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Dynamic-Anycast (Dyncast) Problem Statement and Use Cases

Document Type Replaced Internet-Draft (individual)
Expired & archived
Authors Peng Liu , Philip Eardley , Dirk Trossen , Mohamed Boucadair , Luis M. Contreras , Cheng Li , Yizhou Li
Last updated 2023-01-09 (Latest revision 2022-07-08)
Replaced by draft-liu-can-ps-usecases
RFC stream (None)
Intended RFC status (None)
Stream Stream state (No stream defined)
Consensus boilerplate Unknown
RFC Editor Note (None)
IESG IESG state Replaced by draft-liu-can-ps-usecases
Telechat date (None)
Responsible AD (None)
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This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:


Many service providers have been exploring distributed computing techniques to achieve better service response time and optimized energy consumption. Such techniques rely upon the distribution of computing services and capabilities over many locations in the network, such as its edge, the metro region, virtualized central office, and other locations. In such a distributed computing environment, providing services by utilizing computing resources hosted in various computing facilities (e.g., edges) is being considered, e.g., for computationally intensive and delay sensitive services. Ideally, services should be computationally balanced using service-specific metrics instead of simply dispatching the service requests in a static way or optimizing solely connectivity metrics. For example, systematically directing end user-originated service requests to the geographically closest edge or some small computing units may lead to an unbalanced usage of computing resources, which may then degrade both the user experience and the overall service performance. We have named this kind of network with dynamic sharing of edge compute resources "Computing-Aware Networking" (CAN). This document provides the problem statement and the typical scenarios of CAN, which is to provide the service equivalency by steering traffic dynamically to the appropriate service instance based on the basic edge computing deployment.


Peng Liu
Philip Eardley
Dirk Trossen
Mohamed Boucadair
Luis M. Contreras
Cheng Li
Yizhou Li

(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)