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 "amctd adaptive mobility of courier nodes in threshold optimized dbr protocol for underwater wireless sensor networks"):
  Abstract: In dense underwater sensor networks (UWSN), the major confronts are high error probability, incessant variation in topology of sensor nodes, and much energy consumption for data transmission. However, there are some remarkable applications of UWSN such as management of seabed and oil reservoirs, exploration of deep sea situation and prevention of aqueous disasters. In order to accomplish these applications, ignorance of the limitations of acoustic communications such as high delay and low bandwidth is not feasible. In this paper, we propose Adaptive mobility of Courier nodes in Threshold-optimized Depth-based routing (AMCTD), exploring the proficient amendments in depth threshold and implementing the optimal weight function to achieve longer network lifetime. We segregate our scheme in 3 major phases of weight updating, depth threshold variation and adaptive mobility of courier nodes. During data forwarding, we provide the framework for alterations in threshold to cope with the sparse condition of network. We ultimately perform detailed simulations to scrutinize the performance of our proposed scheme and its comparison with other two notable routing protocols in term of network lifetime and other essential parameters. The simulations results verify that our scheme performs better than the other techniques and near to optimal in the field of UWSN.

Includes members:
  Member "ach away cluster heads scheme for energy efficient clustering protocols in wsns":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "modeling and evaluating performance of routing operations in reactive routing protocols")
  Member "q leach a new routing protocol for wsns":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a new rank order clustering algorithm for prolonging the lifetime of wireless sensor networks")
  Member "heer hybrid energy efficient reactive protocol for wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "survey on variants of distributed energy efficient clustering protocols in heterogeneous wireless sensor network")
  Member "on modeling geometric joint sink mobility with delay tolerant cluster less wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distance aware relaying energy efficient dare to monitor patients in multi hop body area sensor networks")
  Member "lpch and udlpch location aware routing techniques in wsns":
    also connected through other hyperedges:
      (none)
  Member "e horm an energy efficient hole removing mechanism in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "divide and rule scheme for energy efficient routing in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "on adaptive energy efficient transmission in wsns":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an energy efficient decoding scheme for 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.NI(Networking and Internet Architecture)