Intelligent Load Clustering

Context

distributed computing, intelligent algorithms, benchmarks, model checking

Task Description

The task is to perform model checking of a load clustering framework, SILCA, in which will further be plugged new intelligent bio-inspired algorithms (like a slime mold algorithm). The overall benchmarking and comparison with the other intelligent and unintelligent algorithms should be done in different test environments and different network topologies.

Requirements

• Java

Student

open topic (please apply using ID = "SILCA")

Supervisor

A.o. Univ.-Prof. Dr. Dipl.-Ing. eva Kühn

Related Projects in the Network

Vesna Sesum-Cavic, Eva Kühn, "Comparing Configurable Parameters of Swarm Intelligence Algorithms for Dynamic Load Balancing," SASOW, pp.42-49, 2010 Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshop, 2010