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

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

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, ….

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

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”

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

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

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)

Agents State

Agents genotype: Acquisitiveness Satisfaction Price Step Price Next Weight Memory Reputation

For each service: Price Distribution

For each negotiation: Negotiation History

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.

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.

Simulation of ALNs

CDN P2P

GRIDA few, powerful

A lot, modest

Fix

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Stable

Changing

node density

node dynamics

low medium high

medium

high

CDN

P2P

GRID

In an “abstract” simulator

ALN

• 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.

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

Catallactic Message Flow

Components

Generic behaviour on messages

Using generic functions:

- Bargain/RecommendedAction

- Price management

So changing strategies is easy

Particular behaviour on some messages

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

Output - 1

Output - 2

(Catallaxy shows development over time)

Output - 3

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

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

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.

END

Any questions?

More info on http://research.ac.upc.es/catnet/