~ [ source navigation ] ~ [ diff markup ] ~ [ identifier search ] ~ [ freetext search ] ~ [ file search ] ~

Linux Cross Reference
Linux-2.6.17/Documentation/networking/fib_trie.txt

Version: ~ [ 2.6.16 ] ~ [ 2.6.17 ] ~
Architecture: ~ [ ia64 ] ~ [ i386 ] ~ [ arm ] ~ [ ppc ] ~ [ sparc64 ] ~

  1                         LC-trie implementation notes.
  2 
  3 Node types
  4 ----------
  5 leaf 
  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 
 10 trie 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 
 14 A few concepts explained
 15 ------------------------
 16 Bits (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 
 20 Pos (tnode)
 21         The position (in the key) of the key segment used for indexing into
 22         the child array. See Path Compression.
 23 
 24 Path 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 
 35 Level 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 
 44 empty_children
 45         the number of positions in the child array of a given tnode that are
 46         NULL.
 47 
 48 full_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 
 56 Comments
 57 ---------
 58 
 59 We have tried to keep the structure of the code as close to fib_hash as 
 60 possible to allow verification and help up reviewing. 
 61 
 62 fib_find_node()
 63         A good start for understanding this code. This function implements a
 64         straightforward trie lookup.
 65 
 66 fib_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 
 71 trie_leaf_remove()
 72         Looks up a key, deletes it and runs the level compression algorithm.
 73 
 74 trie_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 
 80 resize()
 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 
 86 inflate()
 87         Doubles the size of the child array within a tnode. Used by resize().
 88 
 89 halve()
 90         Halves the size of the child array within a tnode - the inverse of
 91         inflate(). Used by resize();
 92 
 93 fn_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 
 97 fn_trie_flush()
 98         This walks the full trie (using nextleaf()) and searches for empty
 99         leaves which have to be removed.
100 
101 fn_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 
107 Locking
108 -------
109 
110 fib_lock is used for an RW-lock in the same way that this is done in fib_hash.
111 However, the functions are somewhat separated for other possible locking
112 scenarios. It might conceivably be possible to run trie_rebalance via RCU
113 to avoid read_lock in the fn_trie_lookup() function.
114 
115 Main lookup mechanism
116 ---------------------
117 fn_trie_lookup() is the main lookup function.
118 
119 The lookup is in its simplest form just like fib_find_node(). We descend the
120 trie, key segment by key segment, until we find a leaf. check_leaf() does
121 the fib_semantic_match in the leaf's sorted prefix hlist.
122 
123 If we find a match, we are done.
124 
125 If we don't find a match, we enter prefix matching mode. The prefix length,
126 starting out at the same as the key length, is reduced one step at a time,
127 and we backtrack upwards through the trie trying to find a longest matching
128 prefix. The goal is always to reach a leaf and get a positive result from the
129 fib_semantic_match mechanism.
130 
131 Inside each tnode, the search for longest matching prefix consists of searching
132 through the child array, chopping off (zeroing) the least significant "1" of
133 the child index until we find a match or the child index consists of nothing but
134 zeros.
135 
136 At this point we backtrack (t->stats.backtrack++) up the trie, continuing to
137 chop off part of the key in order to find the longest matching prefix.
138 
139 At this point we will repeatedly descend subtries to look for a match, and there
140 are some optimizations available that can provide us with "shortcuts" to avoid
141 descending into dead ends. Look for "HL_OPTIMIZE" sections in the code.
142 
143 To alleviate any doubts about the correctness of the route selection process,
144 a new netlink operation has been added. Look for NETLINK_FIB_LOOKUP, which
145 gives userland access to fib_lookup().

~ [ source navigation ] ~ [ diff markup ] ~ [ identifier search ] ~ [ freetext search ] ~ [ file search ] ~

This page was automatically generated by the LXR engine.
Visit the LXR main site for more information.