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: "multiuser computation offloading and downloading for edge computing with virtualization"
  Abstract: Mobile-edge computing (MEC) is an emerging technology for enhancing the computational capabilities of mobile devices and reducing their energy consumption via offloading complex computation tasks to the nearby servers. Multiuser MEC at servers is widely realized via parallel computing based on virtualization. Due to finite shared I/O resources, interference between virtual machines (VMs), called I/O interference, degrades the computation performance. In this paper, we study the problem of joint radio-and-computation resource allocation (RCRA) in multiuser MEC systems in the presence of I/O interference. Specifically, offloading scheduling algorithms are designed targeting two system performance metrics: sum offloading throughput maximization and sum mobile energy consumption minimization. Their designs are formulated as non-convex mixed-integer programming problems, which account for latency due to offloading, result downloading and parallel computing. A set of low-complexity algorithms are designed based on a decomposition approach and leveraging classic techniques from combinatorial optimization. The resultant algorithms jointly schedule offloading users, control their offloading sizes, and divide time for communication (offloading and downloading) and computation. They are either optimal or can achieve close-to-optimality as shown by simulation. Comprehensive simulation results demonstrate considering of I/O interference can endow on an offloading controller robustness against the performance-degradation factor.

Connected through hyperedge HE-1 (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"
    - "joint computation and communication cooperation for energy efficient mobile edge computing"
    - "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-2 (induced by source paper "collaborative computation offloading in wireless powered mobile edge computing systems"):
  with members:
    - "joint computation and communication cooperation for energy efficient mobile edge computing"
    - "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"
    - "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-3 (induced by source paper "resource awareness in unmanned aerial vehicle assisted mobile edge computing systems"):
  with members:
    - "age of information aware radio resource management in vehicular networks a proactive deep reinforcement learning perspective"
    - "optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning"
    - "multi tenant cross slice resource orchestration a deep reinforcement learning approach"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "a survey on mobile edge computing the communication perspective"
    - "latency and reliability aware task offloading and resource allocation for mobile edge computing"
    - "deep multi user reinforcement learning for distributed dynamic spectrum access"
    - "deep recurrent q learning for partially observable mdps"

Connected through hyperedge HE-4 (induced by source paper "noma aided mobile edge computing via user cooperation"):
  with members:
    - "joint computation and communication cooperation for energy efficient mobile edge computing"
    - "delay minimization for noma mec offloading"
    - "edge computing aware noma for 5g networks"
    - "price based distributed offloading for mobile edge computing with computation capacity constraints"
    - "a survey on mobile edge computing the communication perspective"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "exploiting non causal cpu state information for energy efficient mobile cooperative computing"
    - "mobile edge computing a survey on architecture and computation offloading"

Connected through hyperedge HE-5 (induced by source paper "dynamic spectrum sharing for load balancing in multi cell mobile edge computing"):
  with members:
    - "joint service placement and request routing in multi cell mobile edge computing networks"
    - "mobile edge computing enabled heterogeneous networks"
    - "optimizing user association and spectrum allocation in hetnets a utility perspective"
    - "joint optimization of radio and computational resources for multicell mobile edge computing"
    - "efficient multi user computation offloading for mobile edge cloud computing"
    - "user association for load balancing in heterogeneous cellular networks"

Connected through hyperedge HE-6 (induced by source paper "mobile edge computing enabled heterogeneous networks"):
  with members:
    - "sir coverage analysis in cellular networks with temporal traffic a stochastic geometry approach"
    - "a survey on mobile edge computing the communication perspective"
    - "wireless networks for mobile edge computing spatial modeling and latency analysis extended version"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "latency and reliability aware task offloading and resource allocation for mobile edge computing"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "heterogeneous cellular networks with los and nlos transmissions the role of massive mimo and small cells"
    - "delay optimal computation task scheduling for mobile edge computing systems"

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)