Edge computing brings computing closer to source of data like IOT devices. This improves the operations of a business by reducing latency and bandwidth use. In other words, it is a way of running fewer processes in the cloud and moving those processes to local places, such as on a user’s computer, an IoT device, or a local edge server. Increasing number of IOT devices and computing power of those devices is generating a large volume of complex data. But the unprecedented scale and complexity of data that’s created by connected devices has outpaced network and infrastructure capabilities. Therefore, using traditional data center causes bandwidth and latency issues.
Edge computing offers a more efficient alternative; data is processed and analyzed closer to the point where it’s created. Because data does not traverse over a network to a cloud or data center to be processed, latency is significantly reduced.
According to industry experts, it is estimated that by 2023 over 50% of new enterprise IT infrastructure deployed will be at the Edge rather than corporate datacenters, up from less than 10% in 2020; by 2024, the number of apps at the Edge will increase 800%
Data Handling and Security – Edge Computing
Every class of edge device has different processing capabilities in terms of compute and storage. This ranges from running embedded programs for device controls, performing business rule execution, to executing models that support complete business solution platforms. We classify data handling into the following broad categories:
One of the consequences of edge adoption is the need for new security paradigms and controls, in order to protect data and applications at the edge. Existing security mechanisms do not work well with distributed architectures, computing spread among multiple locations, and when most data is created, processed, and consumed at the edge without entering the central data center perimeter. Security at the edge can be examined at various levels, such as physical, internal or network related. The security risk areas can be classified as follows, even if specific edge devices may demand different types of security measures
Edge Software Frameworks
Edge frameworks support two main aspects of edge devices. First, they provide a platform to provision and run workloads near to the source of data with full lifecycle support. Second, they provide the means to orchestrate such workloads. State-of-the-art edge frameworks have the following characteristics, and provide features that enable critical device functions:
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