human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "evaluating and comparing probability of path loss in dsdv olsr and dymo at 802 11 and 802 11p"):
  Abstract: In this paper, we present path loss model for VANETs and simulate three routing protocols; Destination Sequenced Distance Vector (DSDV), Optimized Link State Routing (OLSR) and Dynamic MANET On-demand (DYMO) to evaluate and compare their performance using NS-2. The main contribution of this work is enhancement of existing techniques to achieve high efficiency of the underlying networks. After extensive simulations in NS-2, we conclude that DSDV best performs with 802.11p while DYMO gives outstanding performance with 802.11. Index Terms: MANETs, VANETs, DSDV, FSR, OLSR, Routing, throughput, E2ED, NRL.

Includes members:
  Member "identifying design requirements for wireless routing link metrics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distance aware relaying energy efficient dare to monitor patients in multi hop body area sensor networks")
  Member "interference and bandwidth adjusted etx in wireless multi hop networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "performance study of ieee802 11e qos in edcf contention based static and dynamic scenarios":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "modeling and simulating network connectivity in routing protocols for manets and vanets")
  Member "performance study of etx based wireless routing metrics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")

Question: Please tell me which class the source paper 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)