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: "modeling spatial and temporal dependencies of user mobility in wireless mobile networks"
  Abstract: Realistic mobility models are fundamental to evaluate the performance of protocols in mobile ad hoc networks. Unfortunately, there are no mobility models that capture the non-homogeneous behaviors in both space and time commonly found in reality, while at the same time being easy to use and analyze. Motivated by this, we propose a time-variant community mobility model, referred to as the TVC model, which realistically captures spatial and temporal correlations. We devise the communities that lead to skewed location visiting preferences, and time periods that allow us to model time dependent behaviors and periodic re-appearances of nodes at specific locations. #R##N#To demonstrate the power and flexibility of the TVC model, we use it to generate synthetic traces that match the characteristics of a number of qualitatively different mobility traces, including wireless LAN traces, vehicular mobility traces, and human encounter traces. More importantly, we show that, despite the high level of realism achieved, our TVC model is still theoretically tractable. To establish this, we derive a number of important quantities related to protocol performance, such as the average node degree, the hitting time, and the meeting time, and provide examples of how to utilize this theory to guide design decisions in routing protocols.

Connected through hyperedge HE-1 (induced by source paper "performance modeling of epidemic routing in mobile social networks with emphasis on scalability"):
  with members:
    - "on the performance analysis of epidemic routing in non sparse delay tolerant networks"
    - "performance of opportunistic epidemic routing on edge markovian dynamic graphs"

Connected through hyperedge HE-2 (induced by source paper "achieving throughput via fine grained path planning in small world dtns"):
  with members:
    - "backpressure with adaptive redundancy bwar"

Connected through hyperedge HE-3 (induced by source paper "learning the relation between mobile encounters and web traffic patterns a data driven study"):
  with members:
    - "data driven co clustering model of internet usage in large mobile societies"

Connected through hyperedge HE-4 (induced by source paper "the effects of mobility on the hit performance of cached d2d networks"):
  with members:
    - "fundamentals of cluster centric content placement in cache enabled device to device networks"
    - "cooperative caching and transmission design in cluster centric small cell networks"
    - "optimal geographic caching in cellular networks"
    - "offloading on the edge analysis and optimization of local data storage and offloading in hetnets"
    - "caching eliminates the wireless bottleneck in video aware wireless networks"
    - "living on the edge the role of proactive caching in 5g wireless networks"
    - "exploiting user mobility for wireless content delivery"
    - "equivalence and comparison of heterogeneous cellular networks"

Connected through hyperedge HE-5 (induced by source paper "multi modal mining and modeling of big mobile networks based on users behavior and interest"):
  with members:
    - "spatio temporal modeling of wireless users internet access patterns using self organizing maps"

Connected through hyperedge HE-6 (induced by source paper "effects of content popularity on the performance of content centric opportunistic networking an analytical approach and applications"):
  with members:
    - "relieving the wireless infrastructure when opportunistic networks meet guaranteed delays"

Connected through hyperedge HE-7 (induced by source paper "user mobility evaluation for 5g small cell networks based on individual mobility model"):
  with members:
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "interference management in 5g reverse tdd hetnets with wireless backhaul a large system analysis"
    - "5g ultra dense cellular networks"
    - "handoff rate and coverage analysis in multi tier heterogeneous networks"
    - "5g wireless backhaul networks challenges and research advances"
    - "what will 5g be"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-8 (induced by source paper "offloading on the edge analysis and optimization of local data storage and offloading in hetnets"):
  with members:
    - "a survey on device to device communication in cellular networks"
    - "femtocaching and device to device collaboration a new architecture for wireless video distribution"
    - "relieving the wireless infrastructure when opportunistic networks meet guaranteed delays"
    - "femtocell networks a survey"

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)