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: "toward demand aware networking a theory for self adjusting networks"
  Abstract: The physical topology is emerging as the next frontier in an ongoing effort to render communication networks more flexible. While first empirical results indicate that these flexibilities can be exploited to reconfigure and optimize the network toward the workload it serves and, e.g., providing the same bandwidth at lower infrastructure cost, only little is known today about the fundamental algorithmic problems underlying the design of reconfigurable networks. This paper initiates the study of the theory of demand-aware, self-adjusting networks. Our main position is that self-adjusting networks should be seen through the lense of self-adjusting datastructures. Accordingly, we present a taxonomy classifying the different algorithmic models of demand-oblivious, fixed demand-aware, and reconfigurable demand-aware networks, introduce a formal model, and identify objectives and evaluation metrics. We also demonstrate, by examples, the inherent advantage of demand-aware networks over state-of-the-art demand-oblivious, fixed networks (such as expanders).

Connected through hyperedge HE-1 (induced by source paper "scheduling for weighted flow and completion times in reconfigurable networks"):
  with members:
    - "demand aware network designs of bounded degree"

Connected through hyperedge HE-2 (induced by source paper "renets toward statically optimal self adjusting networks"):
  with members:
    - "slim fly a cost effective low diameter network topology"
    - "datacenter traffic control understanding techniques and tradeoffs"
    - "demand aware network designs of bounded degree"
    - "online balanced repartitioning"
    - "high throughput data center topology design"
    - "jellyfish networking data centers randomly"
    - "competitive paging algorithms"

Connected through hyperedge HE-3 (induced by source paper "efficient distributed workload re embedding"):
  with members:
    - "datacenter traffic control understanding techniques and tradeoffs"
    - "online balanced repartitioning"
    - "dynamic balanced graph partitioning"
    - "online companion caching"
    - "competitive paging algorithms"

Connected through hyperedge HE-4 (induced by source paper "self adjusting linear networks"):
  with members:
    - "demand aware network designs of bounded degree"
    - "towards communication aware robust topologies"
    - "locally self adjusting skip graphs"
    - "online balanced repartitioning"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"

Connected through hyperedge HE-5 (induced by source paper "demand aware network designs of bounded degree"):
  with members:
    - "locally self adjusting skip graphs"
    - "obst a self adjusting peer to peer overlay based on multiple bsts"
    - "high throughput data center topology design"
    - "fast construction of nets in low dimensional metrics and their applications"
    - "nearly linear time algorithms for graph partitioning graph sparsification and solving linear systems"

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)