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: "proactive resource allocation harnessing the diversity and multicast gains"
  Abstract: This paper introduces the novel concept of proactive resource allocation through which the predictability of user behavior is exploited to balance the wireless traffic over time, and hence, significantly reduce the bandwidth required to achieve a given blocking/outage probability. We start with a simple model in which the smart wireless devices are assumed to predict the arrival of new requests and submit them to the network T time slots in advance. Using tools from large deviation theory, we quantify the resulting prediction diversity gain} to establish that the decay rate of the outage event probabilities increases with the prediction duration T. This model is then generalized to incorporate the effect of the randomness in the prediction look-ahead time T. Remarkably, we also show that, in the cognitive networking scenario, the appropriate use of proactive resource allocation by the primary users improves the diversity gain of the secondary network at no cost in the primary network diversity. We also shed lights on multicasting with predictable demands and show that the proactive multicast networks can achieve a significantly higher diversity gain that scales super-linearly with T. Finally, we conclude by a discussion of the new research questions posed under the umbrella of the proposed proactive (non-causal) wireless networking framework.

Connected through hyperedge HE-1 (induced by source paper "towards jointly optimal placement and delivery to code or not to code in wireless caching networks"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "optimization of heterogeneous coded caching"
    - "structural properties of uncoded placement optimization for coded delivery"
    - "decentralized coded caching attains order optimal memory rate tradeoff"
    - "fundamental limits of caching"
    - "economics of wifi offloading trading delay for cellular capacity"
    - "proactive resource allocation turning predictable behavior into spectral gain"

Connected through hyperedge HE-2 (induced by source paper "on the performance of mobility aware d2d caching networks"):
  with members:
    - "wireless device to device caching networks basic principles and system performance"
    - "towards a marketplace for mobile content dynamic pricing and proactive caching"
    - "fundamental limits of caching in wireless d2d networks"
    - "optimal throughput outage trade off in wireless one hop caching networks"
    - "the throughput outage tradeoff of wireless one hop caching networks"
    - "fundamental limits of caching"

Connected through hyperedge HE-3 (induced by source paper "an online convex optimization approach to dynamic network resource allocation"):
  with members:
    - "introduction to online convex optimization"
    - "online optimization in dynamic environments improved regret rates for strongly convex problems"
    - "a tale of two metrics simultaneous bounds on competitiveness and regret"
    - "online optimization competing with dynamic comparators"
    - "online alternating direction method"

Connected through hyperedge HE-4 (induced by source paper "a survey of anticipatory mobile networking context based classification prediction methodologies and optimization techniques"):
  with members:
    - "context aware scheduling of joint millimeter wave and microwave resources for dual mode base stations"
    - "anticipatory radio resource management for mobile video streaming with linear programming"
    - "kernel based adaptive online reconstruction of coverage maps with side information"
    - "on characterization of feasible interference regions in cognitive radio networks"
    - "spatial wireless channel prediction under location uncertainty"
    - "a control theoretic approach to adaptive video streaming in dense wireless networks"
    - "5g cellular key enabling technologies and research challenges"
    - "context aware small cell networks how social metrics improve wireless resource allocation"

Connected through hyperedge HE-5 (induced by source paper "smarterphones anticipatory download scheduling for wireless video streaming"):
  with members:
    - "probe and adapt rate adaptation for http video streaming at scale"
    - "predicting a user s next cell with supervised learning based on channel states"

Connected through hyperedge HE-6 (induced by source paper "proactive data download and user demand shaping for data networks"):
  with members:
    - "proactive resource allocation turning predictable behavior into spectral gain"

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)