An Adaptive Control Strategy for Resource Allocation of Service-based Systems in Cloud Environment

Service-based systems (SBS) resource allocation in cloud computing environment is important to guarantee Quality of Service (QoS) to satisfy requirements of service requests as well as reduce operating costs. In this paper, a control strategy is presented to allocate the system resources of cloud provider to the servers using PID self-tuning adaptive control dynamically. Meanwhile, an adaptive mechanism using Radial Basis Function (RBF) neural network is devised to adjust parameters of PID controller adaptively in run time. Experimental results show that the approach enables to satisfy the requirements of services-requests with less adjustment of resource allocation, and has better adaptive ability and stability compared to conventional PID control.