Humanity is now generating more data than it can handle; more sensors, smartphones, and devices of all types are coming online every day and contributing to the ever-growing global dataset. The current estimate for the amount of data generated in one year is around 40 zettabytes (or about 2.5 billion times more data than is contained in the library of Congress).
Additionally, the increased use of edge devices—from the Internet of Things (IoT) devices, such as smart cameras, mobile point-of-sale kiosks, medical sensors, and industrial PCs to gateways and computing infrastructure will require real-time smart data processing in addition to capable connectivity and communication. This is driving exponential growth in the amount of data generated and collected.
Over the past decades, cloud computing has been greatly developed and applied owing to its high cost-efficiency and flexibility achieved through consolidation, in which computing, storage, and network management functions work in a centralized manner. The increase of IoT devices at the edge of the network is producing a massive amount of data to be computed at data centers, pushing network bandwidth requirements to the limit. Despite the improvements of network technology, data centers cannot guarantee acceptable transfer rates and response times, which could be a critical requirement for many applications. Mobile devices connected to distant centralized cloud servers try to obtain sophisticated applications, which impose additional load on both Radio Access Networks (RANs) and backhaul networks and result in high latency.
It’s estimated that by 2025, 75 percent of data will be created outside of central data centers, where most processing takes place today. Taking this a step further, approximately 90 percent of all data collected by enterprises today will never be used. Edge computing provides a path to reap the benefits of data collected from devices through high-performance processing, low-latency connectivity, and secure platforms.
The emerging IoT introduces new challenges, such as stringent latency, capacity constraints, resource-constrained devices, uninterrupted services with intermittent connectivity, and enhanced security, which cannot be adequately addressed by the centralized cloud computing architecture.
Next-generation networks will require the support of interactive AI-powered services and some services like autonomous vehicles are sensitive to response latency, which needs to interact intelligently with their environments in real-time. A promising solution is known as “edge computing” is emerging that refers to the storage, processing, and analysis of data nearer to the edge of a user’s network, wherein the data is generated to enable rapid, near real-time analysis and response. Edge computing technology moves the computation away from centralized data centers by exploiting smart objects, mobile phones, or network gateways to perform tasks and provide services on behalf of the cloud.
Although the computing capabilities of wearable watches, smartphones, and other IoT devices have been significantly improved, they are still constrained by fundamental challenges, such as memory size, battery life, and heat dissipation. Mobile devices need to extend battery lifetime by offloading energy-consuming computation of applications to the edge of networks. Edge application services reduce the volumes of data that must be moved, the consequent traffic, and the distance that data must travel. That provides lower latency and reduces transmission costs.
Edge computing is a networking solution that reduces the number of processes running on the cloud and moves them to local devices, such as the user’s computer, an IoT device, or an edge server. It minimizes the amount of long-distance communication between the client and the server, which decreases latency and improves process efficiency. Consequently, several organizations are adopting edge computing as it lowers bandwidth use, associated costs, and server resources
Such a capability would allow us to analyze this information effectively and, in turn, discover solutions to some of our most pressing problems, from traffic congestion to the spread of disease to clean energy alternatives. This offers superior control and management of the data, while cutting down on operational costs.
Securing sensitive data, such as private medical records, at the edge and transmitting less data across the internet could help increase security by reducing the risk of interception. In addition, some governments or customers may require that data remain in the jurisdiction where it was created. In healthcare, for example, there may even be local or regional requirements to limit the storage or transmission of personal data.
Lack of persistent internet connectivity can impede cloud computing, but a variety of network connectivity options make edge-to-cloud computing feasible. For example, 5G provides a high-bandwidth, low-latency connection for rapid data transfer and service delivery from the edge. The amount of data that networks can transmit at one time is limited. For locations with subpar internet connectivity, being able to store and process data at the edge improves reliability when the cloud connection is disrupted.
Edge computing is more suitable to be integrated with IoT to provide efficient and secure services for a large number of end-users, and edge computing-based architecture can be considered for the future IoT infrastructure. IoT and edge computing devices collect data and manage it in one of two main ways. Intelligent edge computing devices with built-in processors may offer advanced capabilities like analytics or AI onboard, while devices without processors send the data they generate to a server deployed at the on-premises edge for storage and analysis.
An on-premises edge server can then process data from the edge computing devices and return critical information needed for near real-time applications or send only the relevant portions of the data to the cloud. Data from numerous edge computing devices can be consolidated in the cloud for more extensive processing and analysis.
Edge Computing for Defense and Security
Acute needs of edge devices are readily identified within the customs and border protection (CBP), where agents controlling illicit drugs and contraband can immediately make decisions instead of communicating with other data centers. With the opioid crisis, the number of sensors will inevitably increase, and EC devices with sufficient computing power and rapid communication rate can provide critical decision-making.
For chemical and biological sensors, real-time data acquisition, rapid processing, and computing are necessary. If the sensor output can be processed locally, instead of being sent to a different location, better mitigation and remediation can be achieved. A closely related EC-use case is the need for intelligent surveillance cameras. With the tremendous need for chem-bio standoff detection, the ability to collect molecular spectral data in addition to visual information would revolutionize surveillance technologies. Aided with AI, EC surveillance cameras will be capable of processing the local streaming and only communicate specific detection results rather than continuous submission of the data. Upon reception, the cloud could then send the EC device new instructions, including programming to different functionalities.
Edge computing advances life-saving possibilities for warfighters and the defense community. From warfighters to first responders and border patrol troops—edge solutions improve performance and minimize risk to those who are putting themselves on the line. Individuals and teams can now make safe, smart decisions without having to wait for information from the central command.
In fact, edge technology has already been used in the Air Force’s F-35, Army’s Digital Soldier, and other budding naval applications. For some time, the concepts underlying edge computing have been powering the most advanced combat aircraft ever created: the F-35. By way of sensors on each platform, F-35 systems assess the environment, fuse data with other F-35 aircraft, and then distribute a single picture of data across the planes. This all happens automatically, while planes fly in formation, by using a multifunction advanced data link (MADL). Here’s how the platform works: When flying in a squadron of four or eight jets, MADL uses high bandwidth to connect and share environmental data between each participating F-35s. It automatically links their systems and their shared sensor data to create a uniform analysis of any threats, targets, or unforeseen change to the airspace—more complete than any one aircraft could gather on its own.
Chris Bogdan, a leader in Booz Allen’s aerospace business, retired U.S. Air Force Lieutenant General, and the former Program Executive Officer for the F-35 Lightning II Joint Program Office, shared a powerful example. He witnessed how a Naval ship shot down an incoming missile using information from a linked F-35 flying beyond the ship’s tracking system range. According to Chris, the use of MADL between the F-35 and the ship allowed the aircraft to pass missile tracking data in real-time enabling the ship to deploy countermeasure to eliminate the threat before it came within range of the ship. Prior to the existence of the MADL technology this type of coordination would occur by relaying approximation from the aircraft pilot, through a command center, and then onto the ship cutting into the time to respond.
While edge computing can and should be used on mechanical platforms like the F-35, Army tanks, or unmanned drones, it’s also being used on these millions of boots on the ground. Since we know ultimately, the edge of the combat area is this “human” platform. Thanks to edge computing, troops have access to insights in remote locations with little connectivity. Weather conditions, machine performance data, and other sensitive information can now be turned into actionable decision-making. As possibilities at the edge advance, these applications continue to expand.
Advances in edge computing are now leading to what the Army calls “Digital Soldier.” Digital Soldier is all about using small, connected sensors that travel with soldiers to enable local data sharing and processing across network participants—and to provide individuals and squadrons with rapid information to ensure overmatch and safety. “When we think about Digital Soldier, the effect of networking is the n-squared—and this effect continues to increase as the number of network participants go up,” shared Greg Wenzel, leader of Booz Allen’s Army business and former service member in the National Guard. “At the end of the day, this ability to compute and process at the point of data capture, without needing to send raw data back for analysis, can save time—a lifesaving prospect for soldiers in the heat of mission operations. As we watch the Army develop these capabilities, we can see the immediate benefits of edge computing on creating more informed and faster squads in the field.”
In that way, Digital Soldier is trying to make Ironman without the suit: omniscient, highly digitized, more secure. When connected with nearby soldiers with sensors and other mechanical platforms, Digital Soldier will ultimately save lives and make missions significantly more effective. It will empower and inform. It will create a fuller picture without waiting for outdated information from a distant central command.
As the Defense Department explores new applications, data protection needs to advance along with the possibilities. Considering cyber basics, a smart backup strategy, connectivity and unique requirements for the technology’s footprint at the edge can ensure sensitive data information is reliable and secure. To ensure security at the edge, strong governance programs are key — beginning with an understanding of what data is being generated as well as how it is processed and transferred. All edge devices must be properly secured despite their less-central location and data should be encrypted at rest and in flight.
The department also needs to continue to evolve effective data backup and management strategy. The “3-2-1-1-0” rule suggests three copies of all data sets and information are kept on at least two different media. In addition, the locations should be distributed, with one copy stored offsite in case an entire region or facility is impacted. At least one copy of the data must be immutable, which is essential given the undetected, lingering threats that can be hidden on agency networks and the growth in ransomware.
For the Defense Department, the definition of “edge” may vary from forward operating bases, through operating in theater, to naval vessels and beyond. In these remote locations, connectivity can become a major barrier.
If a warfighter becomes disconnected from crucial information, there could be a lag in decision-making or lack of vital information while government workers try to reconnect. Every moment disconnected is critical. This is another place where backup comes in. If the necessary information is available reliably and separately from the network at the edge, defense forces won’t need to depend on connectivity to be productive and complete missions. When warfighters become disconnected, they can operate offline and batch changes at the edge, then connect back to the network when possible. Depending on the need, edge-based deployment can asynchronously or sporadically back up at the edge. This flexibility cuts down disconnect times and increases agility in situations where network connectivity isn’t reliable.
Edge Computing Market
Per an IDC report, edge computing market, worldwide, is forecast to reach $250.6 billion by 2024 at a CAGR of 12.5% between 2019 and 2024. Notably, rapid deployment of 5G, migration of workloads to cloud by enterprises and increased proliferation of IoT & AI is facilitating data processing at the edge.
Edge computing introduces a great level of business complexity, as it requires an extensive range of stakeholders for IT infrastructure, connectivity, application development, traffic delivery, and service management. Edge also brings together hardware and software solutions and networking architecture that address the vast number of use cases pursued across several industry verticals. As the technology is still in the early stages of development and its implementation and operational models are yet to mature, an edge is likely to create vast growth opportunities for new entrants in the near future.
Given the benefits of edge computing, all the tech giants including Microsoft MSFT, Intel INTC, and Amazon AMZN are working on advancing edge computing technology, thereby intensifying the competition.
Healthcare and telecom sectors are seeing increased investments in edge and IoT. The telecom sector is witnessing high growth in video conferencing software such as Zoom and Microsoft Teams and is rolling out new products to cope with the ever-increasing demand. For instance, in December 2020, SK Telecom collaborated with Amazon Web Services to launch edge cloud services based on 5G MEC. Companies are grasping the opportunities to tackle the current situation by delivering new services.
The intense escalation of demand for edge computing is expected to continue post-COVID-19 pandemic for the next three to four years as the stress on developing network infrastructure will not subside in the near future. Work from home becoming the new normal and the healthcare system reaching critical mass with online consultation is expected to give rise to such network infrastructure that requires low-latency connectivity and high security. Telecom companies are expected to capitalize on this opportunity as the per-unit cost of edge facilities will be overshadowed by the cost of adding additional switching facilities or building a full-sized data center. This cost advantage will accelerate telecom companies’ movement to a large deployment of data centers in the next couple of years.
Edge computing has become a solution-specific technology with exotic architectures and equipment that are built for particular use cases. 5G and network function virtualization, streaming games, and next-generation CDNs and cloud are some of the use cases where the edge is expected to capture a significant share over the forecast period. This is the first phase in a journey towards a future where the edge becomes readily available and a viable part of the internet with user-friendly interfaces for developers to exploit.
The servers segment captured a revenue share of more than 44% in 2020. Presently, servers that support edge applications are often owned by enterprises, connected to devices over a private network, and deployed on-premises. Servers are increasingly being deployed at many remote and edge locations, thereby helping reduce the latency between producers and consumers of data. Furthermore, with the telco edge evolving, the telcos are working on Multi-access Edge Computing (MEC) server platform for the data processing capabilities.
Edge sensors/routers capture a revenue share of approximately 23%. The increasing number of data centers across various industry verticals is propelling the demand for edge routers. The routers act as a gateway connecting the local network to external WAN. All the data packets approach the network to transmit through the edge router. Moreover, the edge router is eventually responsible for the security of the network, thereby screening out unauthorized access requests. The edge data centers must be well equipped with versatile and powerful edge routers that can handle a large capacity of incoming traffic with minimal latency.
Industry Vertical Insights
The energy and utilities segment captured a revenue share of over 17% in 2020. In the energy and utilities segment, the implementation of smart grids is expected to contribute to revenue growth as they rely on device edge infrastructure. Environmental sustainability initiatives are driving efforts to improve the efficiencies of electrical utility services globally along with the adoption of alternative renewable power sources, such as wind and solar. Smart grids are being implemented globally to improve operational efficiencies and enable capabilities such as integration with smart appliances, real-time consumption management, and micro-grids to support generation from distributed renewable sources.
The Industrial Internet of Things (IIoT) application segment captured a revenue share of over 31% in 2020. Edge computing has played an essential role in allowing manufacturers to achieve digitization of their facilities. In the manufacturing sector, a large share of edge computing is deployed in the form of device edge. The demand for edge infrastructure capabilities is expected to grow as service complexity increases and the infrastructure edge becomes more readily available. Furthermore, the Industry 4.0 initiative provides a framework for transforming manufacturing to address industry disruptions, thereby paving the way for edge deployment.
Industry 4.0 emphasizes operational agility using technologies that bring the convergence between physical and cyber systems. With an edge platform, smart factories have the option to send only filtered data to their cloud solutions. The edge acts as a gateway by analyzing data locally and sending summarized data to the cloud. For instance, in a smart factory, the edge systems can spontaneously reform certain problems proactively and then alert the plant operators to the issues on the factory floor.
The healthcare segment captured a significant revenue share in 2020. The healthcare industry has characteristically been conservative when it comes to the adoption of digital technologies. The industry is closely regulated, where innovation tends to be driven by consent rather than outright disruption. However, owing to the growing digitization across the healthcare sector, hospitals and clinics are increasingly adopting digital health strategies with varying degrees of maturity and success. To support these strategies, clinics and hospitals are implementing edge computing solutions across key use cases, including remote patient care, patient record management, and intervention and continuous patient monitoring.
North America accounted for the largest revenue share of more than 44% in 2020. The convergence of edge computing with IIoT is encouraging manufacturers in the U.S. to move toward connected factories. Additionally, several startups have emerged to provide platforms for developing edge-enabled solutions, which is expected to drive the regional market. For instance, telecom companies in Canada, such as Telus Communications, are working with MobiledgeX, Inc. to develop the MobiledgeX Early Access Programme, which would allow developers to build, experiment, and gauge the effectiveness of edge-enabled applications in a low latency atmosphere.
Asia Pacific captured a significant revenue share in 2020, attributed to the growing emphasis on improving networking technology in the region due to COVID-19. The notable expansion of the connected device ecosystem in the region is resulting in the generation of a large amount of data, thereby creating the need for a powerful computational environment. Moreover, the increased focus of leading service providers such as Microsoft Corporation, which recently announced Azure Edge Zones, and Google Inc., which unveiled its Global Mobile Edge Cloud (GMEC) strategy that was primarily targeted at the U.S. market, is expected to provide impetus to regional growth over the next few years.
Key Companies & Market Share Insights
Edge start-ups are engaged in developing micro-edge data centers, which are small-scale modular data centers that include all the storage, computing, networking, power, and cooling facilities. For instance, in 2020, EdgeMicro launched five new micro-edge data centers across the U.S. The company developed a containerized data center design that can hold up to six racks, each designed to support 8 kW of power.
Another key development in the edge computing space is the hyperscalers, who already have a strong presence in the cloud market. These hyperscalers are transitioning towards the edge by bringing new solutions such as AWS Outposts, Azure Stack, and other IoT offerings. Both telcos and hyperscalers are some of the top contenders to lead the market for edge computing. However, the lack of cloud platforms for telcos and the presence of physical location for hyperscalers are few limitations faced by them. To overcome these limitations, the industry is expected to witness partnerships between operators and hyperscalers, which may impact the short-term and long-term strategies of the market players over the next few years.
Some of the prominent players operating in the global edge computing market are: ABB Ltd., Amazon Web Services (AWS), Inc., Cisco Systems Inc., Digi International Inc., General Electric Company, Hewlett Packard Enterprise Development LP, Huawei Technologies Co. Ltd., IBM Corporation, Intel Corporation, Microsoft Corporation, SAP SE and Siemens AG.
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