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: "beyond counting new perspectives on the active ipv4 address space"
  Abstract: In this study, we report on techniques and analyses that enable us to capture Internet-wide activity at individual IP address-level granularity by relying on server logs of a large commercial content delivery network (CDN) that serves close to 3 trillion HTTP requests on a daily basis. Across the whole of 2015, these logs recorded client activity involving 1.2 billion unique IPv4 addresses, the highest ever measured, in agreement with recent estimates. Monthly client IPv4 address counts showed constant growth for years prior, but since 2014, the IPv4 count has stagnated while IPv6 counts have grown. Thus, it seems we have entered an era marked by increased complexity, one in which the sole enumeration of active IPv4 addresses is of little use to characterize recent growth of the Internet as a whole.   With this observation in mind, we consider new points of view in the study of global IPv4 address activity. Our analysis shows significant churn in active IPv4 addresses: the set of active IPv4 addresses varies by as much as 25% over the course of a year. Second, by looking across the active addresses in a prefix, we are able to identify and attribute activity patterns to networkm restructurings, user behaviors, and, in particular, various address assignment practices. Third, by combining spatio-temporal measures of address utilization with measures of traffic volume, and sampling-based estimates of relative host counts, we present novel perspectives on worldwide IPv4 address activity, including empirical observation of under-utilization in some areas, and complete utilization, or exhaustion, in others.

Connected through hyperedge HE-1 (induced by source paper "anonymizing masses practical light weight anonymity at the network level"):
  with members:
    - "taranet traffic analysis resistant anonymity at the network layer"
    - "a multi perspective analysis of carrier grade nat deployment"
    - "hornet high speed onion routing at the network layer"
    - "dovetail stronger anonymity in next generation internet routing"
    - "netfence preventing internet denial of service from inside out"
    - "active internet traffic filtering real time response to denial of service attacks"

Connected through hyperedge HE-2 (induced by source paper "an internet heartbeat"):
  with members:
    - "yarrp ing the internet randomized high speed active topology discovery"
    - "principles for measurability in protocol design"
    - "encore lightweight measurement of web censorship with cross origin requests"

Connected through hyperedge HE-3 (induced by source paper "clusters in the expanse understanding and unbiasing ipv6 hitlists"):
  with members:
    - "in the ip of the beholder strategies for active ipv6 topology discovery"
    - "kip a measured approach to ipv6 address anonymization"
    - "hloc hints based geolocation leveraging multiple measurement frameworks"
    - "large scale classification of ipv6 ipv4 siblings with variable clock skew"
    - "entropy ip uncovering structure in ipv6 addresses"
    - "towards better internet citizenship reducing the footprint of internet wide scans by topology aware prefix selection"
    - "scanning the ipv6 internet towards a comprehensive hitlist"
    - "carrier grade anomaly detection using time to live header information"

Connected through hyperedge HE-4 (induced by source paper "a multi perspective analysis of carrier grade nat deployment"):
  with members:
    - "a primer on ipv4 scarcity"
    - "peer to peer communication across network address translators"

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)