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: "the energy frequency convexity rule modeling and experimental validation on mobile devices"
  Abstract: This paper provides both theoretical and experimental evidence for the existence of an Energy/Frequency Convexity Rule, which relates energy consumption and CPU frequency on mobile devices. We monitored a typical smartphone running a specific computing-intensive kernel of multiple nested loops written in C using a high-resolution power gauge. Data gathered during a week-long acquisition campaign suggest that energy consumed per input element is strongly correlated with CPU frequency, and, more interestingly, the curve exhibits a clear minimum over a 0.2 GHz to 1.6 GHz window. We provide and motivate an analytical model for this behavior, which fits well with the data. Our work should be of clear interest to researchers focusing on energy usage and minimization for mobile devices, and provide new insights for optimization opportunities.

Connected through hyperedge HE-1 (induced by source paper "offloading and resource allocation with general task graph in mobile edge computing a deep reinforcement learning approach"):
  with members:
    - "optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning"
    - "deep reinforcement learning for online computation offloading in wireless powered mobile edge computing networks"
    - "a survey on mobile edge computing the communication perspective"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "asynchronous methods for deep reinforcement learning"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "energy efficient mobile cloud computing powered by wireless energy transfer"

Connected through hyperedge HE-2 (induced by source paper "game theory based joint task offloading and resources allocation algorithm for mobile edge computing"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "joint task offloading scheduling and transmit power allocation for mobile edge computing systems"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "joint computation and communication cooperation for mobile edge computing"
    - "power delay tradeoff in multi user mobile edge computing systems"
    - "decentralized computation offloading game for mobile cloud computing"
    - "cloud offloading for multi radio enabled mobile devices"

Connected through hyperedge HE-3 (induced by source paper "distributed joint offloading decision and resource allocation for multi user mobile edge computing a game theory approach"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "distributed power control in interference channels with qos constraints and rf energy harvesting a game theoretic approach"
    - "decentralized computation offloading game for mobile cloud computing"
    - "cloud offloading for multi radio enabled mobile devices"
    - "efficient multi user computation offloading for mobile edge cloud computing"
    - "power control in two tier femtocell networks"

Connected through hyperedge HE-4 (induced by source paper "on the accuracy and usefulness of analytic energy models for contemporary multicore processors"):
  with members:
    - "an analysis of core and chip level architectural features in four generations of intel server processors"
    - "kerncraft a tool for analytic performance modeling of loop kernels"
    - "quantifying performance bottlenecks of stencil computations using the execution cache memory model"
    - "chip level and multi node analysis of energy optimized lattice boltzmann cfd simulations"
    - "exploring performance and power properties of modern multicore chips via simple machine models"

Connected through hyperedge HE-5 (induced by source paper "a survey on mobile edge computing the communication perspective"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "joint energy minimization and resource allocation in c ran with mobile cloud"
    - "latency optimization for resource allocation in mobile edge computation offloading"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "proactive edge computing in latency constrained fog networks"
    - "computation peer offloading for energy constrained mobile edge computing in small cell networks"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "online placement of multi component applications in edge computing environments"

Connected through hyperedge HE-6 (induced by source paper "stochastic joint radio and computational resource management for multi user mobile edge computing systems"):
  with members:
    - "joint energy minimization and resource allocation in c ran with mobile cloud"
    - "a survey on mobile edge computing the communication perspective"
    - "delay optimal computation task scheduling for mobile edge computing systems"
    - "joint subcarrier and cpu time allocation for mobile edge computing"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "power delay tradeoff in multi user mobile edge computing systems"
    - "decentralized computation offloading game for mobile cloud computing"

Connected through hyperedge HE-7 (induced by source paper "parameter sensitivity analysis of the energy frequency convexity rule for nanometer scale application processors"):
  with members:
    - "modeling the temperature bias of power consumption for nanometer scale cpus in application processors"
    - "beebs open benchmarks for energy measurements on embedded platforms"
    - "exploring performance and power properties of modern multicore chips via simple machine models"
    - "some observations on optimal frequency selection in dvfs based energy consumption minimization"

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.OH(Other Computer Science)