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authorRobert Olsson <Robert.Olsson@data.slu.se>2005-07-05 19:38:26 -0400
committerDavid S. Miller <davem@davemloft.net>2005-07-05 19:38:26 -0400
commitb2f571026594884e7a2a3f8bc6ad5c92e0703330 (patch)
tree544ec8e4d300b76cc6db96a0321f1d298a52d000 /Documentation
parent908a75c17a9e5a888347c2c1d3572203d1b1c7db (diff)
[IPV4]: Add LC-Trie implementation notes
Signed-off-by: Robert Olsson <Robert.Olsson@data.slu.se> Signed-off-by: David S. Miller <davem@davemloft.net>
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1 LC-trie implementation notes.
2
3Node types
4----------
5leaf
6 An end node with data. This has a copy of the relevant key, along
7 with 'hlist' with routing table entries sorted by prefix length.
8 See struct leaf and struct leaf_info.
9
10trie node or tnode
11 An internal node, holding an array of child (leaf or tnode) pointers,
12 indexed through a subset of the key. See Level Compression.
13
14A few concepts explained
15------------------------
16Bits (tnode)
17 The number of bits in the key segment used for indexing into the
18 child array - the "child index". See Level Compression.
19
20Pos (tnode)
21 The position (in the key) of the key segment used for indexing into
22 the child array. See Path Compression.
23
24Path Compression / skipped bits
25 Any given tnode is linked to from the child array of its parent, using
26 a segment of the key specified by the parent's "pos" and "bits"
27 In certain cases, this tnode's own "pos" will not be immediately
28 adjacent to the parent (pos+bits), but there will be some bits
29 in the key skipped over because they represent a single path with no
30 deviations. These "skipped bits" constitute Path Compression.
31 Note that the search algorithm will simply skip over these bits when
32 searching, making it necessary to save the keys in the leaves to
33 verify that they actually do match the key we are searching for.
34
35Level Compression / child arrays
36 the trie is kept level balanced moving, under certain conditions, the
37 children of a full child (see "full_children") up one level, so that
38 instead of a pure binary tree, each internal node ("tnode") may
39 contain an arbitrarily large array of links to several children.
40 Conversely, a tnode with a mostly empty child array (see empty_children)
41 may be "halved", having some of its children moved downwards one level,
42 in order to avoid ever-increasing child arrays.
43
44empty_children
45 the number of positions in the child array of a given tnode that are
46 NULL.
47
48full_children
49 the number of children of a given tnode that aren't path compressed.
50 (in other words, they aren't NULL or leaves and their "pos" is equal
51 to this tnode's "pos"+"bits").
52
53 (The word "full" here is used more in the sense of "complete" than
54 as the opposite of "empty", which might be a tad confusing.)
55
56Comments
57---------
58
59We have tried to keep the structure of the code as close to fib_hash as
60possible to allow verification and help up reviewing.
61
62fib_find_node()
63 A good start for understanding this code. This function implements a
64 straightforward trie lookup.
65
66fib_insert_node()
67 Inserts a new leaf node in the trie. This is bit more complicated than
68 fib_find_node(). Inserting a new node means we might have to run the
69 level compression algorithm on part of the trie.
70
71trie_leaf_remove()
72 Looks up a key, deletes it and runs the level compression algorithm.
73
74trie_rebalance()
75 The key function for the dynamic trie after any change in the trie
76 it is run to optimize and reorganize. Tt will walk the trie upwards
77 towards the root from a given tnode, doing a resize() at each step
78 to implement level compression.
79
80resize()
81 Analyzes a tnode and optimizes the child array size by either inflating
82 or shrinking it repeatedly until it fullfills the criteria for optimal
83 level compression. This part follows the original paper pretty closely
84 and there may be some room for experimentation here.
85
86inflate()
87 Doubles the size of the child array within a tnode. Used by resize().
88
89halve()
90 Halves the size of the child array within a tnode - the inverse of
91 inflate(). Used by resize();
92
93fn_trie_insert(), fn_trie_delete(), fn_trie_select_default()
94 The route manipulation functions. Should conform pretty closely to the
95 corresponding functions in fib_hash.
96
97fn_trie_flush()
98 This walks the full trie (using nextleaf()) and searches for empty
99 leaves which have to be removed.
100
101fn_trie_dump()
102 Dumps the routing table ordered by prefix length. This is somewhat
103 slower than the corresponding fib_hash function, as we have to walk the
104 entire trie for each prefix length. In comparison, fib_hash is organized
105 as one "zone"/hash per prefix length.
106
107Locking
108-------
109
110fib_lock is used for an RW-lock in the same way that this is done in fib_hash.
111However, the functions are somewhat separated for other possible locking
112scenarios. It might conceivably be possible to run trie_rebalance via RCU
113to avoid read_lock in the fn_trie_lookup() function.
114
115Main lookup mechanism
116---------------------
117fn_trie_lookup() is the main lookup function.
118
119The lookup is in its simplest form just like fib_find_node(). We descend the
120trie, key segment by key segment, until we find a leaf. check_leaf() does
121the fib_semantic_match in the leaf's sorted prefix hlist.
122
123If we find a match, we are done.
124
125If we don't find a match, we enter prefix matching mode. The prefix length,
126starting out at the same as the key length, is reduced one step at a time,
127and we backtrack upwards through the trie trying to find a longest matching
128prefix. The goal is always to reach a leaf and get a positive result from the
129fib_semantic_match mechanism.
130
131Inside each tnode, the search for longest matching prefix consists of searching
132through the child array, chopping off (zeroing) the least significant "1" of
133the child index until we find a match or the child index consists of nothing but
134zeros.
135
136At this point we backtrack (t->stats.backtrack++) up the trie, continuing to
137chop off part of the key in order to find the longest matching prefix.
138
139At this point we will repeatedly descend subtries to look for a match, and there
140are some optimizations available that can provide us with "shortcuts" to avoid
141descending into dead ends. Look for "HL_OPTIMIZE" sections in the code.
142
143To alleviate any doubts about the correctness of the route selection process,
144a new netlink operation has been added. Look for NETLINK_FIB_LOOKUP, which
145gives userland access to fib_lookup().