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: "computation peer offloading for energy constrained mobile edge computing in small cell networks"
  Abstract: The (ultra-)dense deployment of small-cell base stations (SBSs) endowed with cloud-like computing functionalities paves the way for pervasive mobile edge computing (MEC), enabling ultra-low latency and location-awareness for a variety of emerging mobile applications and the Internet of Things. To handle spatially uneven computation workloads in the network, cooperation among SBSs via workload peer offloading is essential to avoid large computation latency at overloaded SBSs and provide high quality of service to end users. However, performing effective peer offloading faces many unique challenges in small cell networks due to limited energy resources committed by self-interested SBS owners, uncertainties in the system dynamics and co-provisioning of radio access and computing services. This paper develops a novel online SBS peer offloading framework, called OPEN, by leveraging the Lyapunov technique, in order to maximize the long-term system performance while keeping the energy consumption of SBSs below individual long-term constraints. OPEN works online without requiring information about future system dynamics, yet provides provably near-optimal performance compared to the oracle solution that has the complete future information. In addition, this paper formulates a novel peer offloading game among SBSs, analyzes its equilibrium and efficiency loss in terms of the price of anarchy in order to thoroughly understand SBSs' strategic behaviors, thereby enabling decentralized and autonomous peer offloading decision making. Extensive simulations are carried out and show that peer offloading among SBSs dramatically improves the edge computing performance.

Connected through hyperedge HE-1 (induced by source paper "cooperative service caching and workload scheduling in mobile edge computing"):
  with members:
    - "joint service caching and task offloading for mobile edge computing in dense networks"
    - "dynamic service placement for mobile micro clouds with predicted future costs"

Connected through hyperedge HE-2 (induced by source paper "budget constrained edge service provisioning with demand estimation via bandit learning"):
  with members:
    - "joint service caching and task offloading for mobile edge computing in dense networks"
    - "spatio temporal edge service placement a bandit learning approach"
    - "a survey on mobile edge computing the communication perspective"
    - "socially trusted collaborative edge computing in ultra dense networks"
    - "context aware proactive content caching with service differentiation in wireless networks"
    - "adaptive ensemble learning with confidence bounds"
    - "distributed online learning via cooperative contextual bandits"
    - "a contextual bandit approach to personalized news article recommendation"

Connected through hyperedge HE-3 (induced by source paper "when social sensing meets edge computing vision and challenges"):
  with members:
    - "the age of social sensing"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "what will 5g be"

Connected through hyperedge HE-4 (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"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "online placement of multi component applications in edge computing environments"
    - "joint computation and communication cooperation for mobile edge computing"

Connected through hyperedge HE-5 (induced by source paper "aact application aware cooperative time allocation for internet of things"):
  with members:
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "incentivizing sharing in realtime d2d streaming networks a mean field game perspective"
    - "energy aware cooperative computation in mobile devices"

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.GT(Computer Science and Game Theory)