Evaluation and optimization of the mixed redundancy strategy in cloud-based systems

Abstract

Mixed redundancy strategies are generally used in cloud-based systems, with different node switch mechanisms from traditional fault-tolerant strategies. Existing studies often concentrate on optimizing a single strategy in cloud computing environment and ignore the impact of mixed redundancy strategies. Therefore, a model is proposed to evaluate and optimize the reliability and performance of cloud-based degraded systems subject to a mixed active and cold standby redundancy strategy. In this strategy, node switching is triggered by a continual monitoring and detection mechanism when active nodes fail. To evaluate the transient availability and the expected job completion rate of systems with such kind of strategy, a continuous-time Markov chain model is built on the state transition process and a numerical method is used to solve the model. To choose the optimal redundancy for the mixed strategy under system constraints, a greedy search algorithm is proposed after sensitivity analysis. Illustrative examples were presented to explain the process of calculating the transient probability of each system state and in turn, the availability and performance of the whole system. It was shown that the near-optimal redundancy solution could be obtained using the optimization method. The comparison with optimization of the traditional mixed redundancy strategy proved that the system behavior was different using different kinds of mixed strategies and less redundancy was assigned for the new type of mixed strategy under the same system constraint.