Toad wrote:
Currently the situation, even with the recently integrated probabilistic rejection, is as follows: We start off with no load We accept some queries Eventually we use up our outbound bandwidth, and due to either messageSendTimeRequest or the output bandwidth limit, we reject queries until our currently transferring requests have been fulfilled. With our current running average code, at this point the node's pSearchFailed estimate will go through the floor, and it won't recover because it won't be routed to. Possible solutions proposed: 1. Try the nodes again after some fixed, perhaps increasing, backoff, once we are into QR mode. One way to do this is to abuse the pSearchFailed estimator as edt has suggested; another way would be to randomly fork requests occasionally such that each node in the RT is visited at least every N seconds as long as the node has some load. The search failed estimator will recover quite fast if it gets retried and is not queryrejecting.
Actually, perhaps we could easily adjust this solution to meet with my goal of reducing the number of queries made: Any time the requestee notices that the requester is not backing off, it punishes the requester by QR:ing all of its requests for a limited period of time.
2. Use a really long term average.
This won't work since then the prediction will still hardly ever match reality. The reality is that the node is usually either 100% QR or 100% QA. The goals are to get requesters to predict *better* as well as reducing the number of queries to match capacity.
<snipped: my expansion of option 3>3. Have the node somehow guess when it will next be available for queries, and tell the requesting node, which then uses that as a backoff time. Somebody suggested this too essentially. You could perhaps guesstimate it from the transfer rate... but sadly the transfer rate will vary over time..
Any other suggestions? Any detail as to why/how a particular option would work?
-Martin
-Martin
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