.