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: "peak transmission rate resilient crosslayer broadcast for body area networks"
  Abstract: Wireless Body Area Networks (WBAN) open an interdisciplinary area within Wireless Sensor Networks (WSN) research, with a tremendous impact in healthcare area where sensors are used to monitor, collect and transmit biological parameters of the human body. We propose the rst network-MAC cross-layer broadcast protocol in WBAN. Our protocol, evaluated in the OMNET++ simulator enriched with realistic human body mobility models and channel models issued from the recent research on biomedical and health informatics, outperforms existing at broadcast strategies in terms of percentage of covered nodes, energy consumption and correct reception of causally-ordered packets (i.e. packets are received in the same order as they were sent by the sink). Furthermore, we investigate the resilience of both existing at broadcast strategies and our new protocol face to various transmission rates and human body mobility. Existing at broadcast strategies without exception start to have a drastic drop of performances for transmission rates above 11Kb/s while our cross-layer protocol performances maintains its good performances for transmission rates up to 190Kb/s.

Connected through hyperedge HE-1 (induced by source paper "wireless broadcast with short labelling"):
  with members:
    - "markovian model for broadcast in wireless body area networks"
    - "ban gzkp optimal zero knowledge proof based scheme for wireless body area networks"
    - "finding the size of a radio network with short labels"
    - "total order reliable convergecast in wban"
    - "time vs information tradeoffs for leader election in anonymous trees"
    - "ubiquitous healthcare in wireless body area networks a survey"

Connected through hyperedge HE-2 (induced by source paper "wireless broadcast with optimal labelling"):
  with members:
    - "ban gzkp optimal zero knowledge proof based scheme for wireless body area networks"
    - "constant length labeling schemes for deterministic radio broadcast"
    - "finding the size of a radio network with short labels"
    - "total order reliable convergecast in wban"
    - "time vs information tradeoffs for leader election in anonymous trees"

Connected through hyperedge HE-3 (induced by source paper "markovian model for broadcast in wireless body area networks"):
  with members:
    - "ban gzkp optimal zero knowledge proof based scheme for wireless body area networks"
    - "broadcast strategies and performance evaluation of ieee 802 15 4 in wireless body area networks wban"
    - "ubiquitous healthcare in wireless body area networks a survey"

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)