Structured P2P Network
Group14: Qiwei Zhang; Shi Yan; Dawei Ouyang; Boyu Sun
What is P2P Network?
• Peer-to-peer (abbreviated to P2P)
Each computer in the network can act as a
client or server for the other computers in the
network.
Allow shared access to files and peripherals
without the need for a central server
Traditional Client-Server Architecture
P2P Architecture
• Centralized:
Nodes in the P2P network issue queries to the
central directory server to find which other
nodes hold the desired files.
• Decentralized and Unstructured:
1. To find a file, a node queries its neighbors.
2. The most typical query method is flooding
• Decentralized but Structured:
1. the P2P overlay topology is tightly controlled
2. files are placed not at random nodes but at
specified locations.
• We focus on the following 3 critical problems
in Structured P2P network:
1. Load Balancing Problem
2. P2P look-up protocol: Chord
3. Content-Addressable (CAN) Network
Structured P2P System
● Use Globally Consistent Protocols
Peers or resources are organized following specific
criteria and algorithms.
Ensure efficiency for routing search desired files
● Distributed Hash Table(DHT)
A class of decentralized distributed systems that
provide a lookup service similar to hash table
A variant of consistent hashing is used to assign
ownership of each file to a particular peer
Distributed Hash Table in P2P
●(key, value) pairs are stored in the DHT
● Any participating node can efficiently retrieve the value associated with a given key
● A change in the set of participants causes a minimal amount of disruption
● Can scale to extremely large numbers of nodes
handle continual node arrivals, departures, and failures.
Load balancing in dynamic structured
P2P networks
P2P networks may face following problems in real world
• data items are continuously inserted and deleted,
• nodes join and depart the system continuously,
• the distribution of data item IDs and item sizes can be skewed.
Efficient load balancing is needed
Load: e.g. number of bits required for an object;
popularity of the object
Move cost : usually proportional to object size.
A load balancing algorithm should be able to achieve:
• Minimize the load imbalance
• Minimize the amount of load moved
Virtual Server in P2P
• A virtual server represents a peer in the DHT
The storage of data items and routing happen at the virtual
server level rather than at the physical node level.
• A physical node hosts one or more virtual servers.
• Load balancing is achieved by moving virtual
servers
From heavily loaded physical nodes to lightly loaded physical
nodes.
Several Typical Schemes
• one-to-one
each lightly loaded node v periodically contacts a random node
w. If w is heavily loaded, virtual servers are transferred from w to
v such that w becomes light without making v heavy
• one-to-many
allows a heavy node to consider more than one light node at a
time.
• many-to-many
each directory maintains load information for a set of both
light and heavy nodes
The new scheme is based on one-to-many and many-to-many
Procedure
Evaluation of the algorithm
Potential Improvements
• Prediction of change in load.
• Balance of multiple resources.
• Beneficial effect of heterogeneous capacities.
ChordA Scalable Peer-to-Peer Lookup Protocol
for Internet Applications
Ion Stoica, Robert Morris, David LibenNowell, David R. Karger, M. Frans Kaashoek,
Frank Dabek, and
Hari Balakrishnan, Member, IEEE
Motivation: A fundamental problem that confronts
peer-to-peer applications is the efficient location of
the nodes that stores a desired data item.
Chord deal with this problem by operation: given a
key, it maps the key onto a node.
 A node's identifier is chosen by hashing its IP address
 The key's identifier is produced by hashing the key
Chord Protocol
1. Consistent hashing
2. Lookup Algorithm
Simple key location algorithm
scalable key location algorithm
Consistent Hashing
Where to store K10?
Is there N10?
No
Then find the first node follows
N10
N14 !
Lookup Algorithm-Simple Key
Lookup Algorithm-Scalable Key
blind point
Dynamic operations and failures
• Chord needs to deal with nodes joining the system
or leaving dynamically.
Conclusion
• Chord simplifies the design of peer-to-peer systems and applications
based on it by addressing these difficult problems:
• Load balance: Chord acts as distributed hash function, spreading keys
evenly over the nodes.(proved in paper). This provides a degree of natural
load balance.
• Decentralization: Chord is fully distributed; no node is more important
than any other. It belongs to the "Decentralized and structured" category.
"structure" means files are placed not at random nodes but at specified
locations that will make subsequent queries easier. We will see the
structure of Chord later.
• Scalability: The cost of a Chord lookup grows as the log of the number of
nodes O(log n).
• (each Chord node needs routing information about only a few other nodes
while previous work assumes that each node is aware of most of other
nodes in the system so that very large system is not feasible.)
• Availability: Chord automatically adjusts its internal tables to reflect newly
jointed nodes and failed nodes.
A Scalable Content-Addressable
Network
• Definition: Content-Addressable Network, AKA,
CAN, is a distributed, decentralized P2P
infrastrucuture that provide hash table
functionality on Internet-scale
• It was one of the original four distributed hash
tables introduced concurrently. (Chord, Pastry
and Tapestry)
• Features: scalability, robustness and low
latency.
• Usage: P2P file-sharing systems, large scale
storage management systems, wide-area
name resolution services.
• Design: Operations performed on CAN are
similar to a hash table: insertion, lookup and
deletion the (key, value) pairs.
Each node stores a zone (a chunk of the entire
hash table), and contains a coordinate routing
table that holds the IP address and virtual
coordinate zone of its immediate neighbors in
the coordinate space.
• Construction of CAN:
When a new node wants to
join the CAN, it must first
find a node already in the
CAN.
Then using the CAN routing
mechanisms, it must find a
node whose zone will be
split.
Finally, the neighbors of the
split zone must be notified
so that routing can include
the new node.
CAN recovery and maintenance:
When a node leave CAN, the zone it occupied
has to be taken over by other nodes. Normally,
the node will explicitly hand over its zone and
the associated(key, value) database to one of its
neighbors.
However, if it is the network failure that disables
the node immediately, the (key, value) pairs held
by the disabled node are lost until the state is
refreshed by the holder of the data
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Design improvements:
Multi-dimensioned coordinate spaces
Reality: multiple coordinate spaces
Better routing metrics: RTT-weighted routing
Overloading coordinate zones
Multiple hash functions
Topologically-sensitive construction
• Multi-dimensioned coordinate spaces
Increasing the dimensions of the CAN coordinate
space reduces the routing path length, and hence
the path latency, only a small increase in the size of
the coordinate routing table
• Reality is multiple independent coordinate
Spaces with each node in the system being assigned
a different zone in each coordinate space. The
contents of the hash table are replicated on every
reality, this replication provides better availability of
the data and also provide fault tolerance.
• Better routing metrics: RTT-weighted routing
This method aims at reducing the latency of
individual hops along the path rather than the
path length.
• Overloading coordinate zones
A node maintains a list of its peers in addition
to its neighbor list. This mechanism reduces
path length, reduces per-hop latency and
improve fault tolerance
• Multiple hash functions
Used to improve data availability by redundancy.
• Topologically-sensitive construction
Basic design which does not include this can
lead to seemingly strange routing scenarios
where two geographically adjacent nodes may
communicate through some node far away. So
topologically sensitive construction of the
overlay network avoid this.