L13 P2P Overlay Networks: Theory by T.S.R.K. Prasad EA C451 Internetworking Technologies
References / Acknowledgements Ch 6: Peer-to-Peer Content Networks, [Hoffman] Sec 2.6: Peer-to-Peer Applications, [Kurose] [Theotokis]
References
Stephanos Androutsellis-Theotokis, A Survey of Peer-to-Peer File Sharing Technologies
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References / Acknowledgements [Ross-P2P]
Keith W. Ross, and Dan Rubenstein, P2P Systems, Infocomm Tutorial
[Kurose-P2P] Ch2: Applications, [Kurose] [Zhang-P2P] Prof. Zhi-Li Zhang, P2P, CSci5221: Foundations of Advanced Networking, Spring 2011. (http://www-users.cselabs.umn.edu/classes/Spring2011/csci5221/index.php)
[Rexford-P2P] Jennifer Rexford, Peer-to-Peer File Sharing, COS 461: Computer Networks (http://www.cs.princeton.edu/courses/archive/spr12/cos461/) References
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References / Acknowledgements [Stoica-P2P]
Ion Stoica, P2P Networks, EE122: Computer Networking, Dept of EECS, UCB, Fall 2002. (www-inst.eecs.berkeley.edu/~ee122/fa02)
References
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Optional Readings [Andersen]
David G. Andersen, Hari Balakrishnan, M. Frans Kaashoek, and Robert Morris, Resilient Overlay Networks, SOPS-2001.
[Lua]
Eng Keong Lua, Jon Crowcroft, Marcelo Pias, Ravi Sharma and Steven Lim, A Survey and Comparison of Peer-to-Peer Overlay Network Schemes, IEEE Communications Survey and Tutorial, March 2004.
[Rodrigues]
Rodrigo Rodrigues, and Peter Druschel, Peer-toPeer Systems
Optional Reading
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Presentation Overview Structured P2P Networks
Unstructured P2P Networks Overlay Networks File Distribution Example Introduction Lecture Outline
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Presentation Overview Structured P2P Networks
Unstructured P2P Networks Overlay Networks File Distribution Example Introduction Lecture Outline
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Client-Server Limitations • • • •
Scalability is hard to achieve Presents a single point of failure Requires administration Unused resources at the network edge
P2P systems try to address these limitations
Introduction C/S Limitations
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Defintion of P2P 1) Significant autonomy from central servers
2) Exploits resources at the edges of the Internet – storage and content – CPU cycles – human presence
3) Resources at edge have intermittent connectivity, being added & removed Introduction Definition of P2P
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It’s a broad definition: • P2P file sharing – Napster, Gnutella, KaZaA, etc
• P2P communication – Instant messaging
• P2P computation
• DHTs & their apps – Chord, CAN, Pastry, Tapestry
• P2P apps built over emerging overlays – PlanetLab
– seti@home
Introduction Definition of P2P
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Pure P2P architecture • no always-on server • arbitrary end systems directly communicate • peers are intermittently connected and change IP addresses
Introduction Pure P2P Architecture
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Characteristics of P2P Networks • Clients are also servers and routers – Nodes contribute content, storage, memory, CPU
• Nodes are autonomous (no administrative • authority) • Network is dynamic: nodes enter and leave the network “frequently” • Nodes collaborate directly with each other (not through well-known servers) • Nodes have widely varying capabilities Introduction Characteristics of P2P Networks
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Benefits of P2P Networks • Efficient use of resources – Unused bandwidth, storage, processing power at the edge of the network
• Scalability – Consumers of resources also donate resources – Aggregate resources grow naturally with utilization Introduction Benefits of P2P Networks
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Benefits of P2P Networks • Reliability – Replicas – Geographic distribution – No single point of failure
• Ease of administration – Nodes self organize – No need to deploy servers to satisfy demand (c.f. scalability) – Built-in fault tolerance, replication, and load balancing Introduction Benefits of P2P Networks
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Key Issues in P2P Networks • Join/leave – How do nodes join/leave? Who is allowed?
• Search and retrieval – How to find content? – How are metadata indexes built, stored, distributed?
• Content Distribution – Where is content stored? How is it downloaded and retrieved? Introduction Key Issues P2P Networks
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Four Key Primitives (APIs) • Join – How to enter/leave the P2P system?
• Publish – How to advertise a file?
• Search – how to find a file?
• Fetch – how to download a file? Introduction Four Key Primitives
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Presentation Overview Structured P2P Networks
Unstructured P2P Networks Overlay Networks File Distribution Example Introduction Lecture Outline
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File Distribution: Client-Server vs Peer-to-Peer Question: how much time to distribute file (size F) from one server to N peers? – peer upload/download capacity is limited resource
F bits
Internet
File Distribution Example The Problem
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Server Distributing a Large File d4
F bits
upload rate us
Internet d1
d3
d2
upload rates ui download rates di File Distribution Example Server Distributing a Large File
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Server Distributing a Large File • Sending an F-bit file to N receivers – Transmitting NF bits at rate us – … takes at least NF/us time
• Receiving the data at the slowest receiver – Slowest receiver has download rate dmin= mini{di} – … takes at least F/dmin time
• Download time: max{NF/us , F/dmin}
File Distribution Example Server Distributing a Large File
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Speeding Up the File Distribution • Increase the server upload rate – Higher link bandwidth at the server – Multiple servers, each with their own link
• Alternative: have the receivers help – Receivers get a copy of the data – … and redistribute to other receivers – To reduce the burden on the server File Distribution Example Speeding up the File Distribution
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Peers Help Distributing a Large File F bits
d4
upload rate us
u4 Internet
d3
d1 u2 u1
u3
d2
upload rates ui download rates di 22
File Distribution Example Peer Helpout
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Peers Help Distributing a Large File • Components of distribution latency – Server must send each bit: min time F/us – Slowest peer must receive each bit: min time F/dmin
• Upload time using all upload resources – Total number of bits: NF – Total upload bandwidth us + sumi(ui)
• Total: max{F/us , F/dmin , NF/(us+sumi(ui))} 23
File Distribution Example Peer Helpout
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Peer-to-Peer is Self-Scaling • Download time grows slowly with N – Client-server: max{NF/u s, F/dmin} – Peer-to-peer: max{F/us , F/dmin , NF/(us+sumi(ui))}
• But… – Peers may come and go – Peers need to find each other – Peers need to be willing to help each other
24
File Distribution Example P2P is Self-Scaling
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Client-server vs. P2P: example client upload rate = u, F/u = 1 hour, us = 10u, dmin ≥ us
Minimum Distribution Time
3.5 P2P Client-Server
3 2.5 2 1.5 1 0.5 0 0
5
10
15
20
25
30
35
N
File Distribution Example Comparison
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P2P file distribution: BitTorrent • file divided into 256Kb chunks • peers in torrent send/receive file chunks tracker: tracks peers participating in torrent
torrent: group of peers exchanging chunks of a file
Alice arrives … … obtains list of peers from tracker … and begins exchanging file chunks with peers in torrent
File Distribution Example BitTorrent
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Presentation Overview Structured P2P Networks
Unstructured P2P Networks Overlay Networks File Distribution Example Introduction Lecture Outline
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Overlay networks overlay edge
Overlay Networks
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Overlay graph Virtual edge • TCP connection • or simply a pointer to an IP address Overlay maintenance • Periodically ping to make sure neighbor is still alive • Or verify liveness while messaging • If neighbor goes down, may want to establish new edge • New node needs to bootstrap Overlay Networks Overlay Graph
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Overlays: all in the application layer Tremendous design flexibility – – – –
application transport network data link physical
Topology, maintenance Message types Protocol Messaging over TCP or UDP
Underlying physical net is transparent to developer
application transport network data link physical
application transport network data link physical
– But some overlays exploit proximity Overlay Networks Overlays @ Application Layer
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Overlay Networks – Normal View
Overlay Networks Normal View
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Overlay Networks Focus at the application level
Overlay Networks Application Level View
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Examples of overlays • • • •
DNS BGP routers and their peering relationships Content distribution networks (CDNs) Application-level multicast – economical way around barriers to IP multicast
• And P2P apps ! Overlay Networks Examples of Overlays
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More about overlays Unstructured overlays • e.g., new node randomly chooses three existing nodes as neighbors Structured overlays • e.g., edges arranged in restrictive structure Proximity • Not necessarily taken into account Overlay Networks More about Overlays
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Presentation Overview Structured P2P Networks
Unstructured P2P Networks Overlay Networks File Distribution Example Introduction Lecture Outline
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Unstructured P2P Networks • • • •
Central Server / Directory (Napster) Flooding (Gnutella) Super Peers / Super Nodes (KaZaA) Swarming (BitTorrent)
Unstructured P2P Networks Types
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Central Server / Directory centralized directory
Join and Publish File list and IP address is uploaded
A
1
1
C
1 B
Unstructured P2P Networks Central Server
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Central Server / Directory Search (a) User requests file search at server (b) Server responds with list of hosts (IP addresses) containing the file.
Unstructured P2P Networks Central Server
centralized directory
2b
2a
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Central Server / Directory Fetch
centralized directory
(a) User pings the sources that have the data (Looks for host with best bandwidth)
Pings
Unstructured P2P Networks Central Server
Pings
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Central Server / Directory Fetch (a) User pings the sources that have the data (Looks for host with best bandwidth) (b) Downloads the file
centralized directory
Downloads the file
Unstructured P2P Networks Central Server
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Pros and Cons of Central Server Pros: • Simple • Search scope is O(1) • Controllable (pro or con?) Cons: • Server maintains O(N) State • Server does all processing • Single point of failure Unstructured P2P Networks Central Server
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Unstructured P2P Networks • • • •
Central Server / Directory (Napster) Flooding (Gnutella) Super Peers / Super Nodes (KaZaA) Swarming (BitTorrent)
Unstructured P2P Networks Types
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Query Flooding • Join – contact a few nodes to become neighbors
• Publish – no need!
• Search – ask neighbors, who ask their neighbors
• Fetch – get file directly from another node
Unstructured P2P Networks Flooding
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Search by Flooding
xyz.mp3
search
xyz.mp3 ?
Flooding
Unstructured P2P Networks Flooding
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Search by Flooding
xyz.mp3 xyz.mp3 ?
Flooding search
Unstructured P2P Networks Flooding
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Search by Flooding
transfer
Unstructured P2P Networks Flooding
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Flooding: Pros and Cons • Advantages – Fully decentralized – Search cost distributed – Processing per node permits powerful search semantics
• Disadvantages – Search scope is O(N) – Search time may be quite long – High overhead, and nodes come and go often Unstructured P2P Networks Flooding
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Unstructured P2P Networks • • • •
Central Server / Directory (Napster) Flooding (Gnutella) Super Peers / Super Nodes (KaZaA) Swarming (BitTorrent)
Unstructured P2P Networks Types
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Super Node Hierarchy • Join – on start, the client contacts a super-node
• Publish – client sends list of files to its super-node
• Search – queries flooded among super-nodes
• Fetch – get file directly from one or more peers
Unstructured P2P Networks Super Nodes Hierarchy
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Motivation for Super Nodes • Query consolidation – Many connected nodes may have only a few files – Propagating query to a sub-node may take more time than for the super-node to answer itself
• Stability – Super-node selection favors nodes with high uptime – How long you’ve been on is a good predictor of how long you’ll be around in the future Unstructured P2P Networks Super Nodes Motivation
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Super Node Architecture • Each peer is either a super node or is assigned to a super node • Each super node knows about many other super nodes (almost mesh overlay) Unstructured P2P Networks Super Nodes Architecture
supernodes
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Super Node Architecture: After Join and Publish xyz.mp3
H3 supernodes
H3
H1
xyz.mp3
H2
abc.mp3 xyz.mp3
H1
abc.mp3
H2
xyz.mp3
Unstructured P2P Networks Super Nodes After Join and Publish
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Super Node Architecture: Search – Query Flooding xyz.mp3
H3 supernodes
xyz.mp3 ? H3
H1
xyz.mp3
H2
abc.mp3 xyz.mp3
H1
abc.mp3
H2
xyz.mp3
Unstructured P2P Networks Super Nodes Query Flooding
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Super Node Architecture: Search – Query Responses xyz.mp3
H3 supernodes
xyz.mp3 available at H1, H2, H3
H3
H1
xyz.mp3
H2
abc.mp3 xyz.mp3
H1
abc.mp3
H2
xyz.mp3
Unstructured P2P Networks Super Nodes Query Response
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Super Node Architecture: Search – Fetch xyz.mp3
H3 supernodes
H3
H1
xyz.mp3
H2
abc.mp3 xyz.mp3
H1
abc.mp3
H2
xyz.mp3
Parallel download of pieces of file possible Unstructured P2P Networks Super Nodes Fetch
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Pros and Cons of Super Nodes Pros: • Tries to take into account node heterogeneity: • Bandwidth • Host Computational Resources • Host Availability (?) • Can take into account network locality Cons: • Mechanisms easy to circumvent • Still no real guarantees on search scope or search time Unstructured P2P Networks Super Nodes
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Unstructured P2P Networks • • • •
Central Server / Directory (Napster) Flooding (Gnutella) Super Peers / Super Nodes (KaZaA) Swarming (BitTorrent)
Unstructured P2P Networks Types
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Swarming Swarming: Download from others who are downloading the same object at the same time • Join – contact centralized “tracker”server, get a list of peers.
• Publish – Run a tracker server.
• Search – Out-of-band. E.g., use Google to find a tracker for the file you want.
• Fetch – Download chunks of the file from your peers. Upload chunks you have to them. Unstructured P2P Networks Swarming
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BitTorrent: Publish/Join Tracker
Unstructured P2P Networks Swarming Publish / Join
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BitTorrent: Fetch
Unstructured P2P Networks Swarming Fetch
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Presentation Overview Structured P2P Networks
Unstructured P2P Networks Overlay Networks File Distribution Example Introduction Lecture Outline
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The Search (Routing) Problem N1 Key=“title” Value=MP3 data… Publisher
N2
Internet
N4
N5
Structured P2P Networks The Search Problem
N3
?
Client Lookup(“title”)
N6
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Routed Queries in Structured P2P Networks N2
N1 Publisher
N3
N4
Key=“title” Value=MP3 data…
N6
N7
Client Lookup(“title”)
N8
N9 In structured overlay networks, searching is equivalent to routing on the structure of the overlay. Structured P2P Networks Routing in Structured P2P Networks
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Distributed Hash Tables • Academic answer to p2p • Goals – Guatanteed lookup success – Provable bounds on search time – Provable scalability
• Makes some things harder – Fuzzy queries / full-text search / etc.
• Read-write, not read-only • Hot Topic in networking since introduction in ~2000/2001
Structured P2P Networks DHT
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DHT: Overview • Abstraction: a distributed “hash-table” (DHT) data structure: – put(id, item); – item = get(id);
• Implementation: nodes in system form a distributed data structure – Can be Ring, Tree, Hypercube, Skip List, Butterfly Network, ...
Structured P2P Networks DHT Overview
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DHT: Overview • Structured Overlay Routing: – Join: On startup, contact a “bootstrap” node and integrate yourself into the distributed data structure; get a node id – Publish: Route publication for file id toward a close node id along the data structure – Search: Route a query for file id toward a close node id. Data structure guarantees that query will meet the publication. – Fetch: Two options: • Publication contains actual file => fetch from where query stops • Publication says “I have file X” => query tells you 128.2.1.3 has X, use IP routing to get X from 128.2.1.3 Structured P2P Networks DHT Overview
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DHT as Library / Platform Distributed application put(key, data)
get (key)
data
Distributed hash table node
node
….
node
DHT provides the information look up service for P2P applications. • Nodes uniformly distributed across key space • Nodes form an overlay network • Nodes maintain list of neighbors in routing table • Decoupled from physical network topology Structured P2P Networks DHT as Library
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DHT Schemes for Structured P2P Networks • • • •
Chord Pastry Tapestry Content Addressable Network (CAN)
Structured P2P Networks DHT Schemes
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Chord Overview • Associate to each node and file a unique id in an unidimensional space (a Ring) – E.g., pick from the range [0...2m] – Usually the hash of the file or IP address
• Properties: – Routing table size is O(log N) , where N is the total number of nodes – Guarantees that a file is found in O(log N) hops
from MIT in 2001 Structured P2P Networks Chord Overview
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Chord IDs • • • •
Key identifier = SHA-1(key) Node identifier = SHA-1(IP address) Both are uniformly distributed Both exist in the same ID space
• How to map key IDs to node IDs? – The heart of Chord protocol is “consistent hashing” Structured P2P Networks Chord Chord IDs
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Chord API • • • • •
insert(key, value)à store key/value at r nodes lookup(key) update(key, newval) join(n) leave()
Structured P2P Networks Chord Chord API
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DHT: Consistent Hashing Key 5
Node 105
K5
N105
K20
Circular ID space
N32
N90 K80 A key is stored at its successor: node with next higher ID Structured P2P Networks Chord Consistent Hashing
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DHT: Chord Basic Lookup N120 N10
“Where is key 80?”
N105
“N90 has K80”
K80
N32
N90
N60
Structured P2P Networks Chord Basic Lookup
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Basic Chord Lookup (Routing) Algorithm Lookup(my-id, key-id) n = my successor if my-id < n < key-id Lookup(id) on node n /go to next hop/ else return my successor /found the correct node/
• Correctness depends only on successors • O(N) lookup time, but we can do better
Structured P2P Networks Chord Basic Lookup Algorithm
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DHT: Chord “Finger Table” 1/4
1/2
1/8
1/16 1/32 1/64 1/128
N80
• Entry i in the finger table of node n is the first node that succeeds or equals n + 2i • In other words, the ith finger points 1/2n-i way around the ring Structured P2P Networks Chord Finger Table
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DHT: Chord Join • Assume an identifier space [0..8] • Node n1 joins
Succ. Table i id+2i succ 0 2 1 1 3 1 2 5 1
0 1
7
6
2
5
3 4
Structured P2P Networks Chord Join
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DHT: Chord Join • Node n2 joins
Succ. Table i id+2i succ 0 2 2 1 3 1 2 5 1
0 1
7
6
2
Succ. Table
5
3 4
Structured P2P Networks Chord Join
i id+2i succ 0 3 1 1 4 1 2 6 1
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DHT: Chord Join Succ. Table
• Nodes n0, n6 join
i id+2i succ 0 1 1 1 2 2 2 4 0
Succ. Table i id+2i succ 0 2 2 1 3 6 2 5 6
0 1
7 Succ. Table i id+2i succ 0 7 0 1 0 0 2 2 2
6
2
Succ. Table
5
3 4
Structured P2P Networks Chord Join
i id+2i succ 0 3 6 1 4 6 2 6 6
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DHT: Chord Join Succ. Table i
i id+2 0 1 1 2 2 4
• Nodes: n1, n2, n0, n6 • Items: f7, f2
Items 7 succ 1 2 0 Succ. Table
0 1
7
Succ. Table
6
i id+2i succ 0 7 0 1 0 0 2 2 2
2
Succ. Table i
5
3 4
Structured P2P Networks Chord Join
i id+2i succ 0 2 2 1 3 6 2 5 6
i id+2 0 3 1 4 2 6
Items succ 1 6 6 6
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DHT: Chord Routing Succ. Table
• Upon receiving a query for item id, a node: • Checks whether stores the item locally • If not, forwards the query to the largest node in its successor table that does not exceed id Succ. Table
i id+2i succ 0 7 0 1 0 0 2 2 2
i
i id+2 0 1 1 2 2 4
Items 7 succ 1 2 0 Succ. Table
0 1
7
i id+2i succ 0 2 2 1 3 6 2 5 6
query(7)
6
2
Succ. Table i
5
3 4
Structured P2P Networks Chord Routing
i id+2 0 3 1 4 2 6
Items succ 1 6 6 6
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Chord Routing Algorithm Lookup(my-id, key-id) look in local finger table for highest node n such that my-id < n < key-id if n exists Lookup(id) on node n /go to next hop/ else return my successor /found the correct node/
Structured P2P Networks Chord Routing Algorithm
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Node Joining in Chord Node n joins the system: • n picks a random identifier, id • n performs n’= lookup(id) • n->successor = n’ • n’->predecessor = n
Structured P2P Networks Chord Node Joining
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State Maintenance: Stabilization Protocol • Periodically node n – Asks its successor, n’, about its predecessor n’’ – If n’’ is between n and n’ • n->successor = n’’ • notify n’’ that n is its predecessor
• When node n’’ receives notification message from n – If n is between n‘’->predecessor and n’’, then • n’’->predecessor = n
• Improve robustness – Each node maintain a successor list(usually of size 2*log N) Structured P2P Networks Chord State Maintenance
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DHT: Network Locality in Chord • Nodes close on a ring can be far on the network
Structured P2P Networks Chord Network Locality
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DHT: Chord Summary • Routing table size? –Log N fingers
• Routing time? –Each hop expects to 1/2 the distance to the desired id => expect O(log N) hops.
Structured P2P Networks Chord Summary
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DHT Schemes for Structured P2P Networks • • • •
Chord Pastry Tapestry Content Addressable Network (CAN)
Structured P2P Networks DHT Schemes
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Pastry: Overview • Similar interface to Chord • Considers network locality to minimize hops messages travel • New node needs to know a nearby node to achieve locality • Each routing hop matches the destination identifier by one more digit • Many choices in each hop (locality possible) Structured P2P Networks Pastry Overview
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Object Distribution 2128 - 1
O
objId
Consistent hashing [Karger et al. ‘97] 128 bit circular id space nodeIds (uniform random)
nodeIds
objIds (uniform random) Invariant: node with numerically closest nodeId maintains object
Structured P2P Networks Pastry Object Distribution
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Object Insertion/Lookup 2128 - 1
O
X
Route(X)
Msg with key X is routed to live node with nodeId closest to X
Problem: complete routing table not feasible
Structured P2P Networks Pastry Object Insertion/Lookup
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Routing (Lookup) in Pastry d471f1 d467c4 d462ba d46a1c d4213f
Route(d46a1c)
65a1fc
Structured P2P Networks Pastry Routing
d13da3
Properties • log16 N steps • O(log N) state
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Node Addition in Pastry d471f1 d467c4 d462ba d46a1c d4213f
New node: d46a1c
Route(d46a1c)
d13da3
65a1fc
Structured P2P Networks Pastry Node Addition
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DHT Schemes for Structured P2P Networks • • • •
Chord Pastry Tapestry Content Addressable Network (CAN)
Structured P2P Networks DHT Schemes
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What is Tapestry? • A prototype of a decentralized, scalable, fault-tolerant, adaptive location and routing infrastructure (Zhao, Kubiatowicz, Joseph et al. U.C. Berkeley)
• Network layer of OceanStore global storage system Suffix-based hypercube routing – Core system inspired by Plaxton Algorithm (Plaxton, Rajamaran, Richa (SPAA97))
• Core API: – publishObject(ObjectID, [serverID]) – sendmsgToObject(ObjectID) – sendmsgToNode(NodeID)
Structured P2P Networks Tapestry Overview
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Tapestry • Uses plaxton mesh data structure – allows nodes to locate objects and route messages to them across an arbitrary-sized network while using a small, constant-sized routing map at each hop – route map is called neighborhood map
• Ideas similar to pastry Structured P2P Networks Tapestry Overview
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Plaxton (Suffix) Routing Example from 67493 to 34567 destination path resolution order: xxxx7 xxx67 xx567 x4567 34567 x represents wild cards All the numbers are in base-10
Structured P2P Networks Tapestry Plaxton Routing
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Example Neighborhood Map • Suffix routing • Each entry points to next node in the neighborhood – A neighbor is a connected node to the present node
• Level corresponds to the number of matching digits
Neighbor Map For “5712” (Octal) 0712
x012
xx02
xxx0
1712
x112
5712
xxx1
2712
x212
xx22
5712
3712
x312
xx32
xxx3
4712
x412
xx42
xxx4
5712
x512
xx52
xxx5
6712
x612
xx62
xxx6
7712
5712
xx72
xxx7
4
3
2
1
Routing Levels
Structured P2P Networks Tapestry Neighborhood Map
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Another Suffix Routing Example Example: Octal digits, 218 namespace, 005712 627510
005712
0 1
2
3 4 5
6 7
00512
340880
0 1
2
3 4 5
6 7
340880
943210
0 1
2
3 4 5
6 7
943210
834510
0 1
2
3 4 5
6 7
833510
387510
0 1
2
3 4 5
6 7
387510
727510
0 1
2
3 4 5
6 7
727510
627510
0 1
2
3 4 5
6 7
627510
Structured P2P Networks Tapestry Plaxton Routing
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DHT Schemes for Structured P2P Networks • • • •
Chord Pastry Tapestry Content Addressable Network (CAN)
Structured P2P Networks DHT Schemes
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Content Addressable Network (CAN) • Associate to each node and item a unique id in an d-dimensional space • Properties – Routing table size O(d) – Guarantee that a file is found in at most d*n1/d steps, where n is the total number of nodes
Structured P2P Networks CAN Overview
EA C451 INET TECH
CAN Example: Two Dimensional Space • Space divided between nodes • All nodes cover the entire space • Each node covers either a square or a rectangular area of ratios 1:2 or 2:1 • Example: – Assume space size (8 x 8) – Node n1:(1, 2) first node that joins cover the entire space
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Structured P2P Networks CAN Example
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EA C451 INET TECH
CAN Example: Two Dimensional Space • Node n2:(4, 2) joins space is divided between n1 and n2
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EA C451 INET TECH
CAN Example: Two Dimensional Space • Node n2:(4, 2) joins space is divided between n1 and n2
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CAN Example: Two Dimensional Space • Nodes n4:(5, 5) and n5:(6,6) join 7 6
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EA C451 INET TECH
CAN Example: Two Dimensional Space • Nodes: n1:(1, 2); n2:(4,2); n3:(3, 5); n4:(5,5);n5:(6,6) • Items: f1:(2,3); f2:(5,1); f3:(2,1); f4:(7,5);
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EA C451 INET TECH
CAN Example: Two Dimensional Space • Each item is stored by the node who owns its mapping in the space
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EA C451 INET TECH
CAN: Query Example • Each node knows its neighbors in the d-space • Forward query to the neighbor that is closest to the query id • Example: assume n1 queries f4
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EA C451 INET TECH
