Artificial Bee Colony Optimization Technique for Effective Resource Allocation

Abstract

Accelerating the development and deployment of advanced communication technologies and complex databases will require a comprehensive strategy integrating efforts from invention to deployment. The concurrent high-performance computing systems are composed of hundreds of thousands of computational nodes, as well as deep memory hierarchies and complex interconnect topologies. Existing high performance algorithms and tools already require courageous programming and optimization efforts to achieve high efficiency on current supercomputers. On the other hand, these efforts are platform-specific and non-portable. Since most of the existing optimization algorithms and tools are not optimized for modern computer architectures and cannot efficiently exploit massively parallel systems, one aim of this research is to identify and to analyze the general problems and modern trends in this research area. This paper investigates the efficiency of artificial bee colony optimization algorithm for effective resource allocation. Parallel version of the algorithm have been proposed based on the flat parallel programming model with message passing for communication between the computational nodes in the platform and parallel programming model with multithreading for communication between the cores inside the computational node. Parallel communications profiling is made and parallel performance parameters are evaluated on the basis of experimental results.