That was just an example, that list has to be completed on a specific network or scenario, it changes dramatically. Imagine you were to create a list for a DoD network instead of public peering based network, it would change dramatically.
On Sat, Aug 15, 2015 at 12:28 PM, Glen Kent <glen.k...@gmail.com> wrote: > Why do you say that Layer 1 issues in the last mile would be very high? > How is it any different from the first mile? > > On Sat, Aug 15, 2015 at 10:56 PM, Rafael Possamai <raf...@gav.ufsc.br> > wrote: > >> Hi Glen, >> >> If you first list the causes of a dropped packet, then you can figure out >> how likely they are at different points in time (first\last\peer\etc) by >> making some assumptions. >> >> Here's an **example**: >> >> *Cause | Location | Likelihood* >> Congestion | Last mile | Low >> Congestion | First mile | Low >> Congestion | Peering | Medium >> Layer 1 | First mile | Low >> Layer 1 | Core | Low >> Layer 1 | Last mile | High >> >> You can even go as far as drawing a cause and effect diagram for each >> location. Then you can collect real world data and fine tune your >> assumptions. >> >> >> Rafael >> >> >> On Sat, Aug 15, 2015 at 11:47 AM, Glen Kent <glen.k...@gmail.com> wrote: >> >>> Hi, >>> >>> Is it fair to say that most traffic drops happen in the access layers, or >>> the first and the last miles, and the % of packet drops in the core are >>> minimal? So, if the packet has made it past the first mile and has >>> "entered" the core then chances are high that the packet will safely get >>> across till the exit in the core. Sure once it gets off the core, then >>> all >>> bets are off on whether it will get dropped or not. However, the key >>> point >>> is that the core usually does not drop too many packets - the probability >>> of drops are highest in the access side. >>> >>> Is this correct? >>> >>> Glen >>> >> >> >
