An intelligent agent-based method for task allocation in competitive cloud environments
In market-based cloud environments, both resource consumers and providers are self-interested; additionally, they can come and leave the environment freely. Therefore, the environment is competitive and uncertain. Because of the competition, participants may cheat in making deals, and this represents that the environment is insecure to resource providers who intend to earn profits through renting their resources to the tasks of resource consumers. Against this, in this paper, intelligent agents are designed to strategically quote for the tasks that they are interested in, on behalf of resource providers. Agents could quote according to the messages it obtained and the information learnt and predicted from the messages, to minimize the influence of insecure factors, such as cheating, competition, and dynamism. The experimental evaluation shows that the proposed method outperforms both a well-known multiresource negotiation-based task allocation method and a max-sum belief propagation-based method.