Genetic programming with negative selection for volunteer computing system optimization

Abstract

Volunteer computing systems like BOINC or Comcute are strongly supported by a great number of volunteers who contribute resources of their computers via the Web. So, the high efficiency of such grid system is required, and that is why we have formulated a multi-criterion optimization problem for a volunteer grid system design. In that dilemma, both the cost of the host system and workload of a bottleneck host are minimized. On the other hand, a reliability of this grid structure is maximized. Moreover, genetic programming has been applied to determine the Pareto solutions. Finally, a negative selection procedure to handle constraints has been discussed.

Many-Objective Quantum-Inspired Particle Swarm Optimization Algorithm for Placement of Virtual Machines in Smart Computing Cloud

“…The Benchmark855 was used for this purpose, too. We consider fifteen non-dominated solutions obtained by MQPSO, Non-dominated Sorting Genetic Algorithm II (NSGA-II) [ 37 ], Multi-criteria Genetic Programming (MGP) [ 38 ], Multi-criteria Differential Evolution (MDE) [ 4 ] and Multi-criteria Harmony Search (MHS) [ 39 ].…”

Browser-based Harnessing of Voluntary Computational Power

“…There exist already libraries such as webGC [11] (based on WebRTC) which could be used to implement direct task-to-task communication. Unfortunately, WebRTC is still not fully supported by all browsers 5 .…”

“…Usually, workers request for another task as soon as they complete the previous one [19][67]. More complicated scheduler was considered for Comcute [5],.…”