A Formal Aspect-Oriented Method for Modeling and Analyzing Adaptive Resource Scheduling in Cloud Computing

Cloud computing has attracted much interest recently from both industry and academia. However, the scale and highly dynamic nature of cloud application imposes significant new challenges to resource management, and efficient resource scheduling schemes are highly demanded. In this paper, we propose a systematic method to address the reliability, running time, and failure processing of resource scheduling in cloud computing. A reflection mechanism is used to abstract the resource scheduling process as a metaobject. Petri nets are used to construct the base layer model, meta layer model, metaobject protocol, and other components, thus forming the resource scheduling model. The adaptive resource scheduling strategy is converted into CTL formulas, and the properties are analyzed. Meanwhile, an enforcement algorithm is proposed, which can guarantee the correct behavior of cloud computing while meeting the required reliability within deadline constraints. The operational semantics and related theories of Petri nets help prove its effectiveness and correctness. We have also performed a series of simulations to evaluate our approach. Results show that it can help reveal the structural and behavioral characteristics of cloud computing and improve the efficiency of resource management.