Edge Computing: Have you ever wondered how a self-driving car instantly decides to apply the brakes when an object comes in front of it? Or how about a smart home that automatically adjusts the temperature before you even realise it’s too hot or too cold? The cutting-edge technology behind these split-second decisions is ‘edge computing’. In this article we will explore game-changing technology and its potential to transform everyday life.
Edge Computing Highlights
- The global market size for edge computing was valued at USD 16.45 billion in 2023. (Source: Grand View Research)
- The projected growth of this huge market is expected to grow at an annual growth rate (compound) of 36.9% from 2024 to 2030. (Source: Grand View Research)
Image Source: Grand View Research
- By 2026, a little above a quarter of the edge sites in the global network will be in China. (Source: STL Partners)
- Sectors that will deploy edge computing the most are media, transport and manufacturing industries, amounting to almost 84% of the market size by 2030. (Source: STL Partners)
- Edge computing poses a higher security, despite the innumerable benefits it offers.
- Despite the gigantic budgets, technology is never without challenges and loopholes. Why is it so difficult to build something completely positive in this world?
What is Edge Computing?
Edge Computing: To truly understand edge computing, it’s important to first understand how data is processed and transferred. In any digital system, data is the core. Data means facts, observations or information gathered from our surroundings, people, machines or devices.
Traditionally, this data is sent to be stored, managed and processed by centralised servers in the cloud. This process is known as cloud computing. However, the cloud is not where the data originates. Data comes from everyday devices, machines and sensors all around us. In cloud-based systems, data must travel all the way to these distant servers for processing, which means decisions can’t be made locally, or at the ‘edge’.
Image Title: Diagrammatic Representation of Edge Computing
Image Source: CB Insights
‘Edge’ stands for the outer edge of a network where the devices actually interact with the world. When data travels to and fro from cloud systems, it creates delays that can be critical in situations where real-time responses are needed, like in self-driving cars or smart homes. Edge computing solves this by allowing devices to process data right where it’s collected, leading to faster, more efficient decision-making.
Edge Computing versus Cloud Computing
Edge Computing: Cloud computing and edge computing differ primarily in their approach to data processing and storage. Cloud computing has dominated the IT industry for years. It involves storing and processing data in centralised data centres managed by service providers like Amazon Web Services (AWS), Microsoft Azure or Google Cloud. Cloud computing offers flexibility, scalability and the ability to store vast amounts of data. However, because the data has to travel from the point of origin to the cloud, there can be significant latency in time-sensitive applications.
Image Source: Orient
Key Differences:
- Location of data processing:
- Cloud computing processes data in centralised locations, which could be geographically distant from the user or device generating the data.
- Edge computing processes data at or near the source, minimising the need for data to travel long distances.
- Latency:
- Cloud computing often results in higher latency since the data has to be transmitted to the cloud and back.
- Edge computing significantly reduces latency by processing data locally, allowing for real-time responses.
- Bandwidth usage:
- Cloud computing consumes more bandwidth as data is continuously sent to central servers for processing.
- Edge computing optimises bandwidth usage by reducing the amount of data transmitted to the cloud, only sending relevant or filtered information.
- Security:
- Cloud computing places data security in the hands of large providers but introduces vulnerabilities during data transmission over the internet.
Edge computing can enhance security by processing sensitive data locally, reducing exposure to external threats during transmission.
Mechanism of Edge Computing
Edge Computing: Edge computing functions by shifting data processing from a central data centre to devices and servers located closer to the user or data source:
- This is achieved by embedding computational resources within devices such as routers, gateways or local servers.
- These devices act as intermediaries, performing preliminary data processing before sending selected information to the cloud for further analysis if needed.
Image Source: Akamai
For example, in a smart factory setting, sensors embedded in machines can collect real-time data about production performance and monitor safety both. Instead of sending all this data to a cloud server, edge devices can process and filter it locally, identifying critical insights such as potential equipment failures or inefficiencies. By making decisions locally, latency is reduced, allowing for real-time control and improved operational efficiency.
Systems Within the Edge Ecosystem:
Edge computing architectures often involve a combination of devices like:
- Edge nodes: Localised servers or gateways that process data closer to the source.
- IoT (Internet of Things) devices: Sensors, cameras or other devices that generate and sometimes process data.
- Microdata centres: Smaller, localised data centres that handle edge workloads without relying on centralised cloud systems.
- Network infrastructure: Routers, switches and other networking equipment that facilitate data transmission between edge devices and the cloud.
Image Title: ‘Defining the edges in edge computing, from edge devices to the network edge and public or private clouds.’
Image Source: IBM
These components work together to ensure that data is processed quickly and efficiently, especially in environments that cannot tolerate latency or delays.
Advantages of Edge Computing
- Reduce data: As edge computing processes data closer to the origin of data, it helps in reducing the large volume of data that overburdens cloud systems and is challenging to store as well.
- Reduced latency: Edge computing allows for actions to be taken at times even less than a millisecond as there is no back and forth of data from cloud systems to devices .
- Faster bandwidth: By eliminating the travel of data to faraway servers, reduces the load and consumption of bandwidth. This in turn saves money.
- Edge AI: The integration of Artificial Intelligence in edge systems is proving beneficial especially in industry or devices with minimal tolerance for latency.
Industrial Applications of Edge Computing
Edge computing is crucial in several industries and applications. Here’s a brief look at some industries:
Autonomous vehicles:
Real-time processing is required for self-driving cars to make instant decisions based on sensory data. Edge computing reduces latency, allowing vehicles to respond faster.
Image Title: Depiction of an edge system for autonomous cars.
Image Source: Lanner Inc
Healthcare:
Edge computing is used in innumerable applications within the Healthcare industry.
- Remote monitoring of patients: Wearable devices can monitor vital signs and process data locally with the patient’s blood pressure, heart rate, glucose metres, etc.
- Smart hospitals: A medical care facility can be set up including IoT devices like sensors, wearables and similar medical equipment. The data gathered from these devices can enable hospitals to optimise facilities and operations.
- Predictive analysis: Early prevention of medical occurrences can be prevented in patients through real-time analysis of patients medical data. This can help hospitals provide personalised services preventive care to patients.
- Emergency care: Wearables and other specialised devices can trigger alerts for medical emergencies like sudden fluctuations in blood pressure, heart rate, etc. Hospitals can use proactive measures to treat patients in such cases.
- Clinical trials: Edge devices can aid collection and analysis of data during clinical trials. This would ultimately lead to better diagnoses and treatments for patients.
- Robotic surgeries: Though this might sound absurd, integrating edge computing technology in surgical robots, can help doctors with more precision in surgeries.
Image Title: A proposed edge computing based secure health monitoring framework
Image Source: An abstract ‘Edge computing based secure health monitoring framework for electronic healthcare system’ by Ashish Singh and Kalki Chatterjee, Springer Link
Smart cities:
Edge computing helps smart traffic systems, surveillance cameras and utility monitoring devices operate in real-time by processing data locally.
- Traffic management: Live data on traffic conditions can be gathered from sensors and cameras. The information can help traffic authorities devise efficient traffic management strategies.
- Air traffic management: Edge devices can be deployed to analyse weather conditions and other factors that impact flight landings and take-offs. It offers a chance to improve efficiency of operations and reduce delays.
- Public transport: Edge computing can be used to collect data about commuter loads, peak hours, preferred routes, etc. This information can be used to lessen overcrowding during peak hours, on-time running of trains and buses, and also reduce on-road congestion.
Image Title: Representation of Edge Computing for Smart Cities
Image Source: TechTarget
Retail:
- Customer experience: computing in smart retail systems can enhance customer experiences by analysing foot traffic or managing inventory locally, providing immediate insights.
- Inventory management: Real-time data can help avoid out-of-stock situations, especially in the FMCG and perishable goods industry.
- Supply chain management: Edge devices installed on storage shelves can alert organisations with real-time data of low stock on shelf. This would help in ordering replacements immediately and optimise the entire supply chain.
- Smart checkout: Shopping carts can be edge-enabled through tracking devices that can configure the number of items and even bill them for clients, ensuring a smooth checkout.
Image Title: Graphic Representation of The Use of Edge Computing in The Retail Industry
Image Source: Lume
Agriculture:
Edge computing has tremendous scope in the agricultural sector.
- Crop management: Sensors on farms can help farmers track moisture levels in soil, humidity, temperature, and other decisive factors real-time. Using this data, farmers can make effective decisions on planting, irrigation, fertilisation, etc.
- Pest management: Similarly, edge devices can support in real-time tracking of any pest infestation. This data can not only help tackle pests early on, but also treat only the specific infested area, instead of spraying chemicals on the entire field.
- Weather forecast: Weather conditions have a bearing influence in farming. Edge computing can deliver real-time weather forecasts to farmers.
- Monitoring food quality: Farmers can improve the quality of their produce through edge computing technology. This also helps access whether the produce meets approved standard guidelines.
Image Title: Depiction of an edge-based agricultural system
Image Source: Chapter 5 – Functional framework for edge-based agricultural system, by S. Premkumar and A.N. Sigappi, ScienceDirect
Can Edge Computing Replace Cloud Computing?
Edge computing is not intended to fully replace cloud computing, but rather to complement it. Both paradigms have their strengths and are suited to different types of applications. While edge computing excels in use cases that demand low latency, real-time data processing, and localised computing power, cloud computing still remains indispensable for large-scale data storage, analytics and more complex computational tasks.
For example, while a smart home device might use edge computing to process voice commands locally for faster response times, it might still rely on cloud computing for software updates, long-term data storage or advanced AI analytics.
■ Also Read: The Future of IT: How Cloud Computing is Reshaping the Digital Landscape?
In short, edge computing can offload specific tasks from the cloud, reducing latency and improving efficiency. However, cloud computing’s global reach, scalability and capacity for handling complex workloads ensure its continued relevance. The future likely involves a hybrid approach, where edge and cloud computing are used together, each performing the tasks best suited to its capabilities.
Dangers of Edge Computing
While edge computing offers several advantages, it also introduces some risks:
- Security vulnerabilities: Decentralising data processing leads to an increased cybersecurity risk as it opens more potential entry points for cyberattacks, especially on less-secure IoT devices.
- Data integrity and consistency: Managing data across multiple edge devices can lead to inconsistencies if not properly synchronised.
Image Title: Security and Privacy Attacks in Edge Computing
Image Source: Researchgate
Citation:
TY – JOUR
AU – Singh, Shivani
AU – Sulthana, Razia
AU – Shewale, Tanvi
AU – Chamola, Vinay
AU – benslimane, abderrahim
AU – Sikdar, Biplab
PY – 2021/07/13
SP –
T1 – Machine Learning Assisted Security and Privacy Provisioning for Edge Computing: A Survey
VL – PP
DO – 10.1109/JIOT.2021.3098051
JO – IEEE Internet of Things Journal
ER –
- Cost of implementation: Setting up and maintaining edge infrastructure can be expensive, especially for smaller organisations without the resources to invest in new technologies.
- Device failure: Since much of the processing is offloaded to localised devices, hardware failure at the edge could disrupt operations or cause data loss.
The Double-edged Sword
The biggest threat to edge computing is the looming risk of security breaches. Despite its groundbreaking advantages, this technology is not immune to data hackers. Imagine the terrifying scenario of an autonomous vehicle being hacked. The passengers would be trapped, unable to even unlock the doors as even that process is automated and now controlled by the hackers.
Why is it that, no matter how remarkable our technological advances, there’s always a downside? Why can’t we experience only the positives?
The answer to this question touches on something much deeper – a spiritual truth that most people are unaware of. While science and spirituality may seem worlds apart, the reality is that we cannot separate spirituality from any aspect of our lives, whether we acknowledge it or not. This profound connection between the two holds the key to understanding why even our greatest innovations come with risks.
Our Journey to This Imperfect World
We’ve been conditioned to believe that life is a constant cycle of ups and downs, leading us to accept that tough times are inevitable. For centuries, we’ve resigned ourselves to this idea, believing there’s no alternative.
However, Jagatguru Tatvadarshi Sant Rampal Ji Maharaj has revealed the existence of another realm – a place where sorrow, obstacles and challenges simply do not exist. And this isn’t just a comforting tale or wishful thinking. Sant Rampal Ji Maharaj has backed His revelations with undeniable proof from our ancient holy scriptures. No other spiritual teacher could ever spot this evidence except Him.
Satlok, the eternal and indestructible realm of our Ultimate Creator, Supreme God Kabir, was once our original home. In this divine abode, everything operates on the unmatched powers of Supreme God Kabir, far surpassing any human technology. While on Earth, we struggle to build complex systems just to process simple data, in Satlok, the entire realm functions effortlessly, without its residents needing to lift a finger or even think about it. Such is the omnipotence of God Kabir.
But how did we fall from such a perfect paradise to this world of suffering and impermanence? What events led to our exile from Satlok, the realm of eternal bliss, to this temporary land filled with pain and struggle? Uncover the complete truth our existence and the choices that distanced us from the place of ultimate joy, through the impeccable insights of Sant Rampal Ji Maharaj:
Edge Computing FAQs
Question: What are examples of edge computing?
Answer: Autonomous vehicles, smart grids, monitoring of patients with edge technology devices are some examples of edge computing.
Question: Is a smartphone an edge device?
Answer: Yes
Question: Who invented edge computing?
Answer: Akamai is believed to have invented edge computing.
