Autonomic setup of fog monitoring agents
This is an older version of an Internet-Draft whose latest revision state is "Active".
Expired & archived
|Authors||Carlos J. Bernardos , Alain Mourad|
|Last updated||2019-09-12 (Latest revision 2019-03-11)|
|Stream||Stream state||(No stream defined)|
|RFC Editor Note||(None)|
|Send notices to||(None)|
This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:
The concept of fog computing has emerged driven by the Internet of Things (IoT) due to the need of handling the data generated from the end-user devices. The term fog is referred to any networked computational resource in the continuum between things and cloud. In fog computing, functions can be stiched together composing a service function chain. These functions might be hosted on resources that are inherently heterogeneous, volatile and mobile. This means that resources might appear and disappear, and the connectivity characteristics between these resources may also change dynamically. This calls for new orchestration solutions able to cope with dynamic changes to the resources in runtime or ahead of time (in anticipation through prediction) as opposed to today's solutions which are inherently reactive and static or semi-static. A fog monitoring solution can be used to help predicting events so an action can be taken before an event actually takes place. This solution is composed of agents running on the fog nodes plus a controller hosted at another device (running in the infrastructure or in another fog node). Since fog environments are inherently volatile and extremely dynamic, it is convenient to enable the use of autonomic technologies to autonomously set-up the fog monitoring platform. This document aims at presenting this use case as well as specifying how to use GRASP as needed in this scenario.
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)