The advent of edge computing is poised to have a significant influence on various industries, exerting its effect on both current and forthcoming verticals. Although certain sectors have already experienced the initial waves of this impact, others are anticipated to adopt it at a relatively slower pace. Consequently, telecommunications companies must exercise caution and prudence in their vertical selection process, ensuring that they choose the most appropriate target area in light of the edge computing impact.
Edge computing refers to a distributed computing paradigm that brings data processing and computation closer to the edge of the network, in close proximity to the data source or end-users. Unlike traditional centralized computing models, where data is sent to a remote data center or the cloud for processing, edge computing enables data processing and analysis to occur at or near the point of data generation.
In edge computing, small-scale data centers, known as edge nodes or edge devices, are deployed at the network edge. These nodes can include routers, gateways, servers, or IoT devices. By processing data locally at the edge, edge computing reduces latency, improves real-time responsiveness, and enhances overall system performance.
The key idea behind edge computing is to bring computation closer to the data source, which offers several advantages. It enables faster data analysis and decision-making, reduces reliance on the cloud for processing and storage, and minimizes the amount of data that needs to be transmitted over the network. This approach is particularly beneficial in scenarios where real-time processing, low latency, bandwidth efficiency, and data privacy are critical requirements, such as IoT applications, autonomous vehicles, industrial automation, and smart cities.
Edge computing has the potential to revolutionize various industries by enabling new use cases and applications that require low-latency data processing, real-time analytics, and localized decision-making. It complements cloud computing by providing a decentralized and distributed computing infrastructure that brings computational power and intelligence closer to where it is needed, unlocking the full potential of emerging technologies and enabling innovative solutions.
The main characteristics of edge computing encompass:
There exist four distinct categories of Edge Computing, each serving different purposes within the overall framework.
By categorizing edge computing into these four types, we can better understand the diverse implementations and their respective roles within the broader landscape.
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Fog computing serves as an extension of cloud networks, which consist of interconnected servers forming a distributed network infrastructure. These networks empower organizations to surpass the resource limitations they would otherwise encounter. A primary advantage of cloud networks lies in their ability to gather data from diverse sources, making it accessible from anywhere via the internet. While fog computing shares similarities with cloud networks, both involving intelligent data processing at the time of creation, a crucial distinction exists between the two in terms of intelligence and computing power.
Fog computing places greater emphasis on intelligence within the local area network (LAN) environment. In this architecture, data originating from endpoints is transmitted to a gateway, which subsequently routes it to appropriate sources for processing. The processed data is then returned to the transmission path. Conversely, cloud networks prioritize computing power and data processing at the edge of the network. This entails performing computational tasks on embedded computing platforms that interface with sensors and controllers.
By deploying fog computing, organizations can leverage local intelligence within their LAN, facilitating efficient and localized processing of data. This approach is particularly beneficial in scenarios where real-time responsiveness, low latency, and optimized resource utilization are critical factors. On the other hand, cloud networks excel in providing substantial computing power and enabling data processing on a broader scale, with a focus on centralized cloud-based infrastructure.
Key takeaways:
The emergence of edge computing is poised to have a substantial and far-reaching influence on various industries. While certain verticals have already experienced the initial effects of this transformative technology, others are expected to be slower in adopting edge computing solutions. Understanding this disparity in adoption readiness is crucial for operators seeking to capitalize on the edge computing opportunity and expand revenue streams beyond core connectivity offerings.
The advancements in edge computing, characterized by reduced latency, improved reliability, enhanced security, and increased mobility, unlock a plethora of new use cases across various industries. One prominent example lies in the realm of security solutions, where the deployment of edge computing infrastructure enables video ingest and analytics at the network edge, leading to significant impacts.
As the prevalence of video surveillance continues to rise, there is a corresponding surge in data volumes generated by the growing number of cameras and the improved quality of video recordings. Edge computing effectively addresses the challenge posed by the escalating data volumes by decentralizing traffic and analysis, enabling on-site processing in real-time for monitoring purposes or triggering alarms.
The latency requirements for real-time processing make it impractical to rely solely on cloud-based solutions. By leveraging edge computing, the necessary functionalities can be performed locally at the network edge, ensuring minimal latency and immediate response. Additionally, conducting these operations at the edge enhances data security, as sensitive information is processed and stored closer to its source, reducing the risk associated with transmitting data to a centralized cloud infrastructure.
Thus, edge computing plays a vital role in meeting the demands of processing and analyzing video data, offering improved security, lower latency, and real-time insights for effective monitoring and alarm triggering in the face of growing data volumes and evolving surveillance requirements.
Telcos can assess potential target verticals for edge computing solutions based on various metrics to determine the most attractive opportunities. Here are several key metrics that telcos could consider.
Indeed, the contribution of an industry to the GDP of a country (or countries) where a telco operates can serve as a useful indicator of its ability and willingness to invest in digital solutions. When telcos consider offering edge computing solutions, the financial aspect plays a crucial role, as significant investments are required. Evaluating the target verticals spending capacity becomes essential for telcos aiming to maximize return on investment (ROI).
Industries that make a substantial contribution to a countrys GDP often possess greater financial resources and a stronger appetite for digital transformation. These industries are more likely to prioritize and allocate budget towards innovative solutions such as edge computing. By targeting verticals with a higher GDP contribution, telcos increase their chances of engaging with industries that are financially capable and inclined to invest in digital advancements.
Using GDP as a proxy for spending capacity provides a useful framework for telcos to assess the potential ROI of their edge computing offerings. It helps identify verticals where the likelihood of securing investment and achieving revenue growth is higher, aligning with the telcos strategic objectives and financial sustainability.
IIoT and edge computing are gaining traction in many industries
Telcos venturing into offering verticalized edge solutions must possess a solid comprehension of the pain points faced by enterprise customers in the present context. Additionally, establishing strong anchor customers with whom they can collaborate to test and develop new solutions becomes crucial. Leveraging existing industry expertise and relationships serves as a valuable starting point for telcos in this endeavor.
For instance, TELUS, with its strong vertical focus on healthcare through TELUS Health, can leverage its industry knowledge and relationships to explore an edge-enabled approach within the healthcare sector. By understanding the specific challenges faced by healthcare organizations, TELUS can tailor edge computing solutions to address their pain points and provide enhanced services and experiences.
Similarly, Verizon, known for its strong vertical presence in the transportation industry through Verizon Connect, can leverage its expertise to pursue edge-enabled opportunities within the transport sector. Building upon their existing industry relationships and understanding the unique requirements of the transportation industry, Verizon can develop and deploy edge computing solutions that cater to the specific needs of transportation companies.
Industries that have reached a higher level of digital maturity are more likely to adopt edge computing-enabled solutions earlier. This is because certain prerequisites, such as having operational data stored in a database rather than manually recorded, are necessary for edge solutions to deliver value. Several indicators can be used to measure digital maturity, including digital spending, the level of digitization in business processes, and the extent of work digitization.
By focusing on industries that are already digitally mature, telcos can strategically target their efforts towards sectors that are better prepared for the adoption of edge computing. Leveraging the existing digital infrastructure and capabilities of these industries, telcos can position themselves as partners in their digital transformation journey, offering tailored edge computing solutions to further enhance operational efficiency, data analytics, and real-time decision-making.
10 edge computing innovators to keep an eye on in 2023
When telcos aim to offer verticalized edge solutions, it is crucial for them to assess enterprise verticals based on various factors in order to determine the optimal target. By evaluating these factors, telcos can make informed decisions and identify the right verticals to focus their efforts on. Here are some key factors to consider:
Key takeaways:
Embracing the boundless possibilities of edge computing, telcos embark on a remarkable journey to weave a tapestry of technological marvels across industries. With an astute understanding of enterprise pain points and a collaborative spirit, telcos forge strong alliances with anchor customers, together venturing into uncharted territories of innovation. Guided by their industry expertise, telcos sculpt tailored edge solutions that seamlessly address challenges, empower businesses, and create transformative experiences.
Like a virtuoso conductor, telcos orchestrate the symphony of edge computing impact, harmonizing connectivity, speed, and intelligence. Through this technological symposium, industries witness a metamorphosis, transcending limitations and unleashing unprecedented possibilities. With each interaction, edge computings influence radiates, amplifying the pulse of real-time analytics, unlocking the gates to low latency, and defying the constraints of conventional computing.
Continued here:
Edge Computing Impact: What Does It Do? - Dataconomy
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