human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "multicast traffic engineering for software defined networks"
  Abstract: Although Software-Defined Networking (SDN) enables flexible network resource allocations for traffic engineering, current literature mostly focuses on unicast communications. Compared to traffic engineering for multiple unicast flows, multicast traffic engineering for multiple trees is very challenging not only because minimizing the bandwidth consumption of a single multicast tree by solving the Steiner tree problem is already NP-Hard, but the Steiner tree problem does not consider the link capacity constraint for multicast flows and node capacity constraint to store the forwarding entries in Group Table of OpenFlow. In this paper, therefore, we first study the hardness results of scalable multicast traffic engineering in SDN. We prove that scalable multicast traffic engineering with only the node capacity constraint is NP-Hard and not approximable within, which is the number of destinations in the largest multicast group. We then prove that scalable multicast traffic engineering with both the node and link capacity constraints is NP-Hard and not approximable within any ratio. To solve the problem, we design an approximation algorithm, named Multi-Tree Routing and State Assignment Algorithm (MTRSA), for the first case and extend it to the general multicast traffic engineering problem. The simulation and implementation results demonstrate that the solutions obtained by the proposed algorithm outperform the shortest-path trees and Steiner trees. Most importantly, MTRSA is computation-efficient and can be deployed in SDN since it can generate the solution with numerous trees in a short time.

Connected through hyperedge HE-1 (induced by source paper "on efficient data transfers across geographically dispersed datacenters"):
  with members:
    - "quickcast fast and efficient inter datacenter transfers using forwarding tree cohorts"
    - "dccast efficient point to multipoint transfers across datacenters"
    - "ddccast meeting point to multipoint transfer deadlines across datacenters using alap scheduling policy"
    - "rcd rapid close to deadline scheduling for datacenter networks"
    - "finishing flows quickly with preemptive scheduling"
    - "jellyfish networking data centers randomly"
    - "an axiomatic theory of fairness in network resource allocation"

Connected through hyperedge HE-2 (induced by source paper "efficient inter datacenter bulk transfers with mixed completion time objectives"):
  with members:
    - "fast and efficient bulk multicasting over dedicated inter datacenter networks"
    - "quickcast fast and efficient inter datacenter transfers using forwarding tree cohorts"
    - "dccast efficient point to multipoint transfers across datacenters"
    - "ddccast meeting point to multipoint transfer deadlines across datacenters using alap scheduling policy"

Connected through hyperedge HE-3 (induced by source paper "quickcast fast and efficient inter datacenter transfers using forwarding tree cohorts"):
  with members:
    - "datacenter traffic control understanding techniques and tradeoffs"
    - "gb pandas throughput and heavy traffic optimality analysis for affinity scheduling"
    - "near data scheduling for data centers with multiple levels of data locality"
    - "dccast efficient point to multipoint transfers across datacenters"
    - "ddccast meeting point to multipoint transfer deadlines across datacenters using alap scheduling policy"

Connected through hyperedge HE-4 (induced by source paper "service overlay forest embedding for software defined cloud networks"):
  with members:
    - "network function virtualization state of the art and research challenges"
    - "online admission control and embedding of service chains"
    - "virtual machine migration planning in software defined networks"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.NI(Networking and Internet Architecture)