Performance of data streaming applications is co-determined by both networking and computing resources, and therefore they should be co-scheduled and co-allocated in an integrated and coordinated way. Dynamic control of resource scheduling and allocation is required, because unilateral redundancy in either networking or computing resources may result in the overprovision of it and the other may become a bottleneck. To avoid resource shortage as well as overprovision, in this paper, a virtualized platform is utilized to implement data streaming and processing. In this platform, fuzzy logic controllers are designed to allocate CPU resources; iterative bandwidth allocation is applied and is processing- and storage-aware to guarantee on-demand data provisioning. Experimental results show that our approach leads to higher application performance as well as higher resource utilization, compared with other resource scheduling and allocation methods. © 2012 IEEE.