In an interaction with CXOToday, Mr. Somenath Nag, VP – Marketing & Corporate Strategy, Calsoft discusses more about the Edge computing
Q1. What is Edge computing and why it is important?
Edge Computing processes move computational capabilities closer to the location where the data originates. This distributed computing model uses different components to process the data in real-time, including devices such as Internet of Things (IoT) devices or sensors to collect data, and edge Data Centre (DC) infrastructure for networking, storage, and computing.
Edge computing is important as it plays a significant role in the digital transformation, and it can create more innovative industrial and enterprise services. The processing of massive amounts of data generated from the diverse set of IoT devices at the edge reduces end-to-end latency. This, in turn, increases operational efficiency as well as the overall performance. Integration of edge computing with key technologies such as 5G, Artificial Intelligence (AI), and blockchain makes it more consistent and easier to manage.
Q2. Difference between Edge computing, Cloud computing and Fog computing?
Industries can process a huge amount of data from heterogeneous sources utilizing fog, edge or cloud computing infrastructures. While these technologies sound similar, they are different layers of computing which complement each other.
In Cloud computing, the computation capabilities are hosted at remote DCs, or managed on the Cloud by a Cloud Service Provider (CSP). Computing resources are available on-demand through internet access, and there are different models to deploy cloud services such as public cloud, private cloud, and hybrid cloud.
Fog computing and edge computing, on the other hand, are similar – the main difference is in the location where the data processing happens locally. In edge computing, the data processing, compute power and intelligence can be hosted in edge devices like sensors. Whereas in fog computing, the local data processing and intelligence takes place at processors in the Local Area Network (LAN), remote from the edge devices.
Q3. What are the benefits of Edge Computing?
Edge computing processes bring the compute power and intelligence of remote core DCs close to end devices. This has several benefits, including:
- Supporting higher data-rate and low-latency applications: Edge computing eliminates the need to transfer data from edge devices to core DCs for processing. The total volume of traffic flowing to and from remote DCs is reduced by keeping the computation at the network edge. This reduces the overall end-to-end latency and enhances response time.
- Enhancing security and reliability: The most important data is only transferred to the remote DCs from the edge. When the data is distributed across different servers, the effect of Distributed Denial of Service (DDoS) is reduced. The edge computing processes can filter and remove unwanted data, making it more secure and reliable.
- Increasing Scalability: With the proliferation of IoT devices, distributed computing is required for the processing of massive amounts of data from these devices. The computing capabilities can be hosted on edge devices to easily manage the data.
- Reducing operational costs: With edge computing, most of the data can be stored locally, eliminating the need for expensive backhaul connectivity to send the data to the cloud. Only the most critical pieces of data are sent to the core DCs. This optimizes bandwidth consumption, further reducing operational cost.
- Supporting AI/ML applications: To provide valuable insights, AI/ML applications require processing power. Edge computing places AI/ML application close to the data collection points, enabling near real-time analytics.
Q4. What is the relationship between Edge computing and 5G?
5G and edge computing are two inseparably linked technologies that can realise next-generation industrial applications. 5G is expected to support Ultra-Reliable Low Latency Communication (URLLC) for applications such as autonomous cars, healthcare, smart factories, and more.
Edge computing becomes a key enabler for 5G to realise such latency-critical services. It can reduce the bandwidth consumption of the backhaul link in the telecom infrastructure, decreasing costs and latency. 5G, when combined with edge computing, can bring new revenue streams to the market. The advent of cloud-native solutions encourages telco service providers to migrate to innovative service models. The emerging trend of Private Network deployments can be enabled by 5G, by using edge computing technology. Private networks demand on-premises infrastructure to host telco workloads to enable reliable and secure connectivity.
Q5. Give some examples of Edge computing
As a result of 5G adoption, digital technology is progressing at a rapid pace, and this has opened several avenues for Edge computing in industry-specific use cases. Here are some of the most important ones:
Optimizing Networking– Mobile network virtualization is progressing rapidly, and Edge computing is a major part of it.
The process involves optimizing network performance by measuring user performance across the internet. Consequently, the use of analytics helps to determine the most reliable, low-latency network path for each user’s traffic. Effectively speaking, Edge computing is used to “steer” traffic across the network for optimal time-sensitive traffic performance.
Manufacturing– By leveraging Edge computing, manufacturing industries are now able to monitor assets remotely, provide real-time analytics, and perform predictive maintenance well in advance.
When sensors are deployed on the Edge, their ability to interact with each other is enhanced, providing a number of benefits. It increases transparency in manufacturing processes, enables leaders to monitor quality, and enhances decision-making capabilities.
Healthcare– One specific area where the implementation of edge computing is rising exponentially is the Healthcare segment, especially in the current post-pandemic world. From remote patient monitoring to real-time patient care, healthcare is truly being federated thanks to edge computing.
Retail- Be it geospatial notifications, usage of beacons, asset management, or inventory management, edge computing is there to enable the industry to effectively and efficiently plan for the days/months to come.
Smart Automotive– Edge computing once again comes to rescue, helping make sense of telemetry data gathered from various cameras and sensors, enabling drivers to make decisions in real-time scenarios.
Q6. How does edge computing affect security?
Edge computing provides several benefits, but it is certainly not without its challenges. With millions of devices and sensors being onboarded to OT devices, it becomes increasingly easy for them to be exposed to vulnerabilities and threats. The major risk factors here involve:
- A lack of passwords and authentication protocols exposes several vulnerabilities, especially when it comes to newly onboarded devices.
- Data sprawl is another major issue, wherein devices become hard to track and monitor as they cross the boundaries of edge bandwidth.
While it might seem like an arduous task to thwart these security challenges, they can be easily mitigated by implementing Zero Trust Security Access. By implementing Zero Trust Security, it becomes easier to implement a narrow set of security protocols on top of IoT devices.
Businesses/organizations can further mitigate security threats by implementing these guidelines:
- Network Administrators must be able to see the entire network
- Data must be encrypted both in transit and at rest
- Automated monitoring tools must be installed
- Data and network resource access must be restricted
Q7. Does Edge computing contradict the federal cloud smart strategy?
Contrary to popular belief, Edge computing does not contradict the federal cloud smart strategy. Rather, edge computing is enabling the Cloud smart strategy by bringing the cloud native functionalities closer to the public. We do so by modernizing existing infrastructure and applications and implementing security measures. This is further complemented by hiring the right set of competent workforces, ones that bridge the gaps between current and future skill gaps. Also, by procuring the right resources at the right time while adhering to Service Level Agreements (SLAs) and edge security requirements, we can make sure that Edge computing will be a strong system of support for the federal cloud smart strategy.