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: "throughput computation in csma wireless networks with collision effects"
  Abstract: It is known that link throughputs of CSMA wireless networks can be computed from a time-reversible Markov chain arising from an ideal CSMA network model (ICN). In particular, this model yields general closed-form equations of link throughputs. However, an idealized and important assumption made in ICN is that the backoff countdown process is in "contiuous-time" and carrier sensing is instantaneous. As a result, there is no collision in ICN. In practical CSMA protocols such as IEEE 802.11, the stations count down in "mini-timeslot" and the process is therefore a "discrete-time" process. In particular, two stations may end their backoff process in the same mini-timeslot and then transmit simultaneously, resulting in a packet collision. This paper is an attempt to study how to compute link throughputs after taking such backoff collision effects into account. We propose a generalized ideal CSMA network model (GICN) to characterize the collision states as well as the interactions and dependency among links in the network. We show that link throughputs and collision probability can be computed from GICN. Simulation results validate GICN's accuracy. Interestingly, we also find that the original ICN model yields fairly accurate results despite the fact that collisions are not modeled.

Connected through hyperedge HE-1 (induced by source paper "applications of belief propagation in csma wireless networks"):
  with members:
    - "message error analysis of loopy belief propagation for the sum product algorithm"
    - "analysis of frequency agile csma wireless networks"
    - "effective carrier sensing in csma networks under cumulative interference"
    - "back of the envelope computation of throughput distributions in csma wireless networks"
    - "sufficient conditions for convergence of the sum product algorithm"

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)