318 lines
14 KiB
Python
318 lines
14 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 random
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import logging
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from binascii import unhexlify
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from twisted.internet import defer
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from lbrynet.dht import constants, kbucket
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from lbrynet.dht.error import TimeoutError
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from lbrynet.dht.distance import Distance
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log = logging.getLogger(__name__)
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class TreeRoutingTable:
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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 whFose 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, getTime=None):
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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._parentNodeID = parentNodeID
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self._buckets = [kbucket.KBucket(rangeMin=0, rangeMax=2 ** constants.key_bits, node_id=self._parentNodeID)]
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if not getTime:
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from twisted.internet import reactor
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getTime = reactor.seconds
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self._getTime = getTime
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self._ongoing_replacements = set()
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def get_contacts(self):
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contacts = []
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for i in range(len(self._buckets)):
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for contact in self._buckets[i]._contacts:
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contacts.append(contact)
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return contacts
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def _shouldSplit(self, bucketIndex, toAdd):
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# https://stackoverflow.com/questions/32129978/highly-unbalanced-kademlia-routing-table/32187456#32187456
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if self._buckets[bucketIndex].keyInRange(self._parentNodeID):
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return True
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contacts = self.get_contacts()
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distance = Distance(self._parentNodeID)
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contacts.sort(key=lambda c: distance(c.id))
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kth_contact = contacts[-1] if len(contacts) < constants.k else contacts[constants.k-1]
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return distance(toAdd) < distance(kth_contact.id)
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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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@rtype: defer.Deferred
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"""
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if contact.id == self._parentNodeID:
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return defer.succeed(None)
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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 if its range includes the host node's id)
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if self._shouldSplit(bucketIndex, contact.id):
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self._splitBucket(bucketIndex)
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# Retry the insertion attempt
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return self.addContact(contact)
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else:
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# We can't split the k-bucket
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#
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# The 13 page kademlia paper specifies that the least recently contacted node in the bucket
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# shall be pinged. If it fails to reply it is replaced with the new contact. If the ping is successful
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# the new contact is ignored and not added to the bucket (sections 2.2 and 2.4).
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#
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# A reasonable extension to this is BEP 0005, which extends the above:
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#
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# Not all nodes that we learn about are equal. Some are "good" and some are not.
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# Many nodes using the DHT are able to send queries and receive responses,
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# but are not able to respond to queries from other nodes. It is important that
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# each node's routing table must contain only known good nodes. A good node is
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# a node has responded to one of our queries within the last 15 minutes. A node
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# is also good if it has ever responded to one of our queries and has sent us a
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# query within the last 15 minutes. After 15 minutes of inactivity, a node becomes
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# questionable. Nodes become bad when they fail to respond to multiple queries
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# in a row. Nodes that we know are good are given priority over nodes with unknown status.
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#
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# When there are bad or questionable nodes in the bucket, the least recent is selected for
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# potential replacement (BEP 0005). When all nodes in the bucket are fresh, the head (least recent)
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# contact is selected as described in section 2.2 of the kademlia paper. In both cases the new contact
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# is ignored if the pinged node replies.
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def replaceContact(failure, deadContact):
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"""
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Callback for the deferred PING RPC to see if the node to be replaced in the k-bucket is still
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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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log.debug("Replacing dead contact in bucket %i: %s:%i (%s) with %s:%i (%s)", bucketIndex,
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deadContact.address, deadContact.port, deadContact.log_id(), contact.address,
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contact.port, contact.log_id())
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try:
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self._buckets[bucketIndex].removeContact(deadContact)
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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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return self.addContact(contact)
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not_good_contacts = self._buckets[bucketIndex].getBadOrUnknownContacts()
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if not_good_contacts:
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to_replace = not_good_contacts[0]
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else:
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to_replace = self._buckets[bucketIndex]._contacts[0]
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if to_replace not in self._ongoing_replacements:
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log.debug("pinging %s:%s", to_replace.address, to_replace.port)
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self._ongoing_replacements.add(to_replace)
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df = to_replace.ping()
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df.addErrback(replaceContact, to_replace)
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df.addBoth(lambda _: self._ongoing_replacements.remove(to_replace))
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else:
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df = defer.succeed(None)
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return df
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else:
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self.touchKBucketByIndex(bucketIndex)
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return defer.succeed(None)
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def findCloseNodes(self, key, count=None, sender_node_id=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, default of k (8)
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@type count: int
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@param sender_node_id: Used during RPC, this is be the sender's Node ID
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Whatever ID is passed in the parameter will get
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excluded from the list of returned contacts.
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@type sender_node_id: 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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exclude = [self._parentNodeID]
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if sender_node_id:
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exclude.append(sender_node_id)
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if key in exclude:
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exclude.remove(key)
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count = count or constants.k
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distance = Distance(key)
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contacts = self.get_contacts()
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contacts = [c for c in contacts if c.id not in exclude]
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contacts.sort(key=lambda c: distance(c.id))
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return contacts[:min(count, len(contacts))]
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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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return self._buckets[bucketIndex].getContact(contactID)
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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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now = int(self._getTime())
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for bucket in self._buckets[startIndex:]:
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if force or now - 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, contact):
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"""
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Remove the contact from the routing table
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@param contact: The contact to remove
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@type contact: dht.contact._Contact
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"""
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bucketIndex = self._kbucketIndex(contact.id)
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try:
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self._buckets[bucketIndex].removeContact(contact)
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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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self.touchKBucketByIndex(self._kbucketIndex(key))
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def touchKBucketByIndex(self, bucketIndex):
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self._buckets[bucketIndex].lastAccessed = int(self._getTime())
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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 = unhexlify(randomID)
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randomID = ((constants.key_bits // 8) - len(randomID)) * b'\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, self._parentNodeID)
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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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def contactInRoutingTable(self, address_tuple):
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for bucket in self._buckets:
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for contact in bucket.getContacts(sort_distance_to=False):
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if address_tuple[0] == contact.address and address_tuple[1] == contact.port:
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return True
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return False
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def bucketsWithContacts(self):
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count = 0
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for bucket in self._buckets:
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if len(bucket):
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count += 1
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return count
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