Title :
Applying Swarm Intelligence Algorithms for Dynamic Load Balancing to a Cloud Based Call Center
Author :
Sesum-Cavic, Vesna ; Kühn, Eva
Author_Institution :
Inst. of Comput. Languages, Vienna Univ. of Technol., Vienna, Austria
fDate :
Sept. 27 2010-Oct. 1 2010
Abstract :
Load-Balancing is a significant problem in heterogeneous distributed systems. Nowadays we face an extreme growth of computer systems and their complexities requiring advanced intelligent solutions for load-balancing that lead to autonomic self-organizing infrastructures. There is still a need to prove that real use cases can benefit from self-* approaches. We developed a pattern, called SILBA, for such an infrastructure based on decentralized control, intelligent and exchangeable policies for load-balancing, and black-board based communication mechanisms. Different types of algorithms (both intelligent and unintelligent) were plugged into SILBA. In this paper, we present one particular use-case - a Call Center that is operated in a Cloud environment.
Keywords :
Internet; artificial intelligence; blackboard architecture; call centres; decentralised control; resource allocation; SILBA; autonomic self-organizing infrastructure; black-board based communication mechanism; cloud based call center; decentralized control; dynamic load balancing; heterogeneous distributed system; intelligent algorithm; swarm intelligence algorithm; Clouds; Heuristic algorithms; Load management; Middleware; Particle swarm optimization; Routing; Servers; call center; load balancing; self-organization; swarm intelligence;
Conference_Titel :
Self-Adaptive and Self-Organizing Systems (SASO), 2010 4th IEEE International Conference on
Conference_Location :
Budapest
Print_ISBN :
978-1-4244-8537-6
Electronic_ISBN :
978-0-7695-4232-4
DOI :
10.1109/SASO.2010.19