~ Merge routing stuff to the one module.

3 files changed, 151 insertions, 202 deletions

diff --git a/src/Data/Kademlia/Routing/Bucket.hs b/src/Data/Kademlia/Routing/Bucket.hs
deleted file mode 100644
index 8d7f3e50..00000000
--- a/src/Data/Kademlia/Routing/Bucket.hs
+++ /dev/null
@@ -1,139 +0,0 @@
--- |
---   Copyright   :  (c) Sam T. 2013
---   License     :  MIT
---   Maintainer  :  pxqr.sta@gmail.com
---   Stability   :  experimental
---   Portability :  portable
---
---   Bucket is used to
---
---   Bucket is kept sorted by time last seen — least-recently seen
---   node at the head, most-recently seen at the tail. Reason: when we
---   insert a node into the bucket we first filter nodes with smaller
---   lifetime since they more likely leave network and we more likely
---   don't reach list end. This should reduce list traversal, we don't
---   need to reverse list in insertion routines.
---
---   Bucket is also limited in its length — thus it's called k-bucket.
---   When bucket becomes full we should split it in two lists by
---   current span bit. Span bit is defined by depth in the routing
---   table tree. Size of the bucket should be choosen such that it's
---   very unlikely that all nodes in bucket fail within an hour of
---   each other.
---
-{-# LANGUAGE RecordWildCards #-}
-module Data.Kademlia.Routing.Bucket
-       ( Bucket(maxSize, kvs)
-
-         -- * Query
-       , size, isFull, member
-
-         -- * Construction
-       , empty, singleton
-
-         -- * Modification
-       , enlarge, split, insert
-
-         -- * Defaults
-       , defaultBucketSize
-       ) where
-
-import Control.Applicative hiding (empty)
-import Data.Bits
-import Data.List as L hiding (insert)
-
-
-type Size = Int
-
-data Bucket k v = Bucket {
-    -- | We usually use equally sized buckets in the all routing table
-    -- so keeping max size in each bucket lead to redundancy. Altrough
-    -- it allow us to use some interesting schemes in route tree.
-    maxSize :: Size
-
-    -- | Key -> value pairs as described above.
-    --   Each key in a given bucket should be unique.
-  , kvs     :: [(k, v)]
-  }
-
--- | Gives /current/ size of bucket.
---
---   forall bucket. size bucket <= maxSize bucket
---
-size :: Bucket k v -> Size
-size = L.length . kvs
-
-isFull :: Bucket k v -> Bool
-isFull Bucket {..} = L.length kvs == maxSize
-
-member :: Eq k => k -> Bucket k v -> Bool
-member k = elem k . map fst . kvs
-
-empty :: Size -> Bucket k v
-empty s = Bucket (max 0 s) []
-
-singleton :: Size -> k -> v -> Bucket k v
-singleton s k v = Bucket (max 1 s) [(k, v)]
-
-
--- | Increase size of a given bucket.
-enlarge :: Size -> Bucket k v -> Bucket k v
-enlarge additional b = b { maxSize = maxSize b + additional }
-
-split :: Bits k => Int -> Bucket k v -> (Bucket k v, Bucket k v)
-split index Bucket {..} =
-    let (far, near) = partition spanBit kvs
-    in (Bucket maxSize near, Bucket maxSize far)
-  where
-    spanBit = (`testBit` index) . fst
-
-
--- move elem to the end in one traversal
-moveToEnd :: Eq k => (k, v) -> Bucket k v -> Bucket k v
-moveToEnd kv@(k, _) b = b { kvs = go (kvs b) }
-  where
-    go [] = []
-    go (x : xs)
-      | fst x == k = xs ++ [kv]
-      | otherwise  = x : go xs
-
-insertToEnd :: (k, v) -> Bucket k v -> Bucket k v
-insertToEnd kv b = b { kvs = kvs b ++ [kv] }
-
--- | * If the info already exists in bucket then move it to the end.
---
---   * If bucket is not full then insert the info to the end.
---
---   * If bucket is full then ping the least recently seen node.
---     Here we have a choice:
---
---         If node respond then move it the end and discard node
---         we  want to insert.
---
---         If not remove it from the bucket and add the
---         (we want to insert) node to the end.
---
-insert :: Applicative f => Eq k
-       => (v ->  f Bool)  -- ^ Ping RPC
-       -> (k, v) -> Bucket k v -> f (Bucket k v)
-
-insert ping new bucket@(Bucket {..})
-    | fst new `member` bucket = pure (new `moveToEnd` bucket)
-    | size bucket < maxSize   = pure (new `insertToEnd` bucket)
-    | least : rest <- kvs     =
-      let select alive = if alive then least else new
-          mk most = Bucket maxSize (rest ++ [most])
-      in mk . select <$> ping (snd least)
-      where
---    | otherwise                 = pure bucket
-     -- WARN: or maybe error "insertBucket: max size should not be 0" ?
-
-lookup :: k -> Bucket k v -> Maybe v
-lookup = undefined
-
-closest :: Int -> k -> Bucket k v -> [(k, v)]
-closest = undefined
-
--- | Most clients use this value for maximum bucket size.
-defaultBucketSize :: Int
-defaultBucketSize = 20
diff --git a/src/Data/Kademlia/Routing/Table.hs b/src/Data/Kademlia/Routing/Table.hs
index b79a0a31..1435db41 100644
--- a/src/Data/Kademlia/Routing/Table.hs
+++ b/src/Data/Kademlia/Routing/Table.hs
@@ -5,19 +5,164 @@
 --   Stability   :  experimental
 --   Portability :  portable
 --
---   Routing table used to lookup . Internally it uses not balanced tree
---
--- TODO write module synopsis
+{-# LANGUAGE RecordWildCards #-}
 module Data.Kademlia.Routing.Table
        ( Table(nodeID)
        ) where
 
-import Control.Applicative
-import Data.List as L
+import Control.Applicative hiding (empty)
+import Data.Bits
+import Data.List as L hiding (insert)
 import Data.Maybe
 
-import Data.Kademlia.Routing.Tree
+{-----------------------------------------------------------------------
+    Bucket
+-----------------------------------------------------------------------}
+
+type Size = Int
+
+-- | Bucket is kept sorted by time last seen — least-recently seen
+--   node at the head, most-recently seen at the tail. Reason: when we
+--   insert a node into the bucket we first filter nodes with smaller
+--   lifetime since they more likely leave network and we more likely
+--   don't reach list end. This should reduce list traversal, we don't
+--   need to reverse list in insertion routines.
+--
+--   Bucket is also limited in its length — thus it's called k-bucket.
+--   When bucket becomes full we should split it in two lists by
+--   current span bit. Span bit is defined by depth in the routing
+--   table tree. Size of the bucket should be choosen such that it's
+--   very unlikely that all nodes in bucket fail within an hour of
+--   each other.
+--
+data Bucket = Empty
+            | Cons {-# UNPACK #-} !NodeAddr {-# UNPACK #-} !TimeStamp !Bucket
+
+-- | Gives /current/ size of bucket.
+--
+--   forall bucket. size bucket <= maxSize bucket
+--
+size :: Bucket k v -> Size
+size = L.length . kvs
+
+isFull :: Bucket k v -> Bool
+isFull Bucket {..} = L.length kvs == maxSize
+
+member :: Eq k => k -> Bucket k v -> Bool
+member k = elem k . map fst . kvs
+
+empty :: Size -> Bucket k v
+empty s = Bucket (max 0 s) []
+
+singleton :: Size -> k -> v -> Bucket k v
+singleton s k v = Bucket (max 1 s) [(k, v)]
+
+
+-- | Increase size of a given bucket.
+enlarge :: Size -> Bucket k v -> Bucket k v
+enlarge additional b = b { maxSize = maxSize b + additional }
+
+split :: Bits k => Int -> Bucket k v -> (Bucket k v, Bucket k v)
+split index Bucket {..} =
+    let (far, near) = partition spanBit kvs
+    in (Bucket maxSize near, Bucket maxSize far)
+  where
+    spanBit = (`testBit` index) . fst
+
+
+-- move elem to the end in one traversal
+moveToEnd :: Eq k => (k, v) -> Bucket k v -> Bucket k v
+moveToEnd kv@(k, _) b = b { kvs = go (kvs b) }
+  where
+    go [] = []
+    go (x : xs)
+      | fst x == k = xs ++ [kv]
+      | otherwise  = x : go xs
+
+insertToEnd :: (k, v) -> Bucket k v -> Bucket k v
+insertToEnd kv b = b { kvs = kvs b ++ [kv] }
+
+-- | * If the info already exists in bucket then move it to the end.
+--
+--   * If bucket is not full then insert the info to the end.
+--
+--   * If bucket is full then ping the least recently seen node.
+--     Here we have a choice:
+--
+--         If node respond then move it the end and discard node
+--         we  want to insert.
+--
+--         If not remove it from the bucket and add the
+--         (we want to insert) node to the end.
+--
+insert :: Applicative f => Eq k
+       => (v ->  f Bool)  -- ^ Ping RPC
+       -> (k, v) -> Bucket k v -> f (Bucket k v)
 
+insert ping new bucket@(Bucket {..})
+    | fst new `member` bucket = pure (new `moveToEnd` bucket)
+    | size bucket < maxSize   = pure (new `insertToEnd` bucket)
+    | least : rest <- kvs     =
+      let select alive = if alive then least else new
+          mk most = Bucket maxSize (rest ++ [most])
+      in mk . select <$> ping (snd least)
+      where
+--    | otherwise                 = pure bucket
+     -- WARN: or maybe error "insertBucket: max size should not be 0" ?
+
+lookup :: k -> Bucket k v -> Maybe v
+lookup = undefined
+
+closest :: Int -> k -> Bucket k v -> [(k, v)]
+closest = undefined
+
+-- | Most clients use this value for maximum bucket size.
+defaultBucketSize :: Int
+defaultBucketSize = 20
+
+{-----------------------------------------------------------------------
+    Tree
+-----------------------------------------------------------------------}
+
+-- | Routing tree should contain key -> value pairs in this way:
+--
+--     * More keys that near to our node key, and less keys that far
+--     from our node key.
+--
+--     * Tree might be saturated. If this happen we can only update
+--     buckets, but we can't add new buckets.
+--
+--   Instead of using ordinary binary tree and keep track is it
+--   following restrictions above (that's somewhat non-trivial) we
+--   store distance -> value keys. This lead to simple data structure
+--   that actually isomorphic to non-empty list. So we first map our
+--   keys to distances using our node ID and store them in tree. When
+--   we need to extract a pair we map distances to keys back, again
+--   using our node ID. This normalization happen in routing table.
+--
+data Tree k v
+  = Tip (Bucket k v)
+  | Bin (Tree k v)   (Bucket k v)
+
+empty :: Int -> Tree k v
+empty = Tip . Bucket.empty
+
+insert :: Applicative f => Bits k
+       => (v -> f Bool) -> (k, v) -> Tree k v -> f (Tree k v)
+insert ping (k, v) = go 0
+  where
+    go n (Tip bucket)
+      | isFull bucket, (near, far) <- split n bucket
+                          = pure (Tip near `Bin` far)
+      |     otherwise     = Tip <$> Bucket.insert ping (k, v) bucket
+
+    go n (Bin near far)
+      | k `testBit` n = Bin <$> pure near <*> Bucket.insert ping (k, v) far
+      | otherwise     = Bin <$> go (succ n) near <*> pure far
+
+{-----------------------------------------------------------------------
+    Table
+-----------------------------------------------------------------------}
 
 data Table k v = Table {
     routeTree     :: Tree k v
@@ -33,6 +178,5 @@ data Table k v = Table {
 --closest :: InfoHash -> Table -> [NodeID]
 --closest = undefined
 
-
 -- TODO table serialization: usually we need to save table between
 -- target program executions for bootstrapping
diff --git a/src/Data/Kademlia/Routing/Tree.hs b/src/Data/Kademlia/Routing/Tree.hs
deleted file mode 100644
index 522bb0c2..00000000
--- a/src/Data/Kademlia/Routing/Tree.hs
+++ /dev/null
@@ -1,56 +0,0 @@
--- |
---   Copyright   :  (c) Sam T. 2013
---   License     :  MIT
---   Maintainer  :  pxqr.sta@gmail.com
---   Stability   :  experimental
---   Portability :  portable
---
---   Routing tree should contain key -> value pairs in this way:
---
---     * More keys that near to our node key, and less keys that far
---     from our node key.
---
---     * Tree might be saturated. If this happen we can only update
---     buckets, but we can't add new buckets.
---
---   Instead of using ordinary binary tree and keep track is it
---   following restrictions above (that's somewhat non-trivial) we
---   store distance -> value keys. This lead to simple data structure
---   that actually isomorphic to non-empty list. So we first map our
---   keys to distances using our node ID and store them in tree. When
---   we need to extract a pair we map distances to keys back, again
---   using our node ID. This normalization happen in routing table.
---
-module Data.Kademlia.Routing.Tree
-       ( Tree, empty, insert
-       ) where
-
-import Control.Applicative hiding (empty)
-import Data.Bits
-
-import Data.Kademlia.Routing.Bucket (Bucket, split, isFull)
-import qualified Data.Kademlia.Routing.Bucket as Bucket
-
-
-
-data Tree k v
-  = Tip (Bucket k v)
-  | Bin (Tree k v)   (Bucket k v)
-
-empty :: Int -> Tree k v
-empty = Tip . Bucket.empty
-
-insert :: Applicative f
-       => Bits k
-       => (v -> f Bool)
-       -> (k, v) -> Tree k v -> f (Tree k v)
-insert ping (k, v) = go 0
-  where
-    go n (Tip bucket)
-      | isFull bucket, (near, far) <- split n bucket
-                          = pure (Tip near `Bin` far)
-      |     otherwise     = Tip <$> Bucket.insert ping (k, v) bucket
-
-    go n (Bin near far)
-      | k `testBit` n = Bin <$> pure near <*> Bucket.insert ping (k, v) far
-      | otherwise     = Bin <$> go (succ n) near <*> pure far