Edge computing is a distributed computing paradigm which brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth. It is basically a distributed computing framework that brings the enterprise applications closer to the data sources, such as the Internet of Things (IoT) devices or the local edge servers.
Proximity to data at its source can deliver real business benefits like faster insights, improved response times, and better bandwidth availability. Modern edge computing significantly extends this approach through virtualization technology that makes it easier to deploy and run a wider range of applications on the edge servers.
Edge computing helps to unlock the potential of the vast amount of unused/underutilized data that’s created by the connected devices. This can uncover new business opportunities, provides faster a reliable, and consistent experience for customers by increasing operational efficiency.
Top benefits of Edge Computing
- Privacy and Security
- Reliability and Scalability
- Bandwidth Savings
The best edge computing models can help you accelerate performance by analyzing data locally. A well-considered approach to edge computing can keep workloads up-to-date according to pre-defined policies, can help maintain privacy, and will adhere to data residency laws and regulations.
But this process is not without its challenges. A useful edge computing model should address network security risks, management complexities, and the limitations of latency and bandwidth. A viable model should help you:
- Manage your workloads across all clouds and on any number of devices.
- Deploy applications to all edge locations reliably and seamlessly.
- Maintain openness and flexibility to adapt to evolving needs.
- Operate more securely and with confidence.
Why Edge Computing?
The explosive growth of IoT devices, and the increasing computing power of these devices, have resulted in unprecedented volumes of data. And data volumes will continue to grow as 5G networks increase the number of connected mobile devices.
In the past, the promise of cloud and artificial intelligence (AI) was to automate and speed innovation by driving actionable insight from data. But the unprecedented scale and complexity of data that are created by connected devices have outpaced network and infrastructure capabilities.
Sending all that device-generated data to a centralized data center or to the cloud causes bandwidth and latency issues.
In Edge computing, data is processed and analyzed closer to the point where it is created. Because data does not traverse over a network to a cloud or data center in order to be processed, latency is significantly reduced. Edge computing — and mobile edge computing on 5G networks — enables faster and more comprehensive data analysis, creating the opportunity for deeper insights, faster response times, and improved customer experiences.
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