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 "throughput analysis of csma wireless networks with finite offered load"):
  Abstract: This paper proposes an approximate method, equivalent access intensity (EAI), for the throughput analysis of CSMA wireless networks in which links have finite offered-load and their MAC-layer transmit buffers may be empty from time to time. Different from prior works that mainly considered the saturated network, we take into account in our analysis the impacts of empty transmit buffers on the interactions and dependencies among links in the network that is more common in practice. It is known that the empty transmit buffer incurs extra waiting time for a link to compete for the channel airtime usage, since when it has no packet waiting for transmission, the link will not perform channel competition. The basic idea behind EAI is that this extra waiting time can be mapped to an equivalent "longer" backoff countdown time for the unsaturated link, yielding a lower link access intensity that is defined as the mean packet transmission time divided by the mean backoff countdown time. That is, we can compute the "equivalent access intensity" of an unsaturated link to incorporate the effects of the empty transmit buffer on its behavior of channel competition. Then, prior saturated ideal CSMA network (ICN) model can be adopted for link throughput computation. Specifically, we propose an iterative algorithm, "Compute-and-Compare", to identify which links are unsaturated under current offered-load and protocol settings, compute their "equivalent access intensities" and calculate link throughputs. Simulation shows that our algorithm has high accuracy under various offered-load and protocol settings. We believe the ability to identify unsaturated links and compute links throughputs as established in this paper will serve an important first step toward the design and optimization of general CSMA wireless networks with offered-load control.

Includes members:
  Member "applications of belief propagation in csma wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient csma using regional free energy approximations")
  Member "fast mixing of parallel glauber dynamics and low delay csma scheduling":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "effective wireless scheduling via hypergraph sketches")
  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-3 (induced by source paper "on the power of randomization for scheduling real time traffic in wireless networks")
  Member "effective carrier sensing in csma networks under cumulative interference":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a stackelberg game model for overlay d2d transmission with heterogeneous rate requirements")
  Member "saturation throughput analysis of ieee 802 11 in the presence of non ideal transmission channel and capture effects":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "probabilistic modeling of ieee 802 11 distributed coordination functions")
  Member "back of the envelope computation of throughput distributions in csma wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cell level modeling of ieee 802 11 wlans")

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)