We examined standard deviation in this way for several different sites, and all showed similar correspondence, but to varying degrees. This shows that in addition to decreasing, transfer rate fluctuates more when the network is under heavy load. That is, data transfer is more 'bursty'. Furthermore, rate 'troughs' are common, even when the network is not under particularly heavy load. However, troughs are more frequent, and of longer duration when the network is heavily loaded.
Troughs can range in duration from several seconds to several minutes.
The fact that there is a clear correspondence between time of day and standard deviation in rate shows that network and server load, and not geographical distance, are the primary factors in determining rate variability during Web fetches. Our experiments allow us to draw several conclusions that may be of use when programming Web applications, in particular with relation to failure interpretation. For each conclusion we speculate how they might relate to programming Web fetches. This anomaly can cause many failure interpretations by latency timeout to be erroneous. An appropriate response to this might be to immediately retry all connections that timeout on latency.