Edge Computing

What is Edge Computing?

Topics Covered

1. What is Edge Computing?
2. Need of Edge computing
3. Benefits of Edge Computing
4. Potential industries using Edge Computing
5. Challenges of Edge Computing

We all know about data existing in the cloud, but have we ever wondered from where this data comes from? Indeed, we use existing data in the cloud and process it with different software which further helps in performing analytics, but we never cared about the origin of the data.  Of course, the data is created by humans in our operating environments while interacting, computing, or performing various tasks. With time, everything upgraded including the information and its computing demands. The rise of real time computing demands has forced the technology drivers to rethink on the cloud computer architecture and relocate it from centralized to distributed servers. Thus, the concept of Edge computing came into action.

What is Edge Computing?

The computing that occurs by placing workloads at the edge of corporate networks where the data is being created is known as Edge Computing. The “edge” is defined as the position where the end devices can access the rest of the network devices like laptops, phones, desktop, machines, routers, and sensors. This technology is used to connect IoT devices so they can deliver data efficiently, receive instructions quickly, and download software updates from a cloud or a data center without any hassle. Edge computing is a new approach to network architecture where first in cloud computing continues to play an important role and secondly the new possibilities offered by IoT devices which are capable of processing the data are forcing companies to rethink their approach to IT infrastructure. Edge devices collects, sorts, and performs the analysis of the data and after processing stores the data it to its destined place.

“Edge Computing is an open distributed computing paradigm that ensures speedy computation, handles data activities, network operations and data storage. It brings the devices closer to the place as a result improving the post time and saving bandwidth. It features decentralized processing power enabling mobile computing and Internet of Things.”

The Edge computing data is either processed by the device itself or by a local computer or server rather than being directly transmitted to a data center. The data computing occurs at the Edge of the device or at the location where data is generated. Thus, it significantly improves the speed of data processing by reducing the data travelling between devices and centralized cloud data centers.  This technology opens a platform for us to communicate into the premises where the work is performed unlike the warehouses, retail store, supermarket, banks, etc,.With the outbreak of the Internet of things or IoT devices, there is a bulk of data present in the centrally located data centers or cloud. Hence, it requires larger and expensive connections to maintain the sheer volume of data. The work performed by these IoT devices creates a need for much faster connections between the data center or cloud and the devices.

For example, in a petroleum refinery station, the valves' sensors detect the dangerously high pressure in the pipes. In that case, the shutoff for the supply of petroleum must be called off immediately. The automatic shut may delay the shutoff process as it takes time to analyze that pressure taking place at distant processing centers. But we can prevent this delay by placing the processing power locally to the end devices. It will minimize the latency, reduce the roundtrip time, and will save the downtime. Thus, causing less damage to man, money, and material. 

The key component of cloud computing is to maintain the security and balancing the stability if there is any failure in its connections. In case of Edge Computing as well, security is at utmost importance as these devices come across various network elements and hold confidential data, if exploited, could compromise other devices as well that contain valuable assets. Edge computing makes sure that the edge devices themselves become a single point of failure network architect by building redundancy and provide failover contingencies in order to avoid crippling downtime.

The edge computing devices are Raspberry Pi 4 B Model, LattePanda Alpha, UDOO Bolt, Jetson Nano (Nvidia), and Intel Neural Compute Stick 2.

What is Need of Edge Computing?

For over a decade centralized cloud computing was consistent and has revolutionized a standard platform to read, write, store, and fetch data. It has a strong data centric architecture where resource storing, and computational operations were efficient and scalable. The cloud has become an indispensable part of data processing and storage.  

But with technology and internet, the era witnessed colossal growth of information known as ‘Internet of Things’. IoT generates incomplete data, which further needs to be processed and answered in a very short time. Resulting with a sudden rise in real time computing demands but with cloud computing the cost for generating the data also increased exponentially. However, the cloud that has been centrally linked on a global scale to process enormous data. Besides, if the physical distance between the user and the cloud increases, it raises the transmission latency and increases the response time, as a result stressing out the user.

On top of that, cloud has only some limited access. Network convergence, streaming videos and internet usage continues to trend towards bandwidth insensitive content, offline access to programs and latency sensitive applications in an increasing demand for cloud services. The solution to these problems is to relocate the cloud computing and data storage to Edge Computing Platform. The edge computing platform works by allowing application processing to be performed by a small edge server position between the cloud and the user. The network edge lowers the data transport time and increases the availability. The objective of this technology is to compute logics and data to edge network so the data will not return to the central server every time the function is execute by an IoT device. This technology allows some of the workloads to be offloaded from the cloud server and push it closer to the user’s devise for processing. Thus, speeding up application’s response time and maintains a low latency response.

Cloud Computing V/S Edge Computing

Edge computing is known as one of the new trendsetters that have raised 5G Wireless technology. Indeed, 5G entails an enormous group of networks wired together with optic fiber connections to provide transmitters and base stations with prompt access to digital data. People often uses cloud computing and edge computing interchangeably. But both are diverse and have different functionalities as given below:

Benefits of Edge Computing

1. Real Time Data Processing: This is the core objective of edge computing. Since the data computing happens locally that can achieve real time data processing. The economical monitoring approach of real time processing prevent many concerns even prior of their occurrence.
2. High Speed and low latency: The data is not traveling every time to cloud server network can greatly reduce latency and can enhance data processing performance. When data is connected closer to the user, information can be shared quickly, securely and without latency. Edge computing is combined with 5G, as a result reducing the latency to 1 millisecond.
3. Reduced Internet bandwidth usage and associated cost: Edge can significantly reduce internet bandwidth usage and cost. Since the data processing happens at the edge network. The server resources are free most of the time and can be utilized in other cloud specific operations hence it can reduce server resources utilization and is associated cost.
4. Responsive and Robust Application Performance – Responsive and robust application performance can be achieved by uploading the processing logic to local edge environment. Therefore, it improves the business efficiency and reliability by doing critical operations in local environment without feeling about network disconnect for response time out.
5. Distributed Security – The key advantage of the Edge computing is that it processes the data locally. Thus, minimizing the direct interaction with the cloud. As a result, it reduces the risk of DDoS attacks that cripple networks and maintains the security.
6. Increased Reliability – Micro data centers operate in all manner of environments due to which the interruptions occurring due to internet and cloud are gone. Edge Computing brings everything closer to the user and supports robust, secure, and intelligent on-premise infrastructure.

Potential Industries Using Edge Computing

Below are the top 10 industries where edge computer can be a game changer by looking at their use cases:

1. Banking and Insurance

With banking business data and processes are most critical things and Edge can play vital role in improving the overall service performance.

• Health care

Real-time information is so important that they cannot compromise with it, such as tracking patient health conditions, monitoring of hospital equipment, active drug tracking, improved fitness, and wellness for users. It also enhances wearable Healthcare Devices for Real-time Data Analysis.

• Energy sector

Oil fields and mines, where edge computing can help to do real-time tracking of worksite safety conditions tracking equipment conditions critical sensor with drilling device conditions monitoring.

• Travel Transport

Edge computing is bliss and incredibly useful for real-time autonomous vehicle control and monitoring. This technology facilitates vehicle scheduling, route tracking, logistics tracking, and equipment efficiency. It also enhances vehicle performance by collecting real-time data on the road. It also facilitates vision Recognition with Deep Learning Algorithm to ensure lane Traffic Congestion Control.

• Infrastructure Development

Edge computing can play a vital role in the development of infrastructure and big construction projects. It can measure the real-time worksite safety condition, maintain the proactive equipment operations, and track a worker's real-time activity.

• Airlines and shipping industries

Edge computing has a good scope in the airline industry. This technology facilitates real-time weather forecasting, safety equipment monitoring, analysis of the inner airplane environment, and report immediately if anything goes wrong. Thus, prevents and remedy even before any problem has occurred. Edge Computing has also impacted satellite functions such as telecom monitoring, weather patterns, ship route navigation, tracking UPS, and shipping containers.

• Public Sectors

In smart cities, a healthy and safe lifestyle involves ample elements. Edge computing has affected citizens' lives by monitoring air quality, traffic check, congestion monitoring, smart parking, water meters management, tracing water leakage, monitoring water quality, etc.,

•  Manufacturing

In the manufacturing sector, edge computing can perform real-time monitoring production, maintain line tracking safety, and track production control improvement.

• Agriculture

In India, agriculture is the primary source of income for most of the citizens. Improving the agriculture sector directly impacts the life of agriculturists. Edge computing monitors the soil condition, sensor-based data collection for Agriculture Industry, track the growth of plants, rain prediction, etc.

1. Retail

In the retail sector, edge computing facilitates real-time inventory tracking and optimization using collected ID billing of material handling store, energy management, CRM data management for leads generation. It also provides logistics Container condition and tracking.

Challenges of Edge Computing

1. Colocation Cloud Data Centers: The method of private housing servers and networking devices in a third-party data center is Colocation. To ensure smooth edge computing operations, the cloud provider would require setting up or collaborate with local data centers, which itself will bring a lot of challenges in terms of data virtualization and replication.
2. 5G Technology: 5G wireless technology ensures the delivery of high-speed data, decreased latency, increased reliability, availability, and vast network capacity. Thus, enhancing user experience to a greater experience. 5g working is required to accelerate real-time applications such as video processing, autonomous cars, AI intelligence, deep learning, and robotics. But indeed, it a challenge for the developers to maintain the 5g technology and provide all the features without any hindrance.
3. Strong Security Management: Strong data secret tools and policies play a major role data for Edge Computing. The securing could be a challenge and troublesome, especially when handled by different devices that might not be as secure as a centralized cloud-based system.
4. Continuous Local hardware Maintenance: With edge computing, the number of edge devices also increases. Thus, it involves large investments and more maintenance costs.  
5. Network Connectivity and Electrical Power Management: Edge computing requires uninterrupted network connectivity and electrical power management because different edge devices require different processing power and network connectivity.