1 | = THIS PAGE DESCRIBES HISTORICAL DESIGN CHOICES. SEE docs/architecture.rst FOR CURRENT DOCUMENTATION = |
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2 | |
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3 | When a file is uploaded, the encoded shares are sent to other peers. But to |
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4 | which ones? The PeerSelection algorithm is used to make this choice. |
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5 | |
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6 | Early in 2007, we were planning to use the following "Tahoe Two" algorithm. |
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7 | By the time we released 0.2.0, we switched to "tahoe3", but when we released |
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8 | v0.6, we switched back (ticket #132). |
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9 | |
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10 | As in Tahoe Three, the verifierid is used to consistently-permute the set of |
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11 | all peers (by sorting the peers by HASH(verifierid+peerid)). Each file gets a |
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12 | different permutation, which (on average) will evenly distribute shares among |
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13 | the grid and avoid hotspots. |
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14 | |
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15 | With our basket of (usually 10) shares to distribute in hand, we start at the |
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16 | beginning of the list and ask each peer in turn if they are willing to hold |
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17 | on to one of our shares (the "lease request"). If they say yes, we remove |
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18 | that share from the basket and remember who agreed to host it. Then we go to |
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19 | the next peer in the list and ask them the same question about another share. |
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20 | If a peer says no, we remove them from the list. If a peer says that they |
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21 | already have one or more shares for this file, we remove those shares from |
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22 | the basket. If we reach the end of the list, we start again at the beginning. |
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23 | If we run out of peers before we run out of shares, we fail unless we've |
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24 | managed to place at least some number of the shares: the likely threshold is |
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25 | to attempt to place 10 shares (out of which we'll need 3 to recover the |
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26 | file), and be content if we can find homes for at least 7 of them. |
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27 | |
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28 | In small networks, this approach will loop around several times and place |
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29 | several shares with each node (e.g. in a 5-host network with plenty of space, |
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30 | each node will get 2 shares). In large networks with plenty of space, the |
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31 | shares will be placed with the first 10 peers in the permuted list. In large |
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32 | networks that are somewhat full, we'll need to traverse more of the list |
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33 | before we find homes for the shares. The average number of peers that we'll |
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34 | need to talk to is vaguely equal to 10 / (1-utilization), with a bunch of |
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35 | other terms that relate to the distribution of free space on the peers and |
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36 | the size of the shares being offered. Small files with small shares will fit |
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37 | anywhere, large files with large shares will only fit on certain peers, so |
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38 | the mesh may have free space but no holes large enough for a very large file, |
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39 | which might indicate that we should try again with a larger number of |
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40 | (smaller) shares. |
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41 | |
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42 | When it comes time to download, we compute a similar list of permuted |
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43 | peerids, and start asking for shares beginning with the start of the list. |
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44 | Each peer gives us a list of the shareids that they are holding. Eventually |
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45 | (depending upon how much churn the peerlist has experienced), we'll find |
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46 | holders for at least 3 shares, or we'll run out of peers. If the mesh is very |
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47 | large and we want to fail faster, we can establish an upper bound on how many |
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48 | peers we should talk to (perhaps by recording the permuted peerid of the last |
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49 | node to which we sent a share, or a count of the total number of peers we |
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50 | talked to during upload). |
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51 | |
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52 | I suspect that this approach handles churn more efficiently than tahoe3, but |
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53 | I haven't gotten my head around the math that could be used to show it. On |
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54 | the other hand, it takes a lot more round trips to find homes in small meshes |
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55 | (one per share, whereas tahoe three can do just one per node). |
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56 | |
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