FLUIDOS AT THE EDGE Sample Clauses

FLUIDOS AT THE EDGE. In many sectors (such as industrial control environment, smart city, smart agriculture, etc.), cloud computing has proven unprecedented cost-effectiveness and flexibility to users, nevertheless, it fails in all use cases where latency is important or where the bandwidth is an issue. For such a reason in the coming years, we expect to see more and more applications and services that require moving computation from the cloud to the edge. FLUIDOS at the Edge provides a way to extend cloud infrastructure by creating a continuum to the edge, managing, and deploying applications seamlessly across both cloud and edge environments. The heterogeneity of edge devices largely contributes to the complexity of the task since the Edge can be broken down into 3 sublayers known as Meta Edge, Deep Edge, and Micro Edge. Edge devices belonging to these sublayers can be distinguished according to the degree of distribution and decentralization of the computation. For instance, the devices at the Micro edge, referred to as IoT edge devices, include sensors (e.g., temperature, inclinometer, pressure), MEMS, wired/wireless communication, ADC, microphone, or cameras, with a low cost/low power microcontroller. Deploying containerized applications on edge devices with existing solutions like KubeEdge is a way to build a baseline continuity from the cloud to the edge. However, the vanilla version of KubeEdge has many limitations, including, the limited support of the well-known IoT protocols such as (▇▇▇▇, sigfox, Bluetooth, MATTER), with the associated limitations to manage the heterogeneity of IoT Edge devices. For this reason, FLUIDOS improves and extends several components of the vanilla KubeEdge. Modern IoT Edge devices can share raw sensor data or the computed values with different applications. Such computed data may include simple raw sensor values (e.g., temperature, humidity, …) or the computed outcome of a fusion AI algorithm. It is important to point out that, compared to the current solutions, the developed FLUIDOS at the Edge will enable the multicasting operations for sharing the pre-processed, computed data or raw data between several applications with a single data transmission from the Far Edge to the cloud. This would result in a significant reduction in power consumption, requiring fewer IoT edge devices and reducing the amount of data transmitted towards cloud applications. Managing data at the edge is a challenging task due to the large number of connected devi...
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