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Exploring Decentralized Resource
Allocation in Application Layer Networks
T. Eymann, M. Reinicke
Albert-Ludwigs-University,
Freiburg (DE)
O. Ardaiz, P. Artigas, L. Díaz de Cerio, F. Freitag,
R. Messeguer, L. Navarro, D. Royo
Universitat Politècnica de Catalunya,
Barcelona (ES)
CATNET project – Open Research, Evaluation
(3/2002-3/2003)
Problem and objective
Problem: Provisioning services
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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.
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:
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ALN have dynamic demands
Deployment/Allocation Requirements:
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Programable Infrastructure:
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Nodes with BW, Storage & Processing Resources.
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Resource Allocation Algorithm, ….
Deployment/Allocation Mechanisms:
ALN Lifecycle
Phases:
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Deployment: initial positioning of resources.
Deployment can also be economically modeled,
although we treat as if done.
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Allocation: main focus here.
 Allocates resources for the demands.
 Changes resource locations:
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Migrate
Clone
Catallaxy Basics
Catallaxy 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
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Adam Smith’s “invisible hand”
Hayek’s “spontaneous order”
Walras’ “non-tâtonnement process”
Catallaxy
Coordination mechanism for systems consisting of
autonomous decentralized devices.
Based on constant negotiation and price signaling
Based on efforts from both agent technology and
economics
Agents 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 properties
Spontaneous order of the
participants

„Unplanned result of
individuals' planful actions“
(Hayek)
Constitutive Elements of
the Catallaxy
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Access to a Market

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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
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Dynamic Co-Evolution
Income expectations and
price relations stabilize
development
Problems
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Tragedy of commons
Free riding
Catnet Properties
Agent-based solution is always inferior to
analytical optimization
Information
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The more information is available, the more accurate
are the choices
The more agents, the more information exists
Computation
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Computation is fully parallel (no central bottleneck)
Solution always exists in the system (no non-allocated
resource)
Agents State
Agents genotype:
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Acquisitiveness
Satisfaction
Price Step
Price Next
Weight Memory
Reputation
For each service:
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Price Distribution
For each negotiation:
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Negotiation History
Parameters to measure
Social Welfare (SWF):
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Sum of all utilities over all participants, in a given
timespan
 Clients subjectively value SC access
 Prices change due to “supply and demand”
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Individual utility = transaction price – market value
Also: Response Time (REST), Resource allocation
efficiency (RAE), Communication cost (CC), ClientResource 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
Fixed networks
Mobile, ad-hoc,
overloaded networks
Changing
Stable
node dynamics
high
P2P
In an
“abstract”
simulator
ALN
medium
CDN
GRID
low
medium
CDN
A few,
powerful
high
node density
P2P
GRID
A lot,
modest
Javasim
The Catnet simulator is build over JavaSim, JavaSim is a network
simulator based in autonomous components.
•
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.
Components
On top of the physical nodes, a number of different
software agents are created, which form the
application layer network:
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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
IP UDP
R
Port 101
C
Port 102
- Running as programs with a socket on a computer
SC
Port 103
- Configuration made at startup script
- Independent on each other at javasim level
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:
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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
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SWF and RAE are dependent
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SWF and CC are dependent
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Every transaction adds to SWF
More transactions add to RAE
Higher CC lowers SWF
SWF and REST are dependent
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Higher REST means more transactions
More transactions add to RAE and SWF
SWF captures all costs and revenues
Dependencies are an emergent feature of the system
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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.
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“Better” is a combination of factors (SWF)
Promising:
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Large scale
Dynamic
Saturation
Future
Future research work:
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Agent technology layer
Application-specific layer
 Both are linked in a feedback loop.
Also:
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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/