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 "a new rank order clustering algorithm for prolonging the lifetime of wireless sensor networks"):
  Abstract: Energy efficient resource management is critical for prolonging the lifetime of wireless sensor networks (WSN). Clustering of sensor nodes with the aim of distributing the traffic loads in the network is a proven approach for balanced energy consumption in WSN. The main body of literature in this topic can be classified as hierarchical and distance-based clustering techniques in which multi-hop, multi-level forwarding and distance-based criteria, respectively, are utilized for categorization of sensor nodes. In this study, we propose the Approximate Rank-Order Wireless Sensor Networks (ARO-WSN) clustering algorithm as a combined hierarchical and distance-based clustering approach. ARO-WSN algorithm which has been extensively used in the field of image processing, runs in the order of O(n) for a large data set, therefore it can be applied on WSN. The results shows that ARO-WSN outperforms the classical LEACH, LEACH-C and K-means clustering algorithms in the terms of energy consumption and network lifetime.

Includes members:
  Member "clustering millions of faces by identity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "person recognition in personal photo collections")
  Member "q leach a new routing protocol for wsns":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "measuring fatigue of soldiers in wireless body area sensor 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.DC(Distributed, Parallel, and Cluster Computing)