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: "optimal context aware resource allocation in cellular networks"
  Abstract: We define and propose a resource allocation architecture for cellular networks. The architecture combines content-aware, time-aware and location-aware resource allocation for next generation broadband wireless systems. The architecture ensures content-aware resource allocation by prioritizing real-time applications users over delay-tolerant applications users when allocating resources. It enables time-aware resource allocation via traffic-dependent pricing that varies during different hours of day (e.g. peak and off-peak traffic hours). Additionally, location-aware resource allocation is integrable in this architecture by including carrier aggregation of various frequency bands. The context-aware resource allocation is an optimal and flexible architecture that can be easily implemented in practical cellular networks. We highlight the advantages of the proposed network structure with a discussion on the research directions for resource allocation architecture. We also provide experimental results to illustrate a general proof of concept for this new architecture.

Connected through hyperedge HE-1 (induced by source paper "optimal resource allocation for cellular networks with matlab instructions"):
  with members:
    - "position estimation of robotic mobile nodes in wireless testbed using geni"
    - "a delay optimal packet scheduler for m2m uplink"
    - "network mimo with partial cooperation between radar and cellular systems"
    - "resource allocation in cellular systems for applications with random parameters"
    - "optimal downlink power allocation in cellular networks"
    - "an efficient multi carrier resource allocation with user discrimination framework for 5g wireless systems"
    - "application aware resource block and power allocation for lte"
    - "implementing an optimal rate allocation tuned to the user quality of experience"

Connected through hyperedge HE-2 (induced by source paper "resource allocation in cellular systems for applications with random parameters"):
  with members:
    - "an optimal resource allocation with joint carrier aggregation in 4g lte"
    - "a utility proportional fairness radio resource block allocation in cellular networks"
    - "multi application resource allocation with users discrimination in cellular networks"
    - "rate adaptation and admission control for video transmission with subjective quality constraints"

Connected through hyperedge HE-3 (induced by source paper "a qos based power allocation for cellular users with different modulations"):
  with members:
    - "optimal downlink power allocation in cellular networks"
    - "an efficient multi carrier resource allocation with user discrimination framework for 5g wireless systems"
    - "multi application resource allocation with users discrimination in cellular networks"

Connected through hyperedge HE-4 (induced by source paper "optimal power allocation for lte users with different modulations"):
  with members:
    - "optimal downlink power allocation in cellular networks"
    - "an efficient multi carrier resource allocation with user discrimination framework for 5g wireless systems"
    - "multi application resource allocation with users discrimination in cellular networks"

Connected through hyperedge HE-5 (induced by source paper "optimal radio resource allocation for hybrid traffic in cellular networks centralized and distributed architecture"):
  with members:
    - "optimal downlink power allocation in cellular networks"
    - "an optimal application aware resource block scheduling in lte"
    - "multi application resource allocation with users discrimination in cellular networks"
    - "implementing an optimal rate allocation tuned to the user 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.NI(Networking and Internet Architecture)