%% You should probably cite draft-liu-can-ps-usecases instead of this I-D.
@techreport{liu-dyncast-ps-usecases-04,
    number =    {draft-liu-dyncast-ps-usecases-04},
    type =      {Internet-Draft},
    institution =   {Internet Engineering Task Force},
    publisher = {Internet Engineering Task Force},
    note =      {Work in Progress},
    url =       {https://datatracker.ietf.org/doc/draft-liu-dyncast-ps-usecases/04/},
    author =    {Peng Liu and Philip Eardley and Dirk Trossen and Mohamed Boucadair and Luis M. Contreras and Cheng Li and Yizhou Li},
    title =     {{Dynamic-Anycast (Dyncast) Problem Statement and Use Cases}},
    pagetotal = 17,
    year =      2022,
    month =     jul,
    day =       8,
    abstract =  {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.},
}