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: "properties of an aloha like stability region"
  Abstract: A well-known inner bound on the stability region of the finite-user slotted Aloha protocol is the set of all arrival rates for which there exists some choice of the contention probabilities such that the associated worst case service rate for each user exceeds the user’s arrival rate, denoted    $\Lambda $   . Although testing membership in    $\Lambda $    of a given arrival rate can be posed as a convex program, it is nonetheless of interest to understand the properties of this set. In this paper, we develop new results of this nature, including, 1) an equivalence between membership in    $\Lambda $    and the existence of a positive root of a given polynomial, 2) a method to construct a vector of contention probabilities to stabilize any stabilizable arrival rate vector, 3) the volume of    $\Lambda $   , 4) explicit polyhedral, spherical, and ellipsoid inner and outer bounds on    $\Lambda $   , and 5) characterization of the generalized convexity properties of a natural “excess rate” function associated with    $\Lambda $   , including the convexity of the set of contention probabilities that stabilize a given arrival rate vector.

Connected through hyperedge HE-1 (induced by source paper "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"):
  with members:
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "m2m massive access in lte rach performance evaluation in a smart city scenario"
    - "on the evaluation of lte random access channel overload in a smart city scenario"
    - "analytical modeling of interference aware power control for the uplink of heterogeneous cellular networks"
    - "modeling cellular networks in fading environments with dominant specular components"
    - "tractable stochastic geometry model for iot access in lte networks"
    - "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks"
    - "are we approaching the fundamental limits of wireless network densification"

Connected through hyperedge HE-2 (induced by source paper "on the aloha throughput fairness tradeoff"):
  with members:
    - "an axiomatic theory of fairness in network resource allocation"
    - "asymptotic stability region of slotted aloha"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

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.IT(Information Theory)