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: "on the reliability of lte random access performance bounds for machine to machine burst resolution time"
  Abstract: Random Access Channel (RACH) has been identified as one of the major bottlenecks for accommodating massive number of machine-to-machine (M2M) users in LTE networks, especially for the case of burst arrival of connection requests. As a consequence, the burst resolution problem has sparked a large number of works in the area, analyzing and optimizing the average performance of RACH. However, the understanding of what are the probabilistic performance limits of RACH is still missing. To address this limitation, in the paper, we investigate the reliability of RACH with access class barring (ACB). We model RACH as a queuing system, and apply stochastic network calculus to derive probabilistic performance bounds for burst resolution time, i.e., the worst case time it takes to connect a burst of M2M devices to the base station. We illustrate the accuracy of the proposed methodology and its potential applications in performance assessment and system dimensioning.

Connected through hyperedge HE-1 (induced by source paper "admission control based traffic agnostic delay constrained random access ac dc ra for m2m communication"):
  with members:
    - "nr wide bandwidth operations"
    - "delay analysis of multichannel parallel contention tree algorithms mp cta"
    - "frameless aloha with reliability latency guarantees"
    - "joint estimation and contention resolution protocol for wireless random access"

Connected through hyperedge HE-2 (induced by source paper "dynamic binary countdown for massive iot random access in dense 5g networks"):
  with members:
    - "enabling lte rach collision multiplicity detection via machine learning"
    - "tractable stochastic geometry model for iot access in lte networks"
    - "understanding the iot connectivity landscape a contemporary m2m radio technology roadmap"
    - "random access for machine type communication based on bloom filtering"

Connected through hyperedge HE-3 (induced by source paper "game theoretic optimization for machine type communications under qos guarantee"):
  with members:
    - "effective capacity analysis in ultra dense wireless networks with random interference"
    - "effective capacity of licensed assisted access in unlicensed spectrum for 5g from theory to application"
    - "on the effective capacity of mtc networks in the finite blocklength regime"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"

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)