Merge pull request #11 from hawkinsw/patch-1

Fix a small typo in draft-olden-ippm-qoo.md

draft-olden-ippm-qoo.md

@@ -243,7 +243,7 @@ Of course, it is possible to specify network requirements for Example.com with m
 # Known Weaknesses and open questions
 We have described a way of simplifying how the network requirements of applications can be compared to quality attenuation measurements. The simplification introduces several artifacts that may or may not be significant. If new information emerges that indicate other tradeoffs are more fit for our purpose, we should switch before this Internet Draft moves further. In this section we discuss some known limitations.
 
-Volatile networks - in particular, mobile cellular networks - pose a challenge for network quality prediction, with the level of assurance of the precition likely to decrease as session duration increases. Historic network conditions for a given cell may help indicate times of network load or reduced transmission power, and their effect on throughput/latency/loss. However: as terminals are mobile, the signal bandwidth available to a given terminal can change by an order of magnitude within seconds due to physical radio factors. These include whether the terminal is at the edge of cell, or undergoing cell handover, the interference and fading from the local environment, and any switch between radio bearers with differing signal bandwidth and transmission-time intervals (e.g. 4G and 5G). This suggests a requirement for measuring quality attenuation to and from an individual terminal, as that can account for the factors described above. How that facility is provisioned onto indiviudal terminals, and how terminal-hosted applications can trigger a quality attenuation query, is an open question.
+Volatile networks - in particular, mobile cellular networks - pose a challenge for network quality prediction, with the level of assurance of the prediction likely to decrease as session duration increases. Historic network conditions for a given cell may help indicate times of network load or reduced transmission power, and their effect on throughput/latency/loss. However: as terminals are mobile, the signal bandwidth available to a given terminal can change by an order of magnitude within seconds due to physical radio factors. These include whether the terminal is at the edge of cell, or undergoing cell handover, the interference and fading from the local environment, and any switch between radio bearers with differing signal bandwidth and transmission-time intervals (e.g. 4G and 5G). This suggests a requirement for measuring quality attenuation to and from an individual terminal, as that can account for the factors described above. How that facility is provisioned onto indiviudal terminals, and how terminal-hosted applications can trigger a quality attenuation query, is an open question.
 
 ## Missing Temporal Information in Distributions.
 These two latency series: 1,200,1,200,1,200,1,200,1,200 and 1,1,1,1,1,200,200,200,200,200 will have identical distributions, but may have different application performance. Ignoring this information is a tradeoff between simplicity and precision. To capture all information necessary to perfectly capture outcomes we are getting into extreme computational complexity. As an application's performance is bound by how the developers react to varying network performance, meaning nearly all different series of latencies may have different application outcomes.