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 "hybrid heterogeneous routing scheme for improved network performance in wsns for animal tracking"):
  Abstract: Wireless Sensor Networks (WSNs) experiences several technical challenges such as limited energy, short transmission range, limited storage capacities, and limited computational capabilities. Moreover, the sensor nodes are deployed randomly and massively over an inaccessible or hostile region. Hence WSNs are vulnerable to adversaries and are usually operated in a dynamic and unreliable environment. Animal tracking using wireless sensors is one such application of WSN where power management plays a vital role. In this paper, an energy-efficient hybrid routing method is proposed that divides the whole network into smaller regions based on sensor location and chooses the routing scheme accordingly. The sensor network consists of a base station (BS) located at a distant place outside the network, and a relay node is placed inside the network for direct communications from nodes nearer to it. The nodes are further divided into two categories based on the supplied energy; such that the ones located far away from BS and relay have higher energy than the nodes nearer to them. The network performance of the proposed method is compared with protocols like LEACH, SEP, and SNRP, considering parameters like stability period, throughput and energy consumption. Simulation result shows that the proposed method outperforms other methods with better network performance.

Includes members:
  Member "residual energy based cluster head selection in wsns for iot application":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "iot technologies for augmented human a survey")
  Member "m gear gateway based energy aware multi hop routing protocol for wsns":
    also connected through other hyperedges:
      (none)

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)