human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "emerging edge computing technologies for distributed iot systems"
  Abstract: The ever-increasing growth of connected smart devices and IoT verticals is leading to the crucial challenges of handling the massive amount of raw data generated by distributed IoT systems and providing timely feedback to the end-users. Although the existing cloud computing paradigm has an enormous amount of virtual computing power and storage capacity, it might not be able to satisfy delay-sensitive applications since computing tasks are usually processed at the distant cloud-servers. To this end, edge/fog computing has recently emerged as a new computing paradigm that helps to extend cloud functionalities to the network edge. Despite several benefits of edge computing including geo-distribution, mobility support and location awareness, various communication and computing related challenges need to be addressed for future IoT systems. In this regard, this article provides a comprehensive view of the current issues encountered in distributed IoT systems and effective solutions by classifying them into three main categories, namely, radio and computing resource management, intelligent edge-IoT systems, and flexible infrastructure management. Furthermore, an optimization framework for edge-IoT systems is proposed by considering the key performance metrics including throughput, delay, resource utilization and energy consumption. Finally, an ML based case study is presented along with some numerical results to illustrate the significance of ML in edge- IoT computing.

Connected through hyperedge HE-1 (induced by source paper "towards tactile internet in beyond 5g era recent advances current issues and future directions"):
  with members:
    - "the effect of iot new features on security and privacy new threats existing solutions and challenges yet to be solved"
    - "ultrareliable and low latency communication techniques for tactile internet services"
    - "scalable intelligence enabled networking with traffic engineering in 5g scenarios for future audio visual tactile internet"
    - "distributed optimization for energy efficient fog computing in the tactile internet"
    - "joint uplink and downlink resource configuration for ultra reliable and low latency communications"
    - "urllc embb slicing to support vr multimodal perceptions over wireless cellular systems"
    - "robust multi path communications for uavs in the urban iot"
    - "a d2d based protocol for ultra reliable wireless communications for industrial automation"

Question: Please tell me which class the center node 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)