Category Archives: Edge Computing

Edge computing refers to processing data close to the “edge” of the network, near the source of data generation.

Edge Computing

Edge Computing: Unravelling Its Fate

Edge computing burst onto the tech scene several years ago with great fanfare and promise. It was heralded as a revolutionary new paradigm that would change computing as we knew it. By pushing computation and data storage closer to the “edge” where local devices and sensors reside, rather than relying solely on the cloud, edge computing aimed to reduce latency, enable real-time data processing, improve reliability, and enhance security. The potential benefits for IoT, AI, AR/VR, autonomous vehicles, and other emerging technologies were tremendous.

However, the heady optimism surrounding edge computing has dampened somewhat in recent years. The technology has not yet lived up to its full disruptive potential. There are several key factors that help explain what happened to edge computing:

  1. Complexity of implementation – While conceptually straightforward, actually deploying and managing edge networks at scale has proven difficult. Integrating heterogeneous devices, optimizing latency across geographies, allocating workloads, and orchestrating connectivity across edge and cloud introduces daunting complexity. The lack of unified standards and best practices has hindered adoption.
  2. Cost – Building out distributed infrastructure across metro areas and globally requires enormous capital expenditure. For many companies, the costs have outweighed the promised benefits thus far, especially given the immaturity of edge-enabled use cases. The edge business case remains unproven.
  3. Skills gap – Extracting value from edge networks requires expertise in OT/IT convergence, data engineering, middleware, device management, and more. Talent with this precise mix of skills has been hard to come by. Many organizations lack the right in-house teams to deploy edge computing.
  4. Security risks – Pushing out compute power to the edge expands the attack surface dramatically. New edge-specific vulnerabilities combined with inadequate security measures have exposed networks to greater risk. Not enough attention has been paid to securing edge devices and infrastructure.
  5. Regulation – Strict data sovereignty and privacy regulations in some regions have made it difficult to deploy centralized, cloud-reliant edge networks. As edge use cases like self-driving cars and smart factories emerge, regulatory uncertainty persists.

In summary, while edge computing is still in its early stages, the hype has cooled as pragmatic challenges have surfaced. However, the core value proposition remains compelling. As technologies and skills mature, edge is likely to proliferate in clearly defined, high-value use cases. But it may take time for edge computing to truly become the seismic shift many predicted. Careful management of complexity, costs, security, and compliance is needed to unlock the full potential of this important innovation.

Edge Computing

Edge Computing Comes up with New Prospects in the IT & Telecom Sector

 

In the last few years, there’s been a significant load on the cloud infrastructure across the world along with a steep increase in the number of intelligent applications, which in turn has driven the global edge computing market growth in several ways.  Moreover, the fact that edge computing supports real-time applications in assessing and meting out collected data has supplemented the market growth even more.

Just unlike regular or standard cloud computing platforms that assimilate storage under a distinct data center, edge computing tends to push the computation or the data handling command to the edge devices to handle. Furthermore, with the high-end technological advancements on board and more & more improvisations being integrated into IoT and 4G/5G, artificially intelligent expedients are getting associated with the Internet almost every day. And, this huge data engendered by all these smart devices thrusts the limits of cloud storage set-up, thus forming a considerable burden on the cloud center. This load further causes concerns with network latency while dishing out the data between the cloud platform and the respective devices. This is where edge computing comes and proves its flair.

According to Allied Market Research, the global edge computing market is anticipated to grow at considerable CAGR from 2018 to 2025. Processing data closer to the corresponding manufacturing unit can prove to be extremely useful, which can be achieved by bringing AI into play. AI-based edge expedients including chips can be utilized in multiple endpoint devices such as cameras, sensors, smartphones, cameras and other IoT enabled devices.

Most importantly, the telecom edge is anticipated to grow at a jet’s pace in the next few years. The telecom edge is expected to implement computing close to the mini-data hubs, which are run and maintained by the telco-owned properties. A number of telecom providers such as Telstra and Telefonica are getting involved in high-end pilot projects of an open-access grid or system assimilated with edge computing. Edge is also projected to rule the telecom industry once 5G infrastructure is rolled out at a full sway. The telecom industry is indeed in a unique position to reap huge advantages from edge computing.

Presently, the use cases of edge computing have surpassed initial infrastructure dispositions and are anticipated to dole out a spur to evolving edge computing use cases and infrastructure outlays. As per the specialists in this domain, edge computing would even become more prevalent and ubiquitous toward platform-centric solutions. With this changeover, edge services could diminish the infrastructure intricacies using erudite management and instrumentation software, and create easy-to-understand settings for developers to set out inventive edge applications and solutions with relative simplicity.

Edge computing comes up as an essential solution for any IoT platform. A lot of open source languages and outlines are available for edge computing. Eclipse Hono, Kapua, ThingsBoard, Kura, and Spring Boot are quite a few names worth mentioning here. These outlines tend to offer provide a lot of different APIs, network, assimilation facilities, edges, connectivity, and other managing & controlling features. This not only aids in assimilating data for edge computing, but also offers huge opportunities for the growth of the market.

AT&T is now collaborating with Microsoft at the pole position of edge computing so as to address a lot of concerns related to edge computing. The main objective is to make it faster and simpler for companies of all sizes and shapes to acquire their private edge networks up and running. As for instance, a healthcare center might utilize its private grid to accurately track apertures, wheelchairs, and other expository items in its structure. However, if a ventilator gets lent to another nursing home, it would still get ensured that the machine always keeps working even beyond the private network.

The private 5G Edge by AT&T is intended to be a cohesive platform offering connectivity and entrenched applications via a single podium with the usage of CBRS spectrum or AT&T range where there are specific customer requirements to meet. The company is also looking for even better tactic to offer top-end graphical and computing processing control with the 5G network, by self-install capacity.

To conclude, it can be stated that the global edge computing market has started growing quite exponentially, and in the next few years to come, it would prosper even more.

 

Author’s Bio- Koyel Ghosh is a blogger with a strong passion and enjoys writing on miscellaneous domains, as she believes it lets her explore a wide variety of niches. She has an innate interest for creativity and enjoys experimenting with different writing styles. A writer who never stops imagining, she has been serving the corporate industry for the last four years.

 

 

Edge Computing

Edge Computing Trends 2022

Workplace safety in the energy sector

One of the most powerful and important benefits of Edge computing is its use in the oil and energy industries. These industries traditionally rely on collecting and transmitting data to surveillance centers located in remote locations. This means that even with real-time sensors monitoring, for example, pressure and conductivity, information about potential emergency situations can reach the data center much later than a critical failure occurs. With Edge computing, anomalies and problems can be tracked and resolved faster than ever before.

Security

Many different emerging technologies, and 5G and IoT are no exception, have their own vulnerabilities. In doing so, edge computing can be used to mitigate potential threats. Traditional centralized networks and data warehouses make it easy for attackers to sign in and access data, but Edge diversifies some aspects of attack and provides better protection.

This does not mean that edge computing is extremely reliable. In fact, for most of 2022, companies will be dealing with vulnerabilities, not the merits of Edge. According to Kollective, 66% of IT teams see this technology as a threat to their organizations.

One of the main threats posed by edge computing is the proliferation of physical data sources. Since Edge involves operating more physical resources in the real world, attackers have more targets to compromise networks. If they gain access to Edge devices, they can extract valuable information, tamper with or destroy node diagrams, or even change the OS and software of the nodes.

According to some experts, fears associated with Edge computing, to some extent, devalue their benefits and may even slow down implementation.

Customer experience

One of the hottest business uses for Edge is in customer service. By reducing latency inherent in this technology, companies can provide optimal service. For example, amusement parks use IoT sensors and edge computing to quickly communicate the performance of their rides. Based on this data, adjustments are made to optimize their performance and prevent possible failures.

Even more tangible is the significant increase in the speed of sales that Edge computing provides. A Deloitte Digital study found that a 100ms increase in mobile retail speed resulted in an 8.4% increase in sales conversions. Reducing latency can also help marketers process customer data in near real time. This allows for more personalized and interactive customer services, advanced chatbots, and even offline interactions.

Internet of Things


The Internet of Things (IoT) is the fastest growing area that includes edge computing devices. These include smart appliances, smartphones, wearable devices, gaming systems, printers, and more.

According to forecasts Statista, by 2025, the prevalence of smart devices will increase four-fold. This is expected to significantly expand edge computing capabilities. In fact, the rise of IoT could lead to great benefits in the Edge sector, such as lower latency. The growth in the number of IoT devices will not only contribute to its development, but will also revolutionize various industries such as healthcare and education. In fact, IoT devices are already being deployed at the edge in healthcare and for remote site monitoring.

Edge computing in healthcare

The healthcare industry is at the forefront of IoT adoption, so it’s expected to lead the way in edge computing as well. Large hospitals are realizing that it is more profitable for them to store medical sensor data, electronic medical records and digital imaging nearby, rather than transfer it to the cloud. An example is a real-time sepsis diagnostic solution. Thanks to Edge, this traditionally lengthy process has been reduced to almost one day.