Research on Virtual Device Management in Real-time Environment

摘要

In this paper, we present improved methods of credit scheduling algorithm of Xen. By using gray-box knowledge reasoning technology, we are able to identify the IO task in the internal workload of each virtual machine. By using this information of the internal workload, we proposed a Boosting mechanism based on the selection. Selectively raise the priority of the virtual processor to give priority to the corresponding field of the I/O Tasks improve the response speed, and reduce the response time to achieve real-time purposes. In addition, we propose four complementary mechanisms for the shortcomings of the proposed BOOST scheduling algorithm based on the selection. The four complementary mechanisms are the cancellation BOOST priority mechanism, reducing Credit precise mechanism, setting Rate value mechanisms and UNDER queue mechanisms. These four mechanisms can effectively fill the insufficient of BOOST scheduling algorithm based selection, and improve the stability of the algorithm.