%% You should probably cite draft-liu-can-ps-usecases instead of this I-D.
@techreport{liu-dyncast-ps-usecases-02,
    number =    {draft-liu-dyncast-ps-usecases-02},
    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/02/},
    author =    {Peng Liu and Peter Willis and Dirk Trossen and Cheng Li},
    title =     {{Dynamic-Anycast (Dyncast) Use Cases \& Problem Statement}},
    pagetotal = 14,
    year =      2022,
    month =     jan,
    day =       18,
    abstract =  {Many service providers are exploring distributed computing techniques to achieve better service response time and optimized energy consumption. by moving Such techniques rely upon the distribution of computing services and capabilities over many locations in the network such as its edge(e.g., 5G MEC (Multi-access Edge Computing) scenarios), the metro region, virtualized central office, and other locations. In such a distributed computing environment, providing services by soliciting 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. This draft provides an overview of scenarios and problems associated with realizing such scenarios, identifying several key areas which require more investigations in terms of architecture and protocol to achieve balanced computing and networking resource utilization among edges providing the services.},
}