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 "on the performance of mobility aware d2d caching networks"):
  Abstract: The increase in demand for spectrum-based services forms a bottleneck in wireless networks. Device-to-Device (D2D) caching networks tackle this problem by exploiting user's behavior predictability and the possibility of sharing data between them to alleviate the network congestion. However, capturing mobility statistics allows Service Providers (SPs) to enhance their caching strategies. In this work, we introduce a mobility-aware D2D caching network where SP harnesses user demand and mobility statistics to minimize the incurred service cost through an optimal caching policy. We investigate two caching schemes: centralized and decentralized caching schemes. In the centralized caching scheme, SP makes the caching decision towards its cost minimization to increase its profit. However, the complexity of optimal caching policy grows exponentially with the number of users. Therefore, we discuss a greedy caching algorithm which has a polynomial order complexity. We also use this greedy algorithm to establish upper and lower bounds on the proactive service gain achieved by the optimal caching policy. In the decentralized caching scheme, users take over and make their caching decisions, in a distributed fashion affected by the SP pricing policy, towards their payment minimization. We formulated the tension between the SP and users as a Stackelberg game. The Best response analysis was used to identify a sub-game perfect Nash equilibrium (SPNE) between users. The optimal solution of proposed model was found to depend on the SP reward preference, which affects the assigned memory in users' devices. We found some regimes for the reward value where the SPNE was non-unique. A fair allocation caching policy was adopted to choose one of these SPNEs. To understand the impact of user behavior, we investigated some special cases to explore how user's mobility statistics affect their caching decision.

Includes members:
  Member "wireless device to device caching networks basic principles and system performance":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint optimization of file placement and delivery in cache assisted wireless networks with limited lifetime and cache space")
  Member "towards a marketplace for mobile content dynamic pricing and proactive caching":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a stackelberg game for incentive proactive caching mechanisms in wireless networks")
  Member "fundamental limits of caching in wireless d2d networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "optimal throughput outage trade off in wireless one hop caching networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exploiting mobility in cache assisted d2d networks performance analysis and optimization")
  Member "the throughput outage tradeoff of wireless one hop caching networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mobile communications computing and caching resources optimization for coded caching with device computing")
  Member "fundamental limits of caching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "proactive resource allocation harnessing the diversity and multicast gains":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "towards jointly optimal placement and delivery to code or not to code in wireless caching networks")

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)