Event-driven load balancing of partially replicated objects through a swarm of mobile agents

Swarms of mobile software agents, imitating the behavior of insects, can solve complex tasks. Such agents individually have simple behavior. However, as a collective unit, constructive behavior emerges, as it does in insect colonies. The problem we address is optimizing the distribution of objects with partial replication over a computer network. We present a new approach, implemented as a prototype, based on swarm intelligence. The system performs dynamic, event-driven, distributed load balancing. Every node of the network is capable of producing new events and introducing them into the network for computation. The architecture is general and can be used as a support for clustering and task allocation applications.

[1]  Kian Hsiang Low,et al.  Task Allocation via Self-Organizing Swarm Coalitions in Distributed Mobile Sensor Network , 2004, AAAI.

[2]  Deborah M. Gordon,et al.  Ants at Work - How an Insect Society Is Organized , 1999 .

[3]  William C. Regli,et al.  Ant inspired server population management in a service based computing environment , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

[4]  David Kotz,et al.  Mobile agents and the future of the internet , 1999, OPSR.

[5]  Vegard Hartmann,et al.  Evolving agent swarms for clustering and sorting , 2005, GECCO '05.

[6]  Leandro Nunes de Castro,et al.  Towards Improving Clustering Ants: An Adaptive Ant Clustering Algorithm , 2005, Informatica.

[7]  Aris M. Ouksel,et al.  Agents and Peer-to-Peer Computing , 2003, Lecture Notes in Computer Science.

[8]  Angelos Bilas,et al.  Dynamic data replication: an approach to providing fault-tolerant shared memory clusters , 2003, The Ninth International Symposium on High-Performance Computer Architecture, 2003. HPCA-9 2003. Proceedings..

[9]  Matthias Jarke,et al.  Performance Modeling of Distributed and Replicated Databases , 2000, IEEE Trans. Knowl. Data Eng..

[10]  George Cybenko,et al.  D'Agents: Applications and performance of a mobile‐agent system , 2002, Softw. Pract. Exp..

[11]  Ichiro Satoh.  Bio-inspired Deployment of Distributed Applications , 2004, PRIMA.

[12]  Roberto Montemanni,et al.  Design patterns from biology for distributed computing , 2006, TAAS.

[13]  Jean-Louis Deneubourg,et al.  The dynamics of collective sorting robot-like ants and ant-like robots , 1991 .

[14]  Marco Dorigo,et al.  Swarm intelligence: from natural to artificial systems , 1999 .

[15]  Gokul Soundararajan,et al.  Online data migration for autonomic provisioning of databases in dynamic content web servers , 2005, CASCON.

[16]  Julia Handl,et al.  Improved Ant-Based Clustering and Sorting , 2002, PPSN.

[17]  D. Gordon.  The organization of work in social insect colonies , 1996, Nature.

[18]  Guy Theraulaz,et al.  Adaptive Task Allocation Inspired by a Model of Division of Labor in Social Insects , 1997, BCEC.

[19]  George Cybenko,et al.  Mobile agents in distributed information retrieval , 1999 .

[20]  A Elamy.  PERSPECTIVES IN AGENT-BASED TECHNOLOGY , 2005 .

[21]  Baldo Faieta,et al.  Diversity and adaptation in populations of clustering ants , 1994 .

[22]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[23]  Ajith Abraham,et al.  Web usage mining using artificial ant colony clustering and linear genetic programming , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..