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: "joint computation and communication cooperation for energy efficient mobile edge computing"
  Abstract: This paper proposes a novel user cooperation approach in both computation and communication for mobile edge computing (MEC) systems to improve the energy efficiency for latency-constrained computation. We consider a basic three-node MEC system consisting of a user node, a helper node, and an access point (AP) node attached with an MEC server, in which the user has latency-constrained and computation-intensive tasks to be executed. We consider two different computation offloading models, namely the partial and binary offloading, respectively. Under this setup, we focus on a particular finite time block and develop an efficient four-slot transmission protocol to enable the joint computation and communication cooperation. Besides the local task computing over the whole block, the user can offload some computation tasks to the helper in the first slot, and the helper cooperatively computes these tasks in the remaining time; while in the second and third slots, the helper works as a cooperative relay to help the user offload some other tasks to the AP for remote execution in the fourth slot. For both cases with partial and binary offloading, we jointly optimize the computation and communication resources allocation at both the user and the helper (i.e., the time and transmit power allocations for offloading, and the CPU frequencies for computing), so as to minimize their total energy consumption while satisfying the user's computation latency constraint. Although the two problems are non-convex in general, we propose efficient algorithms to solve them optimally. Numerical results show that the proposed joint computation and communication cooperation approach significantly improves the computation capacity and energy efficiency at the user and helper nodes, as compared to other benchmark schemes without such a joint design.

Connected through hyperedge HE-1 (induced by source paper "energy efficient federated edge learning with joint communication and computation design"):
  with members:
    - "energy efficient radio resource allocation for federated edge learning"
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "energy efficient federated learning over wireless communication networks"
    - "joint communication and computation optimization for wireless powered mobile edge computing with d2d offloading"
    - "an overview of data importance aware radio resource management for edge machine learning"
    - "in edge ai intelligentizing mobile edge computing caching and communication by federated learning"
    - "robust and communication efficient federated learning from non iid data"
    - "edge ai on demand accelerating deep neural network inference via edge computing"

Connected through hyperedge HE-2 (induced by source paper "joint optimization of signal design and resource allocation in wireless d2d edge computing"):
  with members:
    - "joint task assignment and resource allocation for d2d enabled mobile edge computing"
    - "decentralized computation offloading for multi user mobile edge computing a deep reinforcement learning approach"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "multiuser resource allocation for mobile edge computation offloading"
    - "joint optimization of radio and computational resources for multicell mobile edge computing"
    - "the interplay between massive mimo and underlaid d2d networking"
    - "on feasibility of interference alignment in mimo interference networks"
    - "on feasibility of interference alignment in mimo interference networks"

Connected through hyperedge HE-3 (induced by source paper "optimal energy allocation and task offloading policy for wireless powered mobile edge computing systems"):
  with members:
    - "joint communication and computation optimization for wireless powered mobile edge computing with d2d offloading"
    - "optimal resource allocation for wireless powered mobile edge computing with dynamic task arrivals"
    - "fundamentals of wireless information and power transfer from rf energy harvester models to signal and system designs"
    - "multiuser computation offloading and downloading for edge computing with virtualization"
    - "deep reinforcement learning for online offloading in wireless powered mobile edge computing networks"
    - "online learning for offloading and autoscaling in energy harvesting mobile edge computing"
    - "a survey on mobile edge computing the communication perspective"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"

Connected through hyperedge HE-4 (induced by source paper "energy efficient resource allocation for secure noma enabled mobile edge computing networks"):
  with members:
    - "securing downlink massive mimo noma networks with artificial noise"
    - "joint power and time allocation for noma mec offloading"
    - "improving anti eavesdropping ability without eavesdropper s csi a practical secure transmission design perspective"
    - "exploiting physical layer security for multiuser multicarrier computation offloading"
    - "edge computing aware noma for 5g networks"
    - "impact of non orthogonal multiple access on the offloading of mobile edge computing"
    - "robust and secure resource allocation for full duplex miso multicarrier noma systems"
    - "a survey on mobile edge computing the communication perspective"

Connected through hyperedge HE-5 (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"
    - "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"
    - "exploiting massive d2d collaboration for energy efficient mobile edge computing"
    - "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-6 (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"
    - "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"
    - "exploiting massive d2d collaboration for energy efficient mobile edge computing"
    - "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-7 (induced by source paper "collaborative computation offloading in wireless powered mobile edge computing systems"):
  with members:
    - "wireless powered user cooperative computation in mobile edge computing systems"
    - "deep reinforcement learning for online computation offloading in wireless powered mobile edge computing networks"
    - "joint tx power allocation and rx power splitting for swipt system with multiple nonlinear energy harvesting circuits"
    - "multiuser computation offloading and downloading for edge computing with virtualization"
    - "online learning for offloading and autoscaling in energy harvesting mobile edge computing"
    - "price based distributed offloading for mobile edge computing with computation capacity constraints"
    - "a survey on mobile edge computing the communication perspective"
    - "multi antenna enabled cluster based cooperation in wireless powered communication networks"

Connected through hyperedge HE-8 (induced by source paper "optimal resource allocation for wireless powered mobile edge computing with dynamic task arrivals"):
  with members:
    - "fundamentals of wireless information and power transfer from rf energy harvester models to signal and system designs"
    - "online learning for offloading and autoscaling in energy harvesting mobile edge computing"
    - "a survey on mobile edge computing the communication perspective"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "communications and signals design for wireless power transmission"
    - "a general utility optimization framework for energy harvesting based wireless communications"

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)