Edge Computing Powering Small Devices
Imagine a self-driving car needing real time data processing for a decision in the vicinity of microseconds and just then at the niche of the time latency seeps in. The time-lag in data stream acceleration transmitted via a data centre can result in latency. This critical feature can become a death nail for the entire ubiquitous need of AI in our lives. The general contemplating that went to make cloud a phenomenon is getting localized-both
in space and concept wise. The notion of cloud computing stands to host network of remote servers on the internet itself to process data and manage. The practicality of building and creating cloud storages for such applications that need immediate data processing and analytics highlights the need of Edge Computing, the literal meaning of which can bring wonders to the entire domain of IoT and smaller device and remote datacentres.
The concept of data management, and analytics when bought at the front door of the device’s networks, the idea of data processing without time lag, boosts the whole Edge Computing to an entire level of speed and supremacy.The USP of Edge Computing lies in the fact that data processing with heavy duty data can be efficiently processed near the source, thereby, reducing cost and time both.With such strong concept out in the open, the practicality of confronting Edge Computing to its full potential is still at large. In an upcoming International Conference on Edge Computing (EDGE) 2018, several major topics shall be discussed. Primarily the Communication among Edges of an Edge Computing System, workflow changes, security and reliability. While this concept is in its nascent stage, the lifecycle of services innovation shall get a makeover within AI-driven ubiquitous services. EDGE 2018 is as such a promising platform to unravel few blockheads before Edge Computing takes on the Cloud Computing and become the prerequisite to power small and large IoT devices.