论文部分内容阅读
Service-oriented future internet architecture(SOFIA) is a clean-slate network architecture. In SOFIA, a service request is mainly processed through service resolution and network resource allocation. To realize the network resource allocation, we reference the idea of network virtualization and propose resource scheduling virtualization. In resource scheduling virtualization, a service request is abstracted as a virtual network(VN) and the network resources are allocated by mapping the VN onto the physical network. Resource scheduling virtualization provides centralized resource scheduling control within an autonomous system(AS) and achieves better controllability compared with the distributed schemes. Besides, resource scheduling virtualization supports multi-site selection as well. Meanwhile, we propose a collection of resource scheduling algorithms based on maximum resource tree(MRT) adapting to different scenarios. According to the simulation results, the proposed algorithms show good performance on the key metrics, such as acceptance ratio, revenue, cost and utilization. Moreover, the simulation results reveal that our algorithm is more efficient than the traditional ones.
Service-oriented future internet architecture (SOFIA) is a clean-slate network architecture. In SOFIA, a service request is mainly processed through service resolution and network resource allocation. We refer the idea of network virtualization and propose resource scheduling virtualization. a resource service virtualization. A scheduling request is abstracted as a virtual network (VN) and the network resources are allocated by mapping the VN onto the physical network. ), and achieves better controllability compared with the distributed schemes. Moreover, we propose a collection of resource-scheduling algorithms based on maximum resource tree (MRT) adapting to different scenarios. According to the the simulation results, the proposed algorithms show g ood performance on the key metrics, such as acceptance ratio, revenue, cost and utilization. Moreover, the simulation results reveal that our algorithm is more efficient than the traditional ones.