human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "a survey of anticipatory mobile networking context based classification prediction methodologies and optimization techniques"):
  Abstract: A growing trend for information technology is to not just react to changes, but anticipate them as much as possible. This paradigm made modern solutions, such as recommendation systems, a ubiquitous presence in today's digital transactions. Anticipatory networking extends the idea to communication technologies by studying patterns and periodicity in human behavior and network dynamics to optimize network performance. This survey collects and analyzes recent papers leveraging context information to forecast the evolution of network conditions and, in turn, to improve network performance. In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios. Finally, we consider open challenges and research directions to make anticipatory networking part of next generation networks.

Includes members:
  Member "context aware scheduling of joint millimeter wave and microwave resources for dual mode base stations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimized deployment of millimeter wave networks for in venue regions with stochastic users orientation")
  Member "anticipatory radio resource management for mobile video streaming with linear programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "classifying flows and buffer state for youtube s http adaptive streaming service in mobile networks")
  Member "kernel based adaptive online reconstruction of coverage maps with side information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "boosting vehicle to cloud communication by machine learning enabled context prediction")
  Member "on characterization of feasible interference regions in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio networks")
  Member "spatial wireless channel prediction under location uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep learning and gaussian process based band assignment in dual band systems")
  Member "a control theoretic approach to adaptive video streaming in dense wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "understanding video streaming algorithms in the wild")
  Member "5g cellular key enabling technologies and research challenges":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distributed artificial intelligence solution for d2d communication in 5g networks")
  Member "context aware small cell networks how social metrics improve wireless resource allocation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "network utility maximization based on incentive mechanism for truthful reporting of local information")

Question: Please tell me which class the source paper 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)