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 "an approximation algorithm for path computation and function placement in sdns"):
  Abstract: We consider the task of computing (combined) function mapping and routing for requests in Software-Defined Networks (SDNs). Function mapping refers to the assignment of nodes in the substrate network to various processing stages that requests must undergo. Routing refers to the assignment of a path in the substrate network that begins in a source node of the request, traverses the nodes that are assigned functions for this request, and ends in a destination of the request. The algorithm either rejects a request or completely serves a request, and its goal is to maximize the sum of the benefits of the served requests. The solution must abide edge and vertex capacities. We follow the framework suggested by Even for the specification of the processing requirements and routing of requests via processing-and-routing graphs (PR-graphs). In this framework, each request has a demand, a benefit, and PR-graph. Our main result is a randomized approximation algorithm for path computation and function placement with the following guarantee. Let $m$ denote the number of links in the substrate network, $\eps$ denote a parameter such that $0< \eps <1$, and $\opt_f$ denote the maximum benefit that can be attained by a fractional solution (one in which requests may be partly served and flow may be split along multiple paths). Let $\cmin$ denote the minimum edge capacity, and let $\dmax$ denote the maximum demand. Let $\Deltamax$ denote an upper bound on the number of processing stages a request undergoes. If $\cmin/(\Deltamax\cdot\dmax)=\Omega((\log m)/\eps^2)$, then with probability at least $1-\frac{1}{m}-\textit{exp}(-\Omega(\eps^2\cdot \opt_f /(\bmax \cdot \dmax)))$, the algorithm computes a $(1-\eps)$-approximate solution.

Includes members:
  Member "competitive path computation and function placement in sdns":
    also connected through other hyperedges:
      (none)
  Member "service chain and virtual network embeddings approximations using randomized rounding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust network function virtualization")
  Member "online admission control and embedding of service chains":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust online composition routing and nf placement for nfv enabled services")
  Member "software defined networking a comprehensive survey":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "specifying and placing chains of virtual network functions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a virtual network customization framework for multicast services in nfv enabled core networks")
  Member "merlin a language for provisioning network resources":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "viscr intuitive conflict free automation for securing the dynamic consumer iot infrastructures")
  Member "randomized rounding without solving the linear program":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed edge connectivity in sublinear time")

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)