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: "distributed resource allocation for network slicing over licensed and unlicensed bands"
  Abstract: Network slicing is one of the key enabling technologies for 5G due to its ability to customize and “slice” a common resource to support diverse services and verticals. This paper introduces a novel  inter-operator network slicing framework  in which multiple mobile network operators (MNOs) can coordinate and jointly slice their accessible spectrum resources in both licensed and unlicensed bands. For licensed band slicing, we propose an  inter-operator spectrum aggregation method  that allows two or more MNOs to cooperate and share their licensed bands to support a common set of service types. We then consider the sharing of unlicensed bands. Because all MNOs enjoy equal rights to access these bands, we introduce the concept of  right sharing  for MNOs to share and trade their spectrum access rights. We develop a  modified back-of-the-envelope method  for MNOs to evaluate their  Value-of-Rights  when coexisting with other wireless technologies. A  network slicing game  based on the overlapping coalition formation game is formulated to investigate the possible cooperation among MNOs. We prove that our proposed game always has at least one stable slicing structure that maximizes the social welfare. To implement our proposed framework without requiring MNOs to reveal private information to other MNOs, we develop a distributed algorithm called  distributed alternating direction method of multipliers with partially variable splitting . Performance evaluation of our proposed framework is provided using a discrete-event simulator that is driven by real MNO deployment scenarios based on over 400 base station locations deployed by two primary cellular operators in the city of Dublin. Numerical results show that our proposed frameworks can almost double the capacity for all supported services for each MNO in an urban setting.

Connected through hyperedge HE-1 (induced by source paper "distributed resource allocation for network slicing of bandwidth and computational resource"):
  with members:
    - "joint optimization of computation and communication power in multi user massive mimo systems"
    - "network slicing based 5g and future mobile networks mobility resource management and challenges"
    - "computing resource allocation in three tier iot fog networks a joint optimization approach combining stackelberg game and matching"
    - "heterogeneous cellular networks with spatio temporal traffic delay analysis and scheduling"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "5g ultra dense cellular networks"

Connected through hyperedge HE-2 (induced by source paper "multi operator network sharing for massive iot"):
  with members:
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "computing resource allocation in three tier iot fog networks a joint optimization approach combining stackelberg game and matching"
    - "from network sharing to multi tenancy the 5g network slice broker"

Connected through hyperedge HE-3 (induced by source paper "multi tenant cross slice resource orchestration a deep reinforcement learning approach"):
  with members:
    - "low complexity distributed radio access network slicing algorithms and experimental results"
    - "dynamic network slicing for scalable fog computing systems with energy harvesting"
    - "performance optimization in mobile edge computing via deep reinforcement learning"
    - "network slicing for 5g with sdn nfv concepts architectures and challenges"
    - "a survey on mobile edge computing the communication perspective"
    - "near optimal behavior via approximate state abstraction"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "from network sharing to multi tenancy the 5g network slice broker"

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)