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: "economics of wifi offloading trading delay for cellular capacity"
  Abstract: Cellular networks are facing severe traffic overloads due to the proliferation of smart handheld devices and traffic-hungry applications. A cost-effective and practical solution is to offload cellular data through WiFi. Recent theoretical and experimental studies show that a scheme, referred to as delayed WiFi offloading, can significantly save the cellular capacity by delaying users' data and exploiting mobility and thus increasing chance of meeting WiFi APs (Access Points). Despite a huge potential of WiFi offloading in alleviating mobile data explosion, its success largely depends on the economic incentives provided to users and operators to deploy and use delayed offloading. In this paper, we study how much economic benefits can be generated due to delayed WiFi offloading, by modeling a market based on a two-stage sequential game between a monopoly provider and users. We also provide extensive numerical results computed using a set of parameters from the real traces and Cisco's projection of traffic statistics in year 2015. In both analytical and numerical results, we model a variety of practical scenarios and control knobs in terms of traffic demand and willingness to pay of users, spatio-temporal dependence of pricing and traffic, and diverse pricing and delay tolerance. We demonstrate that delayed WiFi offloading has considerable economic benefits, where the increase ranges from 21% to 152% in the provider's revenue, and from 73% to 319% in the users' surplus, compared to on-the-spot WiFi offloading.

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"
    - "proactive resource allocation harnessing the diversity and multicast gains"
    - "proactive resource allocation turning predictable behavior into spectral gain"

Connected through hyperedge HE-2 (induced by source paper "device to device load balancing for cellular networks"):
  with members:
    - "scalable spectrum allocation and user association in networks with many small cells"
    - "licensed and unlicensed spectrum allocation in heterogeneous networks"
    - "traffic driven spectrum allocation in heterogeneous networks"
    - "an overview of load balancing in hetnets old myths and open problems"
    - "user association for load balancing in heterogeneous cellular networks"

Connected through hyperedge HE-3 (induced by source paper "amuse empowering users for cost aware offloading with throughput delay tradeoffs"):
  with members:
    - "performance and energy efficiency of mobile data offloading with mobility prediction and prefetching"
    - "a survey of smart data pricing past proposals current plans and future trends"
    - "femtocell networks a survey"

Connected through hyperedge HE-4 (induced by source paper "beyond the ultra dense barrier paradigm shifts on the road beyond 1000x wireless capacity"):
  with members:
    - "asymptotic behavior of ultra dense cellular networks and its economic impact"

Connected through hyperedge HE-5 (induced by source paper "pricing mobile data offloading a distributed market framework"):
  with members:
    - "offloading in heterogeneous networks modeling analysis and design insights"

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.NI(Networking and Internet Architecture)