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A novel optimized approach for resource reservation in cloud computing using producer–consumer theory of microeconomics

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Abstract

Designing economic pricing mechanisms have recently attracted a great deal of attention in the context of cloud computing. We believe that microeconomics theory is a good candidate to model the resource reservation operations in cloud networks. Producer–consumer theory of microeconomics guarantees the maximization of social welfare of the customers, conditional that the particular consideration concerning customers and producers are met. As is the case in real-world cloud datacenters, the workload associated with each user is fed into the system and then the user is bound to a virtual machine (VM). In this research, we propose a microeconomic-inspired resource reservation scheme for cloud computing. The designed mechanism includes two steps: in the first step, we seek to find a Pareto efficient reservation set concerning bandwidth of VMs, and in the second step, our goal is to place VMs’ reserved bandwidth rates on physical hosts. In our modeling, VMs and the cloud network are considered as consumers and producers of the market, respectively. Also, the bandwidth of requested services is considered as commodity. As is the case in microeconomics, we prove that the aggregation of users’ utilities (users’ social welfare in microeconomics terminology) could reach to global maximum, known as Pareto efficiency. After finding the best set of reserved bandwidth rates in the first step of mechanism, in the second step, the mechanism seeks to find the best placement for VMs on physical hosts. The placement operation is performed in such a way that results in minimization of total consumed power in datacenter. Since the VM placement problem has been proven to be NP-hard, we use a metaheuristic cuckoo search optimization approach to solve the optimization problem. Simulation results, obtained through the CloudSim framework, established the robustness of the proposed method in terms of significant criteria such as users’ welfare, consumed power and Pareto optimality.

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Authors and Affiliations

  1. Faculty of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

    Alireza Mohammadi & Mohammad Hossein Rezvani

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  1. Alireza Mohammadi
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  2. Mohammad Hossein Rezvani
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Correspondence to Mohammad Hossein Rezvani.

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Mohammadi, A., Rezvani, M.H. A novel optimized approach for resource reservation in cloud computing using producer–consumer theory of microeconomics. J Supercomput 75, 7391–7425 (2019). https://doi.org/10.1007/s11227-019-02951-1

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