Kalman Graffi - IEEE ICC 2013 - Symbiotic Coupling of Peer-to-Peer and Cloud Systems: The Wikipedia...

Symbiotic Coupling of P2P and Cloud Systems: The Wikipedia Case

Lars Bremer, University of Paderborn, Germany

Kalman Graffi, University of Düsseldorf, Germany

Lars Bremer, Kalman Graffi: Symbiotic Coupling of P2P and Cloud Systems: The Wikipedia Case 2

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Background on Wikipedia

Wikipedia– Collaborative Internet Encylopaedia

Numbers on English Wikipedia– Alexa rank: 6– Article Count: 3.8 million– Edits: 3.4 million per month– Page Views: 11.3 million per hour

Figures show the popularity of articles– Top: All articles– Bottom: Top 250 articles

Problem: Costs through high traffic


Motivation and Outline of our Work

Goal: Efficiency increase– Cloud-like performance

• Maintain high data availability

• Quick article delivery

– Low operational costs• Users should help in sharing articles

• Donations of network resources

Approach– Combine peer-to-peer (p2p) and centralized (cloud) architecture– Cloud is used as backup and main hoster

• Much less traffic and costs

– Users participate in p2p overlay• Lookup articles first there

• Provide downloaded articles to other peers


Outline

Motivation / Use Case

Background on Structured P2P Overlays

Symbiotic Coupling of P2P and Cloud Systems

Evaluation

Conclusions


Background on Structured P2P Overlays

Nodes and objects use same ID space

Each object is managed by a node ( responsible)

Assignment based on IDs

Nodes maintain a topology / routing structure to support:

Lookup: getResponsibleNode(ID)

After that: e.g. data tranfer

H(„my data“)= 3107

2207

29063485

201116221008709

611

H(„my data“)= 3107

2207

29063485

201116221008709

611

Lookup

Data transfer


Cloud Computing vs. P2P Technology

Cloud and P2P– Access to a distributed pool of

resources:• Storage, bandwidth, computational

power

Cloud computing– Resource providers: companies– Controlled environment

• No (/minimal) churn • Homogenous devices

– Selective centralized structures – Mainly paid by usage

P2P systems– Resource providers: user devices– Uncontrolled environment

• Churn• Heterogeneous devices• Uncertainty / unpredictability• Distributed access points


Symbiotic Coupling of P2P and Cloud Systems

Goal: High performance at low costs– Performance: data availability, low delays– Costs: traffic at cloud operator (linked to monetary expenses)

Our approach– Main service (here Wikipedia) remains as main data pool– Nodes install an (p2p) addon p2p overlay

• Allows to share content of specific services

– Nodes visiting Wikipedia• Join the p2p overlay and remain online for a while

– Articles are served and provided in p2p overlay– If not available / initially: download from cloud


Overview on the Architecture

Document space– Article ID is hashed article name– Responsible node maintains

list of articles providers– Article providers

• Downloaded once the article

• Registered at resp. node

We use Chord– Any other DHT also fine– Needs to support

Key-based Routing


Operation: Initial Lookup for an Article


Operation: Further Lookup for an Article


Other Operations

Update– Editing done on the Cloud– Active vs. passive updates

• Active: Cloud actively informs node holding references

• Passive: Responsible peers periodically check for updates– Frequency based on object popularity

– Old references are discarded• They point to outdated content

– New reference table is built-up

Leave– Leaving node informs all nodes holding references to it– Can also be detected, but introduces delay


Evaluation

Main questions– What is the efficiency gain?– How much traffic is saved?

Approach– Evaluation through simulation

Layer setup– User mode: downscaled Wikipedia workload– Application: document storage– Overlay: Chord– Network model:

• Global Network Positioning delay model

• OECD bandwidth model


► PeerfactSim.KOM (see www.peerfact.org)

Type– Event-based simulator– Written in Java– Simulations up to 100K peers possible– Focus on simulation of p2p systems on various layers

• User

• Application

• Services: monitoring, replication …

• Overlays

• Network models

Invitation to join the community– Several universities use and extend the simulator actively– Used and heavily extended in the project


Layered View

Layered Architecture– Easy exchange of components– Testing of new applications– Testing of new mechanisms

Main idea– Layers have several implementations– Enables testing of individual layer

mechanisms• on its own

• in combination with other layers

See www.peerfact.org

Application

Overlay

User

Sim

ulation E

ngin

e

Network

Service

Transport

Application

Overlay

User

Sim

ulation E

ngin

e

Network

Service

Transport


Simulation Setup / Workload Model


Simulation Results


Simulation Results


Simulation Results


Conclusions and Future Work

Symbiotic p2p/cloud approach lowers operational costs– Users take load and share content– Traffic load on server was reduced to 27.6% in this experiment– Websites with many users can benefit from p2p support– WebP2P – browser-based p2p via peerjs, nodejs, etc. is coming– User devices are powerful, load can be handled „for free“

Future Work– Investigate WebP2P approach

• Browser plugin to create p2p overlay

– Create p2p framework for social networks• Use capacity of user devices to host a social network• See http://www.p2pframework.com

– Further extend PeerfactSim.KOM – the p2p system simulator• See http://www.peerfact.org


Thank You for Your Attention

Jun.-Prof. Dr.-Ing. Kalman Graffi Technology of Social Networks GroupInstitute of Computer ScienceHeinrich-Heine-Universität Düsseldorf

eMail: [email protected] Web: www.p2pframework.com

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Date post:	15-Jun-2015
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