Joint Optimization of Radio and Virtual Machine Resources With Uncertain User Demands in Mobile Cloud Computing
Yun Li, Jie Liu, Bin Cao, Chonggang Wang · IEEE Transactions on Multimedia · 2018
The resource reservation is one of the key techniques to ensure the quality of service (QoS) of a multimedia application. In mobile cloud computing (MCC), the resource reservation and allocation (RRA) in advance can significantly reduce the total provisioning cost of cloud service providers. However, the uncertain features of mobile users' demands for resources make RRA challengeable. In MCC, the QoS of a mobile application, such as voice IP or video, is determined by both of the radio resource (RR) and the cloud virtual machine resource (VMR) allocated to the mobile application, so we should jointly allocate these two types of resources. In this paper, RRA with uncertain demands of mobile users is formulated as a robust optimization model. Logarithmic utility functions are defined to capture the mobile users' satisfaction, which show how to match the allocations between RRs and VMRs according to the resource demands of the mobile applications. Then, a robust joint resource reservation and allocation algorithm in MCC (JRRA-MCC) is proposed to realize the optimal provisioning of RRs and VMRs. Simulation results show that the proposed JRRA-MCC can minimize the total resource provisioning cost of cloud service providers and enhance the resource utilization efficiently.