Key Criteria to Move Cloud Workloads to the Edge
INTRODUCTION
In today ’ s networks , most compute workloads run in cloud data centers . This is changing , as many critical requirements are not met in the cloud , and a many of these workloads are moving completely or in part to edge computing .
The Industrial Internet Consortium ( IIC ) defines 1 edge as : “ boundary between the pertinent digital and physical entities , delineated by IoT devices ”. It further defines edge computing as : “ distributed computing that is performed near the edge , where the nearness is determined by the system requirements ”. Basically , edge computing is about taking a carefully selected subset of the computational workloads , storage capabilities , and networking infrastructures typically found in cloud data centers and moving them physically and logically closer to the sensors , actuators , and other IoT devices that generate and use the data .
There are many edge architecture philosophies . The Cloudlet work at Carnegie-Mellon university is one of the earliest examples 2 . Fog computing is another example , as exemplified by the work of the OpenFog Consortium ( now part of IIC ) and the IEEE 1934 – IEEE Standard for Adoption of OpenFog Reference Architecture for Fog Computing 3 . The European Telecommunications Standards Institute Multi-access Edge Computing ( ETSI MEC ) 4 is growing in influence . The edge computing architecture variant we will focus on in this paper is described in detail in IIC ’ s “ The Industrial Internet of Things Distributed Computing in the Edge ” whitepaper 5 .
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- 2 - June 2021