The proliferation of heterogeneous networks, such as the Internet of Things (IoT), unmanned aerial vehicle (UAV) networks, and edge networks, has increased the complexity of network operation and administration, driving the emergence of digital twin networks (DTNs) that create digital-physical network mappings. While DTNs enable performance analysis through emulation testbeds, current research focuses on network-level systems, neglecting equipment-level emulation of critical components like core switches and routers. To address this issue, we propose vFabric (short for virtual switch), a digital twin emulator for high-capacity core switching equipment. This solution implements virtual switching and network processor (NP) chip models through specialized processes, deployable on single or distributed servers via socket communication. The vFabric emulator can realize the accurate emulation for the core switching equipment with 720 ports and 100 Gbit/s per port on the largest scale. To our knowledge, this represents the first digital twin emulation framework specifically designed for large-capacity core switching equipment in communication networks.
With the rapid development of wireless network technologies and the growing demand for a high quality of service (QoS), the effective management of network resources has attracted a lot of attention. For example, in a practical scenario, when a network shock occurs, a batch of affected flows needs to be rerouted to respond to the network shock to bring the entire network deployment back to the optimal state, and in the process of rerouting a batch of flows, the entire response time needs to be as short as possible. Specifically, we reduce the time consumed for routing by slicing, but the routing success rate after slicing is reduced compared with the unsliced case. In this context, we propose a two-stage dynamic network resource allocation framework that first makes decisions on the slices to which flows are assigned, and coordinates resources among slices to ensure a comparable routing success rate as in the unsliced case, while taking advantage of the time efficiency gains from slicing.
This paper comes up with a SDN Based Vehicle Ad-Hoc On-Demand Routing Protocol (SVAO), which separates the data forwarding layer and network control layer, as in software defined networking (SDN), to enhance data transmission efficiency within vehicle ad-hoc networks (VANETs). The roadside service unit plays the role of local controller and is in charge of selecting vehicles to forward packets within a road segment. All the vehicles state in the road. Correspondingly, a two-level design is used. The global level is distributed and adopts a ranked query scheme to collect vehicle information and determine the road segments along which a message should be forwarded. On the other hand, the local level is in charge of selecting forwarding vehicles in each road segment determined by the global level. We implement two routing algorithms of SVAO, and compare their performance in our simulation. We compare SVAO with popular ad-hoc network routing protocols, including Optimized Link State Routing (OLSR), Dynamic Source Routing (DSR), Destination Sequence Distance Vector (DSDV), and distance-based routing protocol (DB) via simulations. We consider the impact of vehicle density, speed on data transmission rate and average packet delay. The simulation results show that SVAO performs better than the others in large-scale networks or with high vehicle speeds.
