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 "sixsoid a new paradigm for k coverage in 3d wireless sensor networks"):
  Abstract: Coverage in 3D wireless sensor network (WSN) is always a very critical issue to deal with. Coming up with good coverage models implies more energy efficient networks. $K$-coverage is one model that ensures that every point in a given 3D Field of Interest (FoI) is guaranteed to be covered by $k$ sensors. When it comes to 3D, coming up with a deployment of sensors that gurantees $k$-coverage becomes much more complicated than in 2D. The basic idea is to come up with a geometrical shape that is guaranteed to be $k$-covered by taking a specific arrangement of sensors, and then fill the FoI will non-overlapping copies of this shape. In this work, we propose a new shape for the 3D scenario which we call a \textbf{Devilsoid}. Prior to this work, the shape which was proposed for coverage in 3D was the so called \textbf{Reuleaux Tetrahedron}. Our construction is motivated from a construction that can be applied to the 2D version of the problem \cite{MS} in which it imples better guarantees over the \textbf{Reuleaux Triangle}. Our contribution in this paper is twofold, firstly we show how Devilsoid gurantees more coverage volume over Reuleaux Tetrahedron, secondly we show how Devilsoid also guarantees simpler and more pragmatic deployment strategy for 3D wireless sensor networks. In this paper, we show the constuction of Devilsoid, calculate its volume and discuss its effect on the $k$-coverage in WSN.

Includes members:
  Member "coverage and connectivity in three dimensional networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "beyond 5g with uavs foundations of a 3d wireless cellular network")
  Member "extremal properties of three dimensional sensor networks with applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "underwater optical wireless communications networking and localization a survey")

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)