Structured P2P Network - PowerPoint Presentation

Slide1

Structured P2P Network

Group14:

Qiwei

Zhang; Shi Yan;

Dawei

Ouyang

;

Boyu

SunSlide2

What is P2P Network?

Peer-to-peer

(abbreviated to

P2P

)

E

ach

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 serverSlide3

Traditional

C

lient-Server ArchitectureSlide4

P2P ArchitectureSlide5

Centralized:

Nodes in the P2P network issue queries to the

central directory server to find which other

nodes hold the desired files.Slide6
Slide7

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. Slide8

We focus on the following 3 critical problems in Structured P2P network:

Load Balancing Problem

P2P

look-up protocol: Chord

Content-Addressable

(CAN)

NetworkSlide9

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 Slide10

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.Slide11

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 movedSlide12

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.Slide13

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 heavyone-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-manySlide14

ProcedureSlide15

Evaluation of the algorithmSlide16

Potential Improvements

Prediction of change in load

.

Balance of multiple resources

.

Beneficial effect of heterogeneous

capacities.Slide17

Chord-

A Scalable Peer-to-Peer Lookup Protocol for Internet

Application

s

Ion Stoica, Robert Morris, David Liben-Nowell, David R. Karger, M. Frans Kaashoek, Frank Dabek, and

Hari Balakrishnan, Member, IEEESlide18

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. Slide19

A node's identifier is chosen by hashing its IP address

The key's identifier is produced by hashing the keySlide20

Chord Protocol

1. Consistent hashing

2. Lookup Algorithm

Simple key location algorithm

scalable key location algorithmSlide21

Consistent HashingSlide22

Where to store K10?

Is there N10?

No

Then find the first node follows N10

N14 !Slide23

Lookup Algorithm-Simple KeySlide24

Lookup Algorithm-Scalable Key

blind pointSlide25
Slide26

Dynamic operations and failures

Chord needs to deal with nodes joining the system or leaving dynamically.Slide27

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.Slide28

A Scalable Content-Addressable NetworkSlide29

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)Slide30

Features:

scalability, robustness and low latency.

Usage:

P2P file-sharing systems, large scale storage management systems, wide-area name resolution services.Slide31

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.Slide32

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.Slide33

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 dataSlide34

Design improvements:

Multi-dimensioned coordinate spaces

Reality: multiple coordinate spaces

Better routing metrics: RTT-weighted routing

Overloading coordinate zones

Multiple hash functions

Topologically-sensitive constructionSlide35

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

S

paces

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.Slide36

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 toleranceSlide37

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.