 of the speed of light can be assumed for the information transfer. In this case the distance between two communication partners need to be even less than Smax' that is, 150 km X 0.67 22 100 km. Needless to say this delay cannot be mitigated by any engineering means. Furthermore, there are likely to be additional unavoidable delays due to serialization of the data before transmission over the media, routing and switching delay, etc., which limits the maximal distance even further considerably below 100 km to meet a maximum allowed latency of, for example, 1 ms. Considering the above, the only feasible way to provide low end-to-end latency commu- nications is placing remote compute resources closer to the customer. This is what MEC and other related technologies have been designed for. When it comes to network planning to realize the full benefits of URLLC applications, an operator or provider of such edge services needs to identify the location of customers 7.3 Deployment Objectives and Challenges requiring such low latency services and to place the necessary compute resources within the required range to meet the requested requirements. One of the new NG-RAN architectures, specifically the central unit/distributed unit (CU/DU) split described in Section 4.2, makes it easier to deploy edge applications such as MEC by concentrating more compute-intensive functions of the 5G radio in a central place (e.g. in the same cell site where gNB-CU is deployed). This allows sharing of compute resources to serve the load generated in the gNB-CU by several attached gNB-DUs, which can also be shared with MEC. Concentration of compute hardware in larger data centers allows efficient reuse of other resources such as cooling, power, and broadband/backhaul connectivity, helping to provide URLLC services in a reliable, resilient, failsafe, and economical way. As with many other examples of resource dimensioning, on the one hand there is a dan- ger of overproviding edge compute resources. On the other hand, not providing enough comp