Over the past few years, Edge Computing has been a growing topic in big data.
It is simply the process of performing computing tasks physically close to target devices as possible, rather than in the cloud or on the device itself to reduce the load on the core servers and on the network itself, making the overall network more efficient.
This concept integrates intelligence to edge devices, also known as edge nodes, allowing data to be processed and analyzed near the data collection source in real time.
Most companies traditionally store, manage, and analyze data on a centralized storage, may it be in a public cloud or private cloud environment. But through the years, traditional IT infrastructure and cloud computing no longer meet the requirements for most real life applications.
That’s why digital infrastructures are certainly changing. According to Gartner, for example, 80% of enterprises will have to shut down their traditional data center by 2025, versus 10% in 2018.
The growing amount of data and networking layer limitations (computation) currently lead to a decentralized system called Edge Computing.
A deep dive into Edge Computing
Source: Alibaba Cloud
A form of distributed computing, edge computing goes all the way back to the 1960s. It covers a broad range of technologies, but that’s within local area networks and the first internet, called the ARPANET.
The “edge computing” we know today dates back to the late 1990s, when Akamai, an organization that works towards making Internet fast, reliable, and secure, launched its content delivery network to resolve web congestion.
Despite its history, edge computing is still considered a new paradigm, addressing to move computer workload closer to the consumer, to reduce latency, bandwidth and overhead for the centralized data center.
Why Edge Computing?
Through the emergence of billions of IoT devices and 5G networks, edge computing aims to address proximity thus solving problems about latency. This is much important for latency-sensitive applications, like autonomous vehicles.
Overall, it allows clear scoping of computing resources for optimal processing.
Key benefits of edge computing are:
- Improved Security. Traditionally centralized cloud computing architecture is known to be vulnerable to distributed denial of service (DDoS) attacks and power outages, while for edge computing, it delivers processing, storage and applications across multiple devices and data centers making it much difficult for any single disruption to make a network shutdown.
- Better Reliability.There will be lesser chances of network disruptions in distant location affecting local customers, by having IoT edge computing devices and edge data centers strategically positioned closer to end users. IoT edge computing devices will still continue to operate on their own even at the event of a nearby data center outage.
- Incredible versatility. Via local edge data center partnerships, companies can save costs on real time data transmission. Because they can easily target ideal markets without having pricey infrastructure expansion investments. This is much beneficial for content providers who are looking to deliver uninterrupted streaming services. Empowering IoT devices to gather unprecedented amounts of actionable data, edge computing devices are always active, always connected, and always generating data for future analysis.
- Greater Speed. Having to combat latency, IoT edge computing devices process data locally or in nearby edge data centers. Resulting to higher speeds, with latency measured in microseconds rather than milliseconds. It reduces downtime costs for companies.
- Scalability. Companies will have eased growth costs. Having edge computing far less expensive route to scalability, it allows them to expand their computing capacity through a combination of IoT devices and edge data centers.
Edge computing helps companies to break beyond the limitations imposed by traditional cloud-based networks even though cloud computing is still utilized in modern network architecture. It aims to address proximity thus solving problems about latency, thus forcing companies to rethink their approach to IT infrastructure.
It is secured unlike traditional centralized cloud computing architecture, reliable, versatile, fast, and scalable.
By Tuan Nguyen