Knowledge-Aware VNE Orchestration in Cloud- and Edge-Mixed Data Center Networks
Emerging applications, such as mobile cloud computing and WSN, bring lots of challenges to current data center networks, and many of them need to construct their own virtual networks (VNs) for the flow-line calculation. Besides, delay-sensitive applications, like IoV and mobile 5G broadband application, require to move the computing resource and some parts of databases closed to customer sites. Thus, the computing resource near application fields, the so-called edge computing, becomes more and more in short supply; meanwhile, the backbone network is under an increasing pressure on the long-haul communication workload. In this paper, we first make a knowledge-aware of VN and design a mapping orchestration based on the QoS requirement features and workload matching. Here, we distinguish the computing requirement from each virtual node in VN and allocate them into edge or cloud DC, respectively. Then, we formulate this resource allocation problem and propose a fast and efficient algorithm. Finally, the numerical results verified the advantages of our algorithm in terms of average computing latency and average transmission latency.
KeywordsOptical data center Edge computing Virtual network embedding 5G Mapping orchestration
The work in this paper is funded by Fundamental Research Funds for Central Universities (Grant No. 3132016318, 3132017078 and 3132018181) and National Natural Science Foundation of China (Grant No. 61371091).
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