As a result of the dynamic nature of Virtual Machine allocation in cloud computing, it is not easy to manage system resources or choose the best configuration based solely on human experience. In this work, we used stochastic modelling instead of comprehensive experiments to evaluate the best resource management of the system. In such complex systems, choosing the best decision is a challenge, for this reason we have designed a heuristic algorithm, specifically, dynamic programming as a resource management and programming tool that finds a way that attempts to satisfy the conflicting objectives of high performance and low power consumption. As a scenario for using this algorithm, we addressed the problem of virtual machine allocation, a subset of physical machines is de signated as "reserve", and the reserves are actives when the number of jobs in the system is sufficiently high. The question is how to decide when to activate the reserves. The simulation results demonstrated the benefit of using our framework to identify the policy for consolidation or for a low energy consumption and in order to have a good quality of service in the system.
In intelligent transportation systems, Vehicular Cloud Computing (VCC) is a new technology that can help ensure road security and transport efficiency. The study and evaluation of performances of a VCC is a topic of crucial interest in these environments. This paper presents a model of the computation resource allocation problem in VCC by considering heterogeneity and priority of service requests. We consider service requests from two classes, Primary service requests and Secondary service requests. We involve a Semi-Markov Decision Process (SMDP) to achieve the optimal policy that maximizes the performances of the VCC system taking into account the variability of resources, the income and the system cost. We utilize an iterative approach to achieve the optimal scheme that characterizes the action to be taken under each state. We validate our study by numerical results that show the effectiveness of the proposed SMDP-based scheme.
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