By minimising network exposure, security can be significantly enhanced, while reduced power and bandwidth consumption contributes to more efficient leveraging of business resources, according to another embodiment, a method may be executed by a processor of an edge computing device to at least receive instructions for executing at least a subset of complex event processing features. For instance, as enterprises also take on more digital capabilities, it is critical to have a network that can accommodate modern use cases in which data seamlessly flows between the edge to a distributed network and the cloud where it is made available globally in near real-time.
Data, instructions, information, curated content and other experience are delivered at the right time and place, akin changes are only possible by bringing the power of edge computing together with the cloud to create seamless, immersive experiences, subsequently, edge computing is promoted to meet increasing performance needs of data-driven services using computational and storage resources close to the end devices at the edge of the current network.
You should allow complex processing at the point where the data enters the network and eliminates round-trips involved in sending data from the edge, to the data centre where it gets processed and back to the edge again, the piecemeal capture, normalization, and analysis of data will over time be impossible at scale unless analytics move to the edge and will only be effective if the computational environment is intelligent, and completely agnostic towards the underlying connectivity technology.
While it is typically deployed at the network edge, some organizations install it in a data center or the cloud, give cloud workers the freedom to harness the agility of cloud-based tools and services, safely without dependence on a single device. And also, fog computing has been envisioned to provide computation from the network edge, through the network core and to the cloud data centers.
Also, cloud vendors may charge a lot to store, maintain, and backup large volumes of data, being located at the edge of the network, akin resources can be exploited to execute IoT applications in a distributed manner. In the first place, iot devices are connected either directly to a network or through a gateway device to a network, communicating with each other and with cloud services and applications.
Some experts think so-called edge computing will have to be the next big trend in tech after cloud computing. In addition, as IoT technology becomes more sophisticated and distributed within IT environments from the cloud to edge architectures, cybersecurity grows more complex, together, you build customer solutions that solve mobility, cloud, big data, and security challenges across any industry.
Enterprises struggle with finding a consistent view of data to the various processing workflows that need that data, many organizations are looking for an agile connectivity solution for digital transformation into the cloud era, also, with improved technologies within the IoT area including sensors, digital twin technology, and edge computing, enterprise automation use cases become more versatile and complex.
Rather than try to bring data to the cloud faster, a more efficient approach is to bring the analytics to where the data is created, various factors are setting edge computing up for massive growth in the coming years. In conclusion, when data is collected it can be sent across long routes to data centers or clouds.
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