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: "handover between macrocell and femtocell for umts based networks"
  Abstract: The femtocell networks that use home base station and existing xDSL or other cable line as backhaul connectivity can fulfill the upcoming demand of high data rate for wireless communication system as well as can extend the coverage area. Hence the modified handover procedure for existing networks is needed to support the macrocell/femtocell integrated network. Some modifications of existing network and protocol architecture for the integration of femtocell networks with the existing UMTS based macrocell networks are essential. These modifications change the signal flow for handover procedures due to different 2-tier cell (macrocell and femtocell) environment. The measurement of signal-to-interference ratio parameter should be considered for handover between macrocell and femtocell. A frequent and unnecessary handover is another problem for hierarchical network environment that must be optimized to improve the performance of macrocell/femtocell integrated network. #R##N#In this paper, firstly we propose the concentrator based and without concentrator based femtocell network architecture. Then we present the signal flow with appropriate parameters for the handover between 3GPP UMTS based macrocell and femtocell networks. A scheme for unnecessary handoff minimization is also presented in this paper. We simulate the proposed handover optimization scheme to validate the performance.

Connected through hyperedge HE-1 (induced by source paper "design and analysis of optimal threshold offloading oto algorithm for lte femtocell macrocell networks"):
  with members:
    - "femtocell networks a survey"

Connected through hyperedge HE-2 (induced by source paper "adaptive resource management for multimedia applications in femtocellular and macrocellular networks"):
  with members:
    - "call admission control based on adaptive bandwidth allocation for wireless networks"
    - "cost effective frequency planning for capacity enhancement of femtocellular networks"
    - "network evolution and qos provisioning for integrated femtocell macrocell networks"
    - "self optimized coverage coordination in femtocell networks"
    - "interference mitigation using dynamic frequency re use for dense femtocell network architectures"
    - "femtocell networks a survey"

Connected through hyperedge HE-3 (induced by source paper "handover management in high dense femtocellular networks"):
  with members:
    - "cost effective frequency planning for capacity enhancement of femtocellular networks"
    - "network evolution and qos provisioning for integrated femtocell macrocell networks"
    - "self optimized coverage coordination in femtocell networks"
    - "femtocell networks a survey"

Connected through hyperedge HE-4 (induced by source paper "network evolution and qos provisioning for integrated femtocell macrocell networks"):
  with members:
    - "dynamic sla negotiation using bandwidth broker for femtocell networks"
    - "interference mitigation using dynamic frequency re use for dense femtocell network architectures"
    - "interference mitigation using uplink power control for two tier femtocell networks"
    - "femtocell networks a survey"

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)