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Allocation in Application Layer Networks
T. Eymann, M. ReinickeAlbert-Ludwigs-University, Freiburg (DE)O. Ardaiz, P. Artigas, L. Díaz de Cerio, F. Freitag, R. Messeguer, L. Navarro, D. RoyoUniversitat Politècnica de Catalunya, Barcelona (ES)
CATNET project – Open Research, Evaluation(3/2002-3/2003)
Exploring Decentralized Resource
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Problem: Provisioning services Requiring (huge amount of) resources From large number of computers CDN, Grid and P2P
Objective: evaluation of decentralized mechanism for resource allocation, based on economic paradigm: Catallaxy. (compare against a centralized mechanism using an arbitrator object)A concrete case for an application is, for instance, the distributed provisioning of web services for Adobe’s Acrobat (for creating PDF files) in an Akamai-like application layer network.
Problem and objective
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Application Layer Networks (ALN)
Application layer networks are software architectures that allow the provisioning of services requiring a huge amount of resources by connecting large numbers of individual computers. They are built over a base network that is used to support this second network, “layered” upon the underlying infrastructure.Motivation:
ALN have dynamic demands Deployment/Allocation Requirements:
Programable Infrastructure: Nodes with BW, Storage & Processing Resources.
Deployment/Allocation Mechanisms: Resource Allocation Algorithm, ….
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ALN Lifecycle
Phases: Deployment: initial positioning of
resources. Deployment can also be economically modeled, although we treat as if done.
Allocation: main focus here. Allocates resources for the demands. Changes resource locations:
Migrate Clone
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Catallaxy BasicsCatallaxy is an alternative word for “market economy” (Mises and Von Hayek of the Neo-austrian economic school)
“Fundamentally, in a system in which the knowledge of the relevant facts is dispersed among many people, prices can act to co-ordinate the separate actions of different people in the same way as subjective values help the individual to co-ordinate the parts of his plan.”
(Friedrich A. von Hayek, The Use of Knowledge in Society, 1945)
“The Market” as a technically decentralized, distributed, dynamic coordination mechanism Adam Smith’s “invisible hand” Hayek’s “spontaneous order” Walras’ “non-tâtonnement process”
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CatallaxyCoordination mechanism for systems consisting of autonomous decentralized devices.Based on constant negotiation and price signalingBased on efforts from both agent technology and economicsAgents are able to adapt their strategies using machine learning mechanisms
Evolution of software agent strategies, a stabilization of prices throughout the system and self-regulating coordination patterns
Earlier work has used economic principles for resource allocation in distributed computer systems, but most of these approaches rely on using a centralized auctioneer
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Catallaxy propertiesSpontaneous order of the participants
„Unplanned result of individuals' planful actions“ (Hayek)
Constitutive Elements of the Catallaxy Access to a Market
Knowledge about availability of resources is transported through price information
Constitutional Ignorance Self-interest and autonomy
of participants Ability to choose between
alternative actions
Learning Dynamic Co-Evolution Income expectations and
price relations stabilize development
Problems Tragedy of commons Free riding
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Catnet Properties
Agent-based solution is always inferior to analytical optimizationInformation The more information is available, the more
accurate are the choices The more agents, the more information existsComputation Computation is fully parallel (no central
bottleneck) Solution always exists in the system (no non-
allocated resource)
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Agents State
Agents genotype: Acquisitiveness Satisfaction Price Step Price Next Weight Memory Reputation
For each service: Price Distribution
For each negotiation: Negotiation History
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Parameters to measure
Social Welfare (SWF): Sum of all utilities over all participants, in a
given timespan Clients subjectively value SC access Prices change due to “supply and demand”
Individual utility = transaction price – market value
Also: Response Time (REST), Resource allocation efficiency (RAE), Communication cost (CC), Client-Resource assignment distance.
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Experimental Simulator
Abstracts from a concrete application and implementation.Allows „plug-in“ of different „middleware“ resource allocation mechanisms. Allows easy changes of
Decentralized agent strategies Centralized allocation mechanisms.
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Simulation of ALNs
CDN P2P
GRIDA few, powerful
A lot, modest
Fix
ed
netw
orks
Mob
ile, a
d-ho
c,ov
erlo
ade
dne
twor
ks
Stable
Changing
node density
node dynamics
low medium high
medium
high
CDN
P2P
GRID
In an “abstract” simulator
ALN
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• Javasim models almost every aspect of a real network: latency, bandwith, lost packets, routing, …
• It has some of the more common internet protocols like DV, TCP, UDP, …
• So our components can be easily modified to work in the real world changing the middleware to real sockets.
JavasimThe Catnet simulator is build over JavaSim, JavaSim is a network simulator based in autonomous components.
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Components
On top of the physical nodes, a number of different software agents are created, which form the application layer network:
Client (C): computer program at host, requests service
Service Copy (SC): instance of service, hosted in a resource computer
Resource (R): host computer with limited storage and bandwidth
R Port 101
C Port 102
SC Port 103
UDPIP
- Independent on each other at javasim level
- Running as programs with a socket on a computer
- Configuration made at startup script
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Catallactic Message Flow
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Components
Generic behaviour on messages
Using generic functions:
- Bargain/RecommendedAction
- Price management
So changing strategies is easy
Particular behaviour on some messages
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Configuration
We use TCl to set-up the experiments: Topology Node configuration: wich components
(C/R/SC/MSC) should be on each node. Application Layer Network initialitzation Agent parameters: bandwith, price
ranges, money balance, genotype, … Current experiment parameters
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Output - 1
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Output - 2
(Catallaxy shows development over time)
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Output - 3
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Soundness of Criteria
Interdepencies SWF and RAE are dependent
Every transaction adds to SWF More transactions add to RAE
SWF and CC are dependent Higher CC lowers SWF
SWF and REST are dependent Higher REST means more transactions More transactions add to RAE and SWF
SWF captures all costs and revenuesDependencies are an emergent feature of the system No direct links have been implemented: economic
reasoning works „bottom-up“ in an ACE sense
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Conclusions
Initial simulation results prove that a decentralized, economic model works better in certain situations. “Better” is a combination of factors
(SWF)
Promising: Large scale Dynamic Saturation
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Future
Future research work: Agent technology layer Application-specific layer
Both are linked in a feedback loop.
Also: A lot of influencing parameters apart
from Density and Dynamism, not fully evaluated due to time constraints.
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END
Any questions?
More info on http://research.ac.upc.es/catnet/