bio inspired peer to peer systems

7/30/2019 bio inspired peer to peer systems

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Bio Inspired Peer-to-Peer Systems(Inspired by Ant Colonies)

Research Paper - RAFFAELE GIORDANELLI andCARLO MASTROIANNI, ICAR-CNR

and eco4cloud srl, Italy

MICHELA MEO, Politecnico di Torino, Italy

Navneet Gupta109403CO - 3


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Content

Centralized Information Systems

(Semi-)Decentralized Information Systems Lessons Learned from Napster

Fully Decentralized Information Systems

Self-Organization

Resource Location in P2P Systems

Unstructured P2P Overlay Networks Protocol Message Types

Hierarchical P2P Overlay Networks

Structured P2P Overlay Networks A GENERALIZED ANT-INSPIRED STRATEGY FOR STRUCTURED P2P

SYSTEMS Algorithm

Description

Multi Dimensional Overlay

Conclusion


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Web search engine Global scale application

Example: Google

Centralized Information Systems

Google: 15000 servers

1

Find"aberer"

2

Resulthome page of Karl Aberer

GoogleServer

Client

Client

Client

ClientClient

Client

Client

Client

Client

Client

Strengths Fast response time

Weaknesses Infrastructure, administration, cost

A new company for every global application ?


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(Semi-)Decentralized Information Systems

P2P Music file sharing Global scale application

Example: Napster 1.57 Mio. Users

10 TeraByte of data(2 Mio songs, 220 songs per user)(February 2001)

1

Find

"brick in the wall" "pink floyd" "1 MB" "rock" schema

2

Resultyou find f.mp3 at peer x

3

Request and transfer filef.mp3from peer X directly

NapsterServer

Peer

Peer

Peer

PeerPeer

Peer

Peer

Peer

Peer

PeerX

Napster: 100 servers


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Lessons Learned from Napster

Strengths: Resource Sharing Every node pays its participation by providing access to its resources

physical resources (disk, network), knowledge (annotations), ownership (files)

Every participating node acts as both a client and a server : P2P

global information system without huge investment

decentralization of cost and administration = avoiding resource bottlenecks

Weaknesses: Centralization server is single point of failure

copying copyrighted material made Napster target of legal attack

Centralized

System

Decentralized

System

increasing degree of resource sharing and decentralization


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Fully Decentralized Information Systems

P2P file sharing Global scale application

Example: Gnutella 40.000 nodes, 3 Mio files

(August 2000)

Gnutella: no servers

Strengths No infrastructure, no administration

No single point of failure

Weaknesses High network traffic

No structured search

Free-riding

Find"brick in the wall"

I have"brick_in_the_wall.mp3".

Self-organizing System


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Self-Organization

Self-organized systems well known from physics, biology, cybernetics distribution of control ( = decentralization = symmetry in roles = P2P) local interactions, information and decisions

emergence of global structures

failure resilience

Each component acts locally and autonomously based on local information on

the state of the system. Self-organizing systems exhibit structures andstructured behavior, that are not enforced by some outside entity, but thatemerge from the aggregation of the local interactions of the components ofthe systems


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Resource Location in P2P Systems

Problem: Peers need to locate distributed information Peers with address p store data items d that are identified by a key kd Given a key kd (or a predicate on kd) locate a peer that stores d,

i.e. locate the index information(kd, p)

Thus, the data we have to manage consists of the key-value pairs (kd, p)

Can such a distributed database be maintained and accessed by a set ofpeers without central control ?

P1

P2 P3

P4

P5

P6P7

P8kd="xyz"p="P8"

d=xyz.docx"

kd ="xyz" ?

(xyz",P8)


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1. Unstructured P2P Overlay Networks

No index information is used i.e. the information (k, p) is only available directly from p

Simplest approach: Message Flooding (Gossiping) send query message to C neighbors

messages have limited time-to-live TTL

messages have IDs to eliminate cycles

k=xyz"

Example: C=3, TTL=2


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Protocol Message Types

Type Description Contained Information

Ping Announce availability and probe forother servents

None

Pong Response to a ping IP address and port# of responding servent;number and total kb of files shared

Query Search request Minimum network bandwidth of respondingservent; search criteria

QueryHit Returned by servents that havethe requested file

IP address, port# and network bandwidth of

responding servent; number of results and

result set

Push File download requests for

servents behind a firewall

Servent identifier; index of requested file; IP

address and port to send file to


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CA

B D

EAs pingBs pongCs pong

Ds pong

Es pong


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Searching (Query/QueryHit/GET)

CA

B D

EAs query (e.g., X.mp3)Cs query hit

Es query hit

X.mp3

X.mp3

GET X.mp3 X.mp3


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2. Hierarchical P2P Overlay Networks

Servers provide index information, i.e. the information (k, p) is availablefrom dedicated servers

Simplest Approach one central server

user register files

service (file exchange) is organized

as P2P architecture

k="jingle-bells"

index server


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Napster

Central (virtual) database which holds an index of offered MP3/WMAfiles

Clients connect to this server, identify themselves (account) and send alist of MP3/WMA files they are sharing (C/S)

Other clients can search the index and learn from which clients they canretrieve the file (P2P)

Additional services at server (chat etc.)

A B

Napster Serverregister

(user, files)

Ahas X.wmv

Download X.wmv


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3. Structured P2P Overlay Networks

Peers are organized in accordance with a predefined logical structure ring, multi-dimensional grid, tree and resources are assigned to peerswith a precise strategy.

These are generally based on DHT, whose purpose is to assign keys toresources, and indexes to peers, by means of hash functions.

Each peer is responsible for a portion of the key space, and is requiredto manage the keys belonging to this portion.

However, the use of hash functions has an important drawback: since

similar resources are mapped to completely different keys, they aregenerally assigned to peers that are located far from each other in theoverlay. This hinders the efficient execution of queries for resourceshaving similar characteristics, or range queries.


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Distribution of Index Information

Goal: provide efficient search using few messages without usingdesignated servers

Easy: distribution of index information over all peers, i.e. every peermaintains and provides part of the index information (k, p)

Difficult: distributing the data access structure to support efficientsearch

index information I

server

data access

structure

peers (storing data)

peers (storing data and index information)

I1 I2 I3 I4

?

Search starts here

Where to start the search?


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Topological Routing (CAN)

Based on hashing of keys into a d-dimensional space (a torus) Each peer is responsible for keys of a subvolume of the space (a zone) Each peer stores the adresses of peers responsible for the neighboring

zones for routing

Search requests are greedily forwarded to the peers in the closest zones

Assignment of peers to zones depends on a random selection made bythe peer


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A GENERALIZED ANT-INSPIRED STRATEGY FORSTRUCTURED P2P SYSTEMS

INSPIRATION

In any kind of structured P2P systems, the main objective is to provideclients a way to rapidly discover the desired resources along thedistributed overlay.

This is done exploiting the Distributed Hash Table paradigm: everyresource is given a key using a hash function applied to the resourcename, and the key is assigned to a node of the structure whose code isequal or very close to the resource key.

The hash function is needed to fairly distribute the resources over thestructure, but this is possible only if the popularity of the resources isuniform. If this is not the case, some peers may be overloaded, sinceresources with the same name are mapped to the same peer.


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Moreover, the keys of resources having similar features are inevitablydispersed. This prevents the possibility of executing a range queryefficiently, since the target resources are most likely to be located indifferent and remote regions of the network.


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Use Of Swarm Intelligence

The basic idea is to use resource attribute(s) directly as the key,without using any hash function, and adopt an ant-inspired algorithm tosort the keys over the structure and, at the same time, distribute themto the peers in a fair fashion.

This implies that resource keys are decoupled and independent from

peer codes, while the two entities are strictly correlated in classical P2Psystems.


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PREREQUISITES

First, it is necessary to choose the overlay that best fits the type ofattributes used for indexing and searching the resources.

The second step is to define, for each peer, its centroid. The peercentroid must represent, with a single quantity, the set of keys storedin a local region of the structure that comprises the peer itself and a

few close-by peers.

Finally, a set of mobile agents must be generated to perform thereorganization. The agents use the underlying structure to travel thesystem, but do not alter the structure and the way it is managed.


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ALGORITHM

The agent can either be loaded, when it is moving a key between peers,or unloaded.

When unloaded, the agent travels the P2P overlay structure performinga random walk through neighbouring peers. Whenever the agent visits anew peer, it attempts to pick a key from the peer.

If a pick operation succeeds, the agent becomes loaded and starts aprocess aiming at dropping the key in a more appropriate peer.

Thus, a loaded agent carrying a key k moves towards a region of the

overlay structure that islikely populated with keys that are similar (orclose) to k.

The agent moves makingjumps towards the desired region. Finally,whenever a loaded agent visits a new peer, it attempts to drop the key.


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Ants Swarming in a Ring: the Self-Chord System

Self-Chord is a structured P2P systems, uses the ring-shaped overlay toestablish P2P interconnections, but distributes resource keys amongpeers using the operations of ant-inspired mobile agents.

A mobile agent arrives at a peer with centroid C=30, picks key 55, andthen hops to a region of the ring where peers are supposed to havecentroids close to 55.


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Four macro operations are identified:Random Walk, Pick, Jump and Drop.

Random Walk - While the agent is unloaded (does not carry any key), ittravels the network randomly, exploiting the links towards other peersthat are provided by the specific overlay.

Pick -The goal of this operation is to pick a key that, being far from thecentroid (i.e., different from the keys typically stored in the peer).

Jump- Once the agent has picked a key, it jumps to a region of theoverlay wherethe key is supposed to better respect the currentsorting.

Drop - The objective is to drop the carried key in a peer that holdssimilar keys.


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DESCRIPTION

The collective operations of agents sort both the centroids and the keysover the corresponding overlay.

A notable improvement of the new strategy is that resource keys can begiven a semantic meaning, which implies that similar resources arestored in neighbour peers and range queries can be executed efficiently.

Indeed, once a search message has found a key included in the targetrange specified in the query, all the other keys can be discovered veryrapidly, exploring the neighbour peers.

This efficiency is very hard to obtain in classical P2P systems, becausethe keys of similar resources are spread by the hash function.


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Each peer, at the time that it connects to the network, generates anagent with a probability Pgen.

The average number of agents Na that circulatein the network at agiven instant of time is associated with the average number of peersconnected in the network at the same time, Np,

Na= Np Pgen

2006, Karl Aberer, Manfred Hauswirth - EPFL-IC, Laboratoire de systmes d'informations rpartis


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The ant-inspired strategy has furtherinteresting properties

it is self-organizing, as the assignment of keys is not predetermined butemerges from the combined behaviour of very simple agents;

it is completely decentralized, since agent operations are exclusivelydriven by local information;

it guarantees stability: once a correct sorting has been achieved, it isquickly recovered

it ensures a fair load balance, even in the presence of non uniform keypopularity.


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Ant Based Strategy Applied to Diff. Overlays

RING OVERLAY If a resource can be characterized by the value of a single attribute.

The local region centered at a peer includes the peer itself, number ofpeers on the left, and the same number of peers on the right.

For this scenario, agent operations can be instantiated as follows.

Random Walk. The unloaded agent travels from adjacent to adjacentpeer.

Jump. The agent examines the peers and jumps to the one that is theclosest to the target peer.

Pick and Drop. Pick and drop probability functions are, respectively,directly and inversely proportional to the distance between theconsidered key and the local centroid.


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MultiDimensional Overlay

A multidimensional overlay is preferable when a resource is convenientlycharacterized by several independent attributes.

Example - a Grid/Cloud infrastructure in which the hosts arecharacterized by CPU,memory, and bandwidth.

Agent operations are specialized as follows -

Random Walk. The agent travels from adjacent to adjacent peer,randomly choosing both the dimension and the direction.

Pick. As usual, a key should be picked when its distance from the localcentroid is high.

Jump. The agent moves along the dimension that allows to minimize the

distancebetween the carried key and the centroid of the target peer.Drop. An agent that arrives at a new peer should drop the carried keyif its valueis similar to the peer centroid.


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CONCLUSION

This article has presented a generalized ant-inspired approach that canbe used to sort the resource keys over any kind of P2P overlay.

The process sorting, performed through the pick and drop operations of

mobile agents, is statistically driven, self-organising, and decentralized.

This enables the possibility of preserving the values of significantresource attributes into the resource keys, instead of generating thelatter with hash functions.

The advantages of this approach are numerous, ranging from a more

efficient execution of complex queries to improved behaviour in termsof adaptivity and load balancing.


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Refrences

Bio-Inspired P2P Systems: The Case of Multidimensional Overlay byRAFFAELE GIORDANELLI and CARLO MASTROIANNI, ICAR-CNR andeco4cloud srl, Italy MICHELA MEO, Politecnico di Torino, Italy.

Peer To Peer Networking :Configuring Issues and DistributedProgramming by ODD ARILDSKAFLESTAD and NINA KAUREL


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Thank you!!

Questions ?

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bio inspired peer to peer systems

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