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 "explicit back off rates for achieving target throughputs in csma ca networks"):
  Abstract: Carrier-sense multiple access/collision avoidance networks have often been analyzed using a stylized model that is fully characterized by a vector of back-off rates and a conflict graph. Furthermore, for any achievable throughput vector    $\vec \theta $   , the existence of a unique vector    $\vec \nu (\vec \theta )$    of back-off rates that achieves this throughput vector was proven. Although this unique vector can in principle be computed iteratively, the required time complexity grows exponentially in the network size, making this only feasible for small networks. In this paper, we present an explicit formula for the unique vector of back-off rates    $\vec \nu (\vec \theta )$    needed to achieve any achievable throughput vector    $\vec \theta $    provided that the network has a  chordal  conflict graph. This class of networks contains a number of special cases of interest such as (inhomogeneous) line networks and networks with an acyclic conflict graph. Moreover, these back-off rates are such that the back-off rate of a node only depends on its own target throughput and the target throughput of its neighbors and can be determined in a  distributed  manner. We further indicate that back-off rates of this form cannot be obtained in general for networks with non-chordal conflict graphs. For general conflict graphs, we nevertheless show how to adapt the back-off rates when a node is added to the network when its interfering nodes form a clique in the conflict graph. Finally, we introduce a distributed chordal approximation algorithm for general conflict graphs, which is shown (using numerical examples) to be more accurate than the Bethe approximation.

Includes members:
  Member "csma using the bethe approximation scheduling and utility maximization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient csma using regional free energy approximations")
  Member "queue based random access algorithms fluid limits and stability issues":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hybrid scheduling in heterogeneous half and full duplex wireless networks")
  Member "approaching throughput optimality in distributed csma scheduling algorithms with collisions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "throughput optimal decentralized scheduling with single bit state feedback for a class of queueing systems")
  Member "throughput optimal random access with order optimal delay":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "efficient csma using regional free energy approximations")
  Member "analysis of frequency agile csma wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "applications of belief propagation in csma wireless networks")
  Member "performance of csma in multi channel wireless networks":
    also connected through other hyperedges:
      (none)
  Member "q csma queue length based csma ca algorithms for achieving maximum throughput and low delay in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the power of randomization for scheduling real time traffic in wireless 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)