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Cost-Efficient Request Scheduling and Resource Provisioning in Multiclouds for Internet of Things

To satisfy the increasingly complex demands of the Internet of Things (IoT) applications, multiclouds are a promising solution that can provide scalable, various, and abundant resources. However, in multiclouds, each cloud has its specific virtual machine (VM) type and pricing scheme. In addition, the request arrival, network bandwidth, and VM’s price all vary with time and are hardly predicted. In such cases, the request scheduling and resource provisioning (RSRP) for cost efficiency becomes a highly challenging work. In this article, to capture the dynamics in the multiclouds environment, we formulate a stochastic optimization problem where the aim is to minimize the system cost and guarantee the IoT applications’ queueing delay. By applying stochastic optimization theory, the original problem is transformed into a deterministic optimization problem in each slot, and then the deterministic problem is further decomposed into three independent subproblems. An online RSRP algorithm is devised to obtain these subproblems’ optimal solutions. Mathematical analysis shows that RSRP can approach the optimal system cost while bounding the queueing delay, and make an arbitrary tradeoff between system cost and queueing delay as well. Moreover, trace-driven simulation results show the effectiveness of RRSP.