# DDS: A Delay-Based Differentiated Service Virtual Network Embedding Algorithm
## 6 Conclusions  
In order to flexibly respond to virtual network requests with differentiated resource requirements and QoS requirements, we propose a virtual network embedding algorithm that distinguishes network types. We first divide virtual network requests into ordinary requests and delay-sensitive requests according to the low latency requirements of virtual networks. Next, we design different embedding strategies for different types of virtual network requests. For ordinary requests, we adopt a heuristic two-stage embedding sub  
Figure 10: Comparison of DDS with PURE-ILP under various VNR arrival ratios.  
algorithm based on greedy strategy and considering resource consumption balance. We use a constrained integer linear programming sub-algorithm to solve delay-sensitive requests.  
We conducted a comprehensive simulation and evaluation of the proposed algorithm. Experimental results showed that our algorithm outperforms the compared algorithm. Our algorithm can accept more virtual network embedding requests, reduce virtual network embedding cost, and maximize the utilization of substrate network resources. In addition, the task of placing service function chain (SFC) in network function virtualization (NFV) [33] can be seen as a virtual network embedding problem with network function constraints. Therefore, the proposed algorithm in this paper can also be applied to other network environments such as NFV.  
In the next research stage, there are still some aspects to be improved. In order to improve the persuasiveness of the algorithm, it is meaningful to evaluate the algorithm in realistic traffic and network scenarios based on a real SDN substrate infrastructure and tenant requests. The network environment is complex and changeable, and the traffic in the network will change dynamically. In a future work, we should also consider resource reallocation [34] in the case of dynamic network traffic. A preliminary idea is to combine the global view of SDN, consider the state of resources allocated before, and reconfigure network elements that do not satisfy resource requirements to maintain network stability. Furthermore, considering the complexity of the actual network, the classification criteria for virtual network requests may not be comprehensive. In the future, it is important to consider other classification criteria for the actual network environment and propose personalized embedding algorithm research for differentiated networks, such as the cost demand network, delay demand network, bandwidth demand network, etc.  
Conceptualization, J.T., [PERSON] ([PERSON]), and [PERSON] ([PERSON]); methodology, J.T. and X.Z. ([PERSON]); software, J.T.; validation, J.T., [PERSON] ([PERSON]), and [PERSON] ([PERSON]); formal analysis, J.T.; investigation, J.T.; resources, J.T.; data curation, J.T.; writing--original draft preparation, J.T.; writing--review and editing, [PERSON], [PERSON] ([PERSON]), and [PERSON] ([PERSON]); visualization, J.T.; supervision, [PERSON] ([PERSON]) and [PERSON] ([PERSON]); project administration, [PERSON] ([PERSON]); funding acquisition, [PERSON] ([PERSON]) and [PERSON] ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
This research was funded by Strategic Leadership Project of Chinese Academy of Sciences: SEANET Technology Standardization Research System Development (Project No. XDC02070100) and Goal-Oriented Project Independently Deployed by Institute of Acoustics, Chinese Academy of Sciences (Project No. MBDX202114).  
Not applicable.  
We would like to express our gratitude to [PERSON] and [PERSON] for their meaningful support in this work.  
The authors declare no conflict of interest.