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 survey of multi objective optimization in wireless sensor networks metrics algorithms and open problems"):
  Abstract: Wireless sensor networks (WSNs) have attracted substantial research interest, especially in the context of performing monitoring and surveillance tasks. However, it is challenging to strike compelling tradeoffs amongst the various conflicting optimization criteria, such as the network’s energy dissipation, packet-loss rate, coverage, and lifetime. This paper provides a tutorial and survey of recent research and development efforts addressing this issue by using the technique of multi-objective optimization (MOO). First, we provide an overview of the main optimization objectives used in WSNs. Then, we elaborate on various prevalent approaches conceived for MOO, such as the family of mathematical programming-based scalarization methods, the family of heuristics/metaheuristics-based optimization algorithms, and a variety of other advanced optimization techniques. Furthermore, we summarize a range of recent studies of MOO in the context of WSNs, which are intended to provide useful guidelines for researchers to understand the referenced literature. Finally, we discuss a range of open problems to be tackled by future research.

Includes members:
  Member "distributed energy spectral efficiency optimization for partial full interference alignment in multi user multi relay multi cell mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "iterative distributed minimum total mse approach for secure communications in mimo interference channels")
  Member "energy efficient ofdma networks maintaining statistical qos guarantees for delay sensitive traffic":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "effective capacity in wireless networks a comprehensive survey")
  Member "wireless sensor network virtualization a survey":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance enhancement of diffusion based molecular communication with photolysis")
  Member "markov decision processes with applications in wireless sensor networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimized trajectory design in uav based cellular networks for 3d users a double q learning approach")
  Member "accuracy of homology based coverage hole detection for wireless sensor networks on sphere":
    also connected through other hyperedges:
      (none)
  Member "end to end reliability aware scheduling for wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "boost your cots ieee 802 15 4 network with inter slot interference cancellation for industrial iot")
  Member "multiband spectrum access great promises for future cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reconfigurable wireless networks")
  Member "spectral and energy spectral efficiency optimization of joint transmit and receive beamforming based multi relay mimo ofdma cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "low complexity downlink user selection for massive mimo systems")

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)