146 lines
5.7 KiB
Plaintext
146 lines
5.7 KiB
Plaintext
LC-trie implementation notes.
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Node types
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----------
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leaf
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An end node with data. This has a copy of the relevant key, along
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with 'hlist' with routing table entries sorted by prefix length.
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See struct leaf and struct leaf_info.
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trie node or tnode
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An internal node, holding an array of child (leaf or tnode) pointers,
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indexed through a subset of the key. See Level Compression.
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A few concepts explained
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------------------------
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Bits (tnode)
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The number of bits in the key segment used for indexing into the
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child array - the "child index". See Level Compression.
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Pos (tnode)
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The position (in the key) of the key segment used for indexing into
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the child array. See Path Compression.
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Path Compression / skipped bits
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Any given tnode is linked to from the child array of its parent, using
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a segment of the key specified by the parent's "pos" and "bits"
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In certain cases, this tnode's own "pos" will not be immediately
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adjacent to the parent (pos+bits), but there will be some bits
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in the key skipped over because they represent a single path with no
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deviations. These "skipped bits" constitute Path Compression.
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Note that the search algorithm will simply skip over these bits when
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searching, making it necessary to save the keys in the leaves to
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verify that they actually do match the key we are searching for.
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Level Compression / child arrays
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the trie is kept level balanced moving, under certain conditions, the
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children of a full child (see "full_children") up one level, so that
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instead of a pure binary tree, each internal node ("tnode") may
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contain an arbitrarily large array of links to several children.
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Conversely, a tnode with a mostly empty child array (see empty_children)
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may be "halved", having some of its children moved downwards one level,
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in order to avoid ever-increasing child arrays.
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empty_children
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the number of positions in the child array of a given tnode that are
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NULL.
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full_children
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the number of children of a given tnode that aren't path compressed.
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(in other words, they aren't NULL or leaves and their "pos" is equal
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to this tnode's "pos"+"bits").
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(The word "full" here is used more in the sense of "complete" than
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as the opposite of "empty", which might be a tad confusing.)
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Comments
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---------
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We have tried to keep the structure of the code as close to fib_hash as
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possible to allow verification and help up reviewing.
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fib_find_node()
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A good start for understanding this code. This function implements a
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straightforward trie lookup.
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fib_insert_node()
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Inserts a new leaf node in the trie. This is bit more complicated than
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fib_find_node(). Inserting a new node means we might have to run the
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level compression algorithm on part of the trie.
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trie_leaf_remove()
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Looks up a key, deletes it and runs the level compression algorithm.
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trie_rebalance()
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The key function for the dynamic trie after any change in the trie
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it is run to optimize and reorganize. It will walk the trie upwards
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towards the root from a given tnode, doing a resize() at each step
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to implement level compression.
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resize()
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Analyzes a tnode and optimizes the child array size by either inflating
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or shrinking it repeatedly until it fulfills the criteria for optimal
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level compression. This part follows the original paper pretty closely
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and there may be some room for experimentation here.
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inflate()
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Doubles the size of the child array within a tnode. Used by resize().
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halve()
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Halves the size of the child array within a tnode - the inverse of
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inflate(). Used by resize();
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fn_trie_insert(), fn_trie_delete(), fn_trie_select_default()
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The route manipulation functions. Should conform pretty closely to the
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corresponding functions in fib_hash.
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fn_trie_flush()
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This walks the full trie (using nextleaf()) and searches for empty
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leaves which have to be removed.
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fn_trie_dump()
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Dumps the routing table ordered by prefix length. This is somewhat
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slower than the corresponding fib_hash function, as we have to walk the
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entire trie for each prefix length. In comparison, fib_hash is organized
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as one "zone"/hash per prefix length.
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Locking
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-------
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fib_lock is used for an RW-lock in the same way that this is done in fib_hash.
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However, the functions are somewhat separated for other possible locking
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scenarios. It might conceivably be possible to run trie_rebalance via RCU
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to avoid read_lock in the fn_trie_lookup() function.
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Main lookup mechanism
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---------------------
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fn_trie_lookup() is the main lookup function.
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The lookup is in its simplest form just like fib_find_node(). We descend the
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trie, key segment by key segment, until we find a leaf. check_leaf() does
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the fib_semantic_match in the leaf's sorted prefix hlist.
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If we find a match, we are done.
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If we don't find a match, we enter prefix matching mode. The prefix length,
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starting out at the same as the key length, is reduced one step at a time,
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and we backtrack upwards through the trie trying to find a longest matching
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prefix. The goal is always to reach a leaf and get a positive result from the
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fib_semantic_match mechanism.
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Inside each tnode, the search for longest matching prefix consists of searching
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through the child array, chopping off (zeroing) the least significant "1" of
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the child index until we find a match or the child index consists of nothing but
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zeros.
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At this point we backtrack (t->stats.backtrack++) up the trie, continuing to
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chop off part of the key in order to find the longest matching prefix.
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At this point we will repeatedly descend subtries to look for a match, and there
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are some optimizations available that can provide us with "shortcuts" to avoid
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descending into dead ends. Look for "HL_OPTIMIZE" sections in the code.
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To alleviate any doubts about the correctness of the route selection process,
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a new netlink operation has been added. Look for NETLINK_FIB_LOOKUP, which
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gives userland access to fib_lookup().
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