346 lines
15 KiB
Python
346 lines
15 KiB
Python
# This library is free software, distributed under the terms of
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# the GNU Lesser General Public License Version 3, or any later version.
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# See the COPYING file included in this archive
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#
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# The docstrings in this module contain epytext markup; API documentation
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# may be created by processing this file with epydoc: http://epydoc.sf.net
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import time
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import random
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from zope.interface import implements
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import constants
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import kbucket
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from interface import IRoutingTable
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from error import TimeoutError
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import logging
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log = logging.getLogger(__name__)
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class TreeRoutingTable(object):
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""" This class implements a routing table used by a Node class.
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The Kademlia routing table is a binary tree whose leaves are k-buckets,
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where each k-bucket contains nodes with some common prefix of their IDs.
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This prefix is the k-bucket's position in the binary tree; it therefore
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covers some range of ID values, and together all of the k-buckets cover
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the entire n-bit ID (or key) space (with no overlap).
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@note: In this implementation, nodes in the tree (the k-buckets) are
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added dynamically, as needed; this technique is described in the 13-page
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version of the Kademlia paper, in section 2.4. It does, however, use the
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C{PING} RPC-based k-bucket eviction algorithm described in section 2.2 of
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that paper.
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"""
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implements(IRoutingTable)
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def __init__(self, parentNodeID):
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"""
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@param parentNodeID: The n-bit node ID of the node to which this
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routing table belongs
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@type parentNodeID: str
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"""
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# Create the initial (single) k-bucket covering the range of the entire n-bit ID space
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self._buckets = [kbucket.KBucket(rangeMin=0, rangeMax=2 ** constants.key_bits)]
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self._parentNodeID = parentNodeID
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def addContact(self, contact):
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""" Add the given contact to the correct k-bucket; if it already
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exists, its status will be updated
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@param contact: The contact to add to this node's k-buckets
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@type contact: kademlia.contact.Contact
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"""
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if contact.id == self._parentNodeID:
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return
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bucketIndex = self._kbucketIndex(contact.id)
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try:
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self._buckets[bucketIndex].addContact(contact)
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except kbucket.BucketFull:
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# The bucket is full; see if it can be split (by checking
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# if its range includes the host node's id)
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if self._buckets[bucketIndex].keyInRange(self._parentNodeID):
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self._splitBucket(bucketIndex)
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# Retry the insertion attempt
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self.addContact(contact)
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else:
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# We can't split the k-bucket
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# NOTE:
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# In section 2.4 of the 13-page version of the
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# Kademlia paper, it is specified that in this case,
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# the new contact should simply be dropped. However,
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# in section 2.2, it states that the head contact in
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# the k-bucket (i.e. the least-recently seen node)
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# should be pinged - if it does not reply, it should
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# be dropped, and the new contact added to the tail of
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# the k-bucket. This implementation follows section
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# 2.2 regarding this point.
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def replaceContact(failure):
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""" Callback for the deferred PING RPC to see if the head
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node in the k-bucket is still responding
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@type failure: twisted.python.failure.Failure
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"""
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failure.trap(TimeoutError)
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print '==replacing contact=='
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# Remove the old contact...
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deadContactID = failure.getErrorMessage()
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try:
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self._buckets[bucketIndex].removeContact(deadContactID)
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except ValueError:
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# The contact has already been removed (probably due to a timeout)
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pass
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# ...and add the new one at the tail of the bucket
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self.addContact(contact)
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# Ping the least-recently seen contact in this k-bucket
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head_contact = self._buckets[bucketIndex]._contacts[0]
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df = head_contact.ping()
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# If there's an error (i.e. timeout), remove the head
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# contact, and append the new one
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df.addErrback(replaceContact)
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def findCloseNodes(self, key, count, _rpcNodeID=None):
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""" Finds a number of known nodes closest to the node/value with the
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specified key.
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@param key: the n-bit key (i.e. the node or value ID) to search for
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@type key: str
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@param count: the amount of contacts to return
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@type count: int
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@param _rpcNodeID: Used during RPC, this is be the sender's Node ID
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Whatever ID is passed in the paramater will get
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excluded from the list of returned contacts.
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@type _rpcNodeID: str
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@return: A list of node contacts (C{kademlia.contact.Contact instances})
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closest to the specified key.
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This method will return C{k} (or C{count}, if specified)
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contacts if at all possible; it will only return fewer if the
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node is returning all of the contacts that it knows of.
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@rtype: list
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"""
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bucketIndex = self._kbucketIndex(key)
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closestNodes = self._buckets[bucketIndex].getContacts(constants.k, _rpcNodeID)
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# This method must return k contacts (even if we have the node
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# with the specified key as node ID), unless there is less
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# than k remote nodes in the routing table
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i = 1
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canGoLower = bucketIndex - i >= 0
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canGoHigher = bucketIndex + i < len(self._buckets)
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# Fill up the node list to k nodes, starting with the closest neighbouring nodes known
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while len(closestNodes) < constants.k and (canGoLower or canGoHigher):
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# TODO: this may need to be optimized
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if canGoLower:
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closestNodes.extend(
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self._buckets[bucketIndex - i].getContacts(
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constants.k - len(closestNodes), _rpcNodeID))
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canGoLower = bucketIndex - (i + 1) >= 0
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if canGoHigher:
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closestNodes.extend(
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self._buckets[bucketIndex + i].getContacts(
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constants.k - len(closestNodes), _rpcNodeID))
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canGoHigher = bucketIndex + (i + 1) < len(self._buckets)
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i += 1
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return closestNodes
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def getContact(self, contactID):
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""" Returns the (known) contact with the specified node ID
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@raise ValueError: No contact with the specified contact ID is known
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by this node
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"""
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bucketIndex = self._kbucketIndex(contactID)
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try:
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contact = self._buckets[bucketIndex].getContact(contactID)
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except ValueError:
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raise
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else:
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return contact
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def getRefreshList(self, startIndex=0, force=False):
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""" Finds all k-buckets that need refreshing, starting at the
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k-bucket with the specified index, and returns IDs to be searched for
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in order to refresh those k-buckets
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@param startIndex: The index of the bucket to start refreshing at;
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this bucket and those further away from it will
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be refreshed. For example, when joining the
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network, this node will set this to the index of
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the bucket after the one containing it's closest
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neighbour.
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@type startIndex: index
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@param force: If this is C{True}, all buckets (in the specified range)
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will be refreshed, regardless of the time they were last
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accessed.
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@type force: bool
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@return: A list of node ID's that the parent node should search for
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in order to refresh the routing Table
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@rtype: list
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"""
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bucketIndex = startIndex
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refreshIDs = []
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for bucket in self._buckets[startIndex:]:
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if force or (int(time.time()) - bucket.lastAccessed >= constants.refreshTimeout):
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searchID = self._randomIDInBucketRange(bucketIndex)
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refreshIDs.append(searchID)
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bucketIndex += 1
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return refreshIDs
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def removeContact(self, contactID):
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""" Remove the contact with the specified node ID from the routing
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table
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@param contactID: The node ID of the contact to remove
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@type contactID: str
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"""
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bucketIndex = self._kbucketIndex(contactID)
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try:
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self._buckets[bucketIndex].removeContact(contactID)
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except ValueError:
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return
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def touchKBucket(self, key):
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""" Update the "last accessed" timestamp of the k-bucket which covers
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the range containing the specified key in the key/ID space
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@param key: A key in the range of the target k-bucket
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@type key: str
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"""
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bucketIndex = self._kbucketIndex(key)
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self._buckets[bucketIndex].lastAccessed = int(time.time())
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def _kbucketIndex(self, key):
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""" Calculate the index of the k-bucket which is responsible for the
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specified key (or ID)
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@param key: The key for which to find the appropriate k-bucket index
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@type key: str
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@return: The index of the k-bucket responsible for the specified key
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@rtype: int
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"""
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i = 0
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for bucket in self._buckets:
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if bucket.keyInRange(key):
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return i
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else:
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i += 1
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return i
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def _randomIDInBucketRange(self, bucketIndex):
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""" Returns a random ID in the specified k-bucket's range
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@param bucketIndex: The index of the k-bucket to use
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@type bucketIndex: int
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"""
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idValue = random.randrange(
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self._buckets[bucketIndex].rangeMin, self._buckets[bucketIndex].rangeMax)
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randomID = hex(idValue)[2:]
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if randomID[-1] == 'L':
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randomID = randomID[:-1]
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if len(randomID) % 2 != 0:
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randomID = '0' + randomID
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randomID = randomID.decode('hex')
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randomID = (constants.key_bits / 8 - len(randomID)) * '\x00' + randomID
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return randomID
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def _splitBucket(self, oldBucketIndex):
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""" Splits the specified k-bucket into two new buckets which together
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cover the same range in the key/ID space
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@param oldBucketIndex: The index of k-bucket to split (in this table's
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list of k-buckets)
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@type oldBucketIndex: int
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"""
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# Resize the range of the current (old) k-bucket
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oldBucket = self._buckets[oldBucketIndex]
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splitPoint = oldBucket.rangeMax - (oldBucket.rangeMax - oldBucket.rangeMin) / 2
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# Create a new k-bucket to cover the range split off from the old bucket
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newBucket = kbucket.KBucket(splitPoint, oldBucket.rangeMax)
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oldBucket.rangeMax = splitPoint
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# Now, add the new bucket into the routing table tree
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self._buckets.insert(oldBucketIndex + 1, newBucket)
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# Finally, copy all nodes that belong to the new k-bucket into it...
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for contact in oldBucket._contacts:
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if newBucket.keyInRange(contact.id):
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newBucket.addContact(contact)
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# ...and remove them from the old bucket
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for contact in newBucket._contacts:
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oldBucket.removeContact(contact)
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class OptimizedTreeRoutingTable(TreeRoutingTable):
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""" A version of the "tree"-type routing table specified by Kademlia,
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along with contact accounting optimizations specified in section 4.1 of
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of the 13-page version of the Kademlia paper.
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"""
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def __init__(self, parentNodeID):
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TreeRoutingTable.__init__(self, parentNodeID)
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# Cache containing nodes eligible to replace stale k-bucket entries
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self._replacementCache = {}
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def addContact(self, contact):
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""" Add the given contact to the correct k-bucket; if it already
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exists, its status will be updated
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@param contact: The contact to add to this node's k-buckets
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@type contact: kademlia.contact.Contact
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"""
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if contact.id == self._parentNodeID:
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return
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# Initialize/reset the "successively failed RPC" counter
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contact.failedRPCs = 0
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bucketIndex = self._kbucketIndex(contact.id)
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try:
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self._buckets[bucketIndex].addContact(contact)
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except kbucket.BucketFull:
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# The bucket is full; see if it can be split (by checking
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# if its range includes the host node's id)
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if self._buckets[bucketIndex].keyInRange(self._parentNodeID):
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self._splitBucket(bucketIndex)
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# Retry the insertion attempt
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self.addContact(contact)
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else:
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# We can't split the k-bucket
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# NOTE: This implementation follows section 4.1 of the 13 page version
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# of the Kademlia paper (optimized contact accounting without PINGs
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# - results in much less network traffic, at the expense of some memory)
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# Put the new contact in our replacement cache for the
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# corresponding k-bucket (or update it's position if
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# it exists already)
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if bucketIndex not in self._replacementCache:
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self._replacementCache[bucketIndex] = []
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if contact in self._replacementCache[bucketIndex]:
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self._replacementCache[bucketIndex].remove(contact)
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elif len(self._replacementCache[bucketIndex]) >= constants.replacementCacheSize:
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self._replacementCache[bucketIndex].pop(0)
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self._replacementCache[bucketIndex].append(contact)
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def removeContact(self, contactID):
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""" Remove the contact with the specified node ID from the routing
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table
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@param contactID: The node ID of the contact to remove
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@type contactID: str
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"""
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bucketIndex = self._kbucketIndex(contactID)
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try:
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contact = self._buckets[bucketIndex].getContact(contactID)
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except ValueError:
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return
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contact.failedRPCs += 1
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if contact.failedRPCs >= constants.rpcAttempts:
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self._buckets[bucketIndex].removeContact(contactID)
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# Replace this stale contact with one from our replacement cache, if we have any
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if bucketIndex in self._replacementCache:
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if len(self._replacementCache[bucketIndex]) > 0:
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self._buckets[bucketIndex].addContact(
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self._replacementCache[bucketIndex].pop())
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