A complex adaptive system based on squirrels behaviors for distributed resource allocation

Authors:
Sergio Camorlinga;Ken Barker
Affiliations:
Department of Computer Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada;Department of Computer Science, University of Calgary, Calgary, AB T2N 1N4, Canada
Venue:
Web Intelligence and Agent Systems
Year:
2006

Citing 6
Cited 2

An equilibratory market-based approach for distributed resource allocation and its applications to communication network control

Market-based control
Challenger: a multi-agent system for distributed resource allocation

AGENTS '97 Proceedings of the first international conference on Autonomous agents
Dynamic resource allocation by market-based routing in telecommunications networks

IATA '98 Proceedings of the second international workshop on Intelligent agents for telecommunication applications
Anthill: A Framework for the Development of Agent-Based Peer-to-Peer Systems

ICDCS '02 Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02)
Messor: load-balancing through a swarm of autonomous agents

AP2PC'02 Proceedings of the 1st international conference on Agents and peer-to-peer computing
Ant system: optimization by a colony of cooperating agents

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Spatial pattern growth and emergent animat segregation

Web Intelligence and Agent Systems
An experimental analysis of biased parallel greedy approximation for combinatorial auctions

International Journal of Intelligent Information and Database Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper introduces new general-purpose Complex Adaptive System (CAS) algorithms that solve the resource allocation problem in distributed systems. These CAS algorithms are based on squirrel natural behaviors and provide a novel CAS metaphor. The CAS Squirrels system is described together with its associated class architecture. A comprehensive set of experiments is carried to corroborate our hypothesis that CAS Squirrel based algorithms provide a efficient resource allocation on a distributed system. The algorithms are based on squirrel hoarding mechanisms. The scalability and reliability obtained from the experiments are maintained across a wide variety of distributed system characteristics. The research work uses the Peer-to-Peer Distributed File System storage resource allocation problem to validate our hypothesis.