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: "exploiting massive d2d collaboration for energy efficient mobile edge computing"
  Abstract: In this article we propose a novel Device-to-Device (D2D) Crowd framework for 5G mobile edge computing, where a massive crowd of devices at the network edge leverage the network-assisted D2D collaboration for computation and communication resource sharing among each other. A key objective of this framework is to achieve energy-efficient collaborative task executions at network-edge for mobile users. Specifically, we first introduce the D2D Crowd system model in details, and then formulate the energy-efficient D2D Crowd task assignment problem by taking into account the necessary constraints. We next propose a graph matching based optimal task assignment policy, and further evaluate its performance through extensive numerical study, which shows a superior performance of more than 50% energy consumption reduction over the case of local task executions. Finally, we also discuss the directions of extending the D2D Crowd framework by taking into variety of application factors.

Connected through hyperedge HE-1 (induced by source paper "edge intelligence paving the last mile of artificial intelligence with edge computing"):
  with members:
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "in edge ai intelligentizing mobile edge computing caching and communication by federated learning"
    - "peer to peer federated learning on graphs"
    - "pcamp performance comparison of machine learning packages on the edges"
    - "client selection for federated learning with heterogeneous resources in mobile edge"
    - "on device federated learning via blockchain and its latency analysis"
    - "federated learning strategies for improving communication efficiency"
    - "communication compression for decentralized training"

Connected through hyperedge HE-2 (induced by source paper "joint communication and computation optimization for wireless powered mobile edge computing with d2d offloading"):
  with members:
    - "joint task assignment and resource allocation for d2d enabled mobile edge computing"
    - "joint computation and communication cooperation for energy efficient mobile edge computing"
    - "wireless powered user cooperative computation in mobile edge computing systems"
    - "throughput maximization for uav enabled wireless powered communication networks"
    - "waveform design for wireless power transfer with limited feedback"
    - "a survey on mobile edge computing the communication perspective"
    - "uav enabled wireless power transfer trajectory design and energy optimization"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"

Connected through hyperedge HE-3 (induced by source paper "joint task assignment and resource allocation for d2d enabled mobile edge computing"):
  with members:
    - "energy efficient mobile edge computation offloading for applications with shared data"
    - "joint computation and communication cooperation for energy efficient mobile edge computing"
    - "exploiting physical layer security for multiuser multicarrier computation offloading"
    - "resource sharing of a computing access point for multi user mobile cloud offloading with delay constraints"
    - "a survey on mobile edge computing the communication perspective"
    - "joint task offloading scheduling and transmit power allocation for mobile edge computing systems"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "mobile edge computing a survey on architecture and computation offloading"

Connected through hyperedge HE-4 (induced by source paper "stochastic control of computation offloading to a helper with a dynamically loaded cpu"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "energy efficient mobile edge computing in dense cellular networks"
    - "wireless networks for mobile edge computing spatial modeling and latency analysis extended version"
    - "exploiting non causal cpu state information for energy efficient mobile cooperative computing"
    - "joint computation and communication cooperation for mobile edge computing"
    - "delay optimal computation task scheduling for mobile edge computing systems"
    - "less is more participation incentives in d2d enhanced mobile edge computing under infectious ddos attacks"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"

Connected through hyperedge HE-5 (induced by source paper "follow me at the edge mobility aware dynamic service placement for mobile edge computing"):
  with members:
    - "edge intelligence on demand deep learning model co inference with device edge synergy"
    - "efficient resource allocation for on demand mobile edge cloud computing"
    - "emm energy aware mobility management for mobile edge computing in ultra dense networks"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "toward hierarchical mobile edge computing an auction based profit maximization approach"
    - "dynamic service placement for mobile micro clouds with predicted future costs"
    - "a non stochastic learning approach to energy efficient mobility management"
    - "dynamic service migration in mobile edge clouds"

Connected through hyperedge HE-6 (induced by source paper "joint computation and communication cooperation for mobile edge computing"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "exploiting non causal cpu state information for energy efficient mobile cooperative computing"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "delay optimal computation task scheduling for mobile edge computing systems"
    - "energy efficient mobile cloud computing powered by wireless energy transfer"
    - "user cooperation in wireless powered communication networks"

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)