Runtime measurements in the cloud: observing, analyzing, and reducing variance
Proceedings of the VLDB Endowment
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume PartI
A three-dimensional abstraction framework to compare multi-agent system models
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume PartI
iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator
Journal of Grid Computing
Developing an Elastic Cloud Computing Application through Multi-Agent Systems
International Journal of Cloud Applications and Computing
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In this paper we propose MAScloud, a framework for optimizing both cost and performance in cloud computing systems. This framework is based on both multi-agent systems (MAS) and simulation, where agents are categorized in two different groups: mng-agents and sim-agents. First type of agents, mng-agents, are in charge of managing the configuration and deployment of different cloud models. Second type, sim-agents, are in charge of generating and launching simulated cloud environments obtained from a specific cloud model. The basic idea is that a set of agents collaborate to obtain the configuration that minimize cost, in cloud computing systems, for the execution of a given application by performing simulations. The simulation of cloud computing systems has been performed using the iCanCloud simulation platform. Finally, we present some performance experiments using the proposed framework that model actual cloud computing systems.