Author/Authors :
Cortés-Mendoza, Jorge M. CICESE Research Center - Ensenada, BC, Mexico , Tchernykh, Andrei CICESE Research Center - Ensenada, BC, Mexico , Armenta-Cano, Fermin A. CICESE Research Center - Ensenada, BC, Mexico , Bouvry, Pascal University of Luxembourg - Luxembourg City, Luxembourg , Drozdov, Alexander Yu. Moscow Institute of Physics and Technology, Moscow, Russia , Didelot, Loic MIXvoip S.A., Steinsel, Luxembourg
Abstract :
Voice over Internet Protocol (VoIP) allows communication of voice and/or data over the internet in less expensive and reliable manner than traditional ISDN systems. This solution typically allows flexible interconnection between organization and companies on any domains. Cloud VoIP solutions can offer even cheaper and scalable service when virtualized telephone infrastructure is used in the most efficient way. Scheduling and load balancing algorithms are fundamental parts of this approach. Unfortunately, VoIP scheduling techniques do not take into account uncertainty in dynamic and unpredictable cloud environments. In this paper, we formulate the problem of scheduling of VoIP services in distributed cloud environments and propose a new model for biobjective optimization. We consider the special case of the on-line nonclairvoyant dynamic bin-packing problem and discuss solutions for provider cost and quality of service optimization. We propose twenty call allocation strategies and evaluate their performance by comprehensive simulation analysis on real workload considering six months of the MIXvoip company service.
