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

机译:使用微观经济学的生产者-消费者理论的云计算中资源预留的一种新型优化方法

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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.
机译:在云计算的背景下,设计经济定价机制最近引起了很多关注。我们认为微观经济学理论是对云网络中的资源预留操作进行建模的理想人选。微观经济学的生产者-消费者理论保证了顾客社会福利的最大化,前提是要满足有关顾客和生产者的特殊考虑。与现实世界中的云数据中心一样,与每个用户关联的工作负载被馈送到系统中,然后将该用户绑定到虚拟机(VM)。在这项研究中,我们提出了一种受微观经济启发的云计算资源预留方案。设计的机制包括两个步骤:第一步,我们寻求找到有关VM带宽的Pareto有效预留集;第二步,我们的目标是将VM的预留带宽速率置于物理主机上。在我们的建模中,虚拟机和云网络分别被视为市场的消费者和生产者。同样,所请求服务的带宽被视为商品。与微观经济学中的情况一样,我们证明了用户效用的汇总(微观经济学术语中的用户社会福利)可以达到全球最大水平,即帕累托效率。在机制的第一步中找到最佳的预留带宽速率集之后,在第二步中,该机制将寻求在物理主机上找到虚拟机的最佳位置。放置操作以使数据中心的总功耗最小的方式执行。由于VM放置问题已被证明是NP难题,因此我们使用元启发式布谷鸟搜索优化方法来解决优化问题。通过CloudSim框架获得的仿真结果根据重要标准(例如用户的福利,消耗的功率和帕累托最优)建立了所提出方法的鲁棒性。

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