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 "networked computing in wireless sensor networks for structural health monitoring"):
  Abstract: This paper studies the problem of distributed computation over a wireless network of resource constrained sensor#R##N#nodes. In particular, we focus our attention on sensor networks used for structural health monitoring. Within#R##N#this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode#R##N#shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a#R##N#central location, computing SVD within the network can result in a significantly smaller energy consumption#R##N#and delay. Recent results have proposed methods to decompose SVD into components that can be carried out in#R##N#a distributed way. The focus of this paper is to determine a near-optimal communication structure that enables#R##N#the distribution of this computation and the reassembly of the final results, with the objective of minimizing#R##N#energy consumption subject to a computational delay constraint. We show that this reduces to a generalized#R##N#clustering problem; a cluster forms a unit on which a component of the overall computation is performed. We#R##N#establish that this problem is NP-hard. By relaxing the delay constraint, we derive a lower bound to this problem.#R##N#We also show that the optimal solution to the unconstrained problem has a simple structure that reveals insights#R##N#into the solution of the original constrained problem. We then propose an integer linear program (ILP) to solve#R##N#the constrained problem exactly as well as an approximate algorithm with a proven approximation ratio. We#R##N#also present a distributed version of the approximate algorithm. Numerical results are presented.

Includes members:
  Member "model based event detection in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "local convergence of an algorithm for subspace identification from partial data")
  Member "optimal strategies for computing symmetric boolean functions in collocated networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal computation of symmetric boolean functions in collocated networks")
  Member "overlapping multihop clustering for wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimizing the number of fog nodes for cloud fog thing 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)