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: "non stationary resource allocation policies for delay constrained video streaming application to video over internet of things enabled networks"
  Abstract: Due to the high bandwidth requirements and stringent delay constraints of multi-user wireless video transmission applications, ensuring that all video senders have sufficient transmission opportunities to use before their delay deadlines expire is a longstanding research problem. We propose a novel solution that addresses this problem without assuming detailed packet-level knowledge, which is unavailable at resource allocation time. Instead, we translate the transmission delay deadlines of each sender's video packets into a monotonically-decreasing weight distribution within the considered time horizon. Higher weights are assigned to the slots that have higher probability for deadline-abiding delivery. Given the sets of weights of the senders' video streams, we propose the low-complexity Delay-Aware Resource Allocation (DARA) approach to compute the optimal slot allocation policy that maximizes the deadline-abiding delivery of all senders. A unique characteristic of the DARA approach is that it yields a non-stationary slot allocation policy that depends on the allocation of previous slots. We prove that the DARA approach is optimal for weight distributions that are exponentially decreasing in time. We further implement our framework for real-time video streaming in wireless personal area networks that are gaining significant traction within the new Internet-of-Things (IoT) paradigm. For multiple surveillance videos encoded with H.264/AVC and streamed via the 6tisch framework that simulates the IoT-oriented IEEE 802.15.4e TSCH medium access control, our solution is shown to be the only one that ensures all video bitstreams are delivered with acceptable quality in a deadline-abiding manner.

Connected through hyperedge HE-1 (induced by source paper "authentication access control privacy threats and trust management towards securing fog computing environments a review"):
  with members:
    - "user s privacy in recommendation systems applying online social network data a survey and taxonomy"
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "fogbus a blockchain based lightweight framework for edge and fog computing"
    - "fog computing survey of trends architectures requirements and research directions"
    - "blockchain in internet of things challenges and solutions"
    - "big data computing and clouds"
    - "combining ensemble methods and social network metrics for improving accuracy of ocsvm on intrusion detection in scada systems"

Connected through hyperedge HE-2 (induced by source paper "data collection and wireless communication in internet of things iot using economic analysis and pricing models a survey"):
  with members:
    - "economics of internet of things iot an information market approach"
    - "target tracking via crowdsourcing a mechanism design approach"
    - "from participatory sensing to mobile crowd sensing"
    - "machine learning in wireless sensor networks algorithms strategies and applications"
    - "motivating smartphone collaboration in data acquisition and distributed computing"
    - "fairness and social welfare in incentivizing participatory sensing"
    - "optimal pricing and load sharing for energy saving in communications cooperation"
    - "incentives for privacy tradeoff in community sensing"

Connected through hyperedge HE-3 (induced by source paper "allocation of heterogeneous resources of an iot device to flexible services"):
  with members:
    - "flexible allocation of heterogeneous resources to services on an iot device"
    - "optimization of free space optical wireless network for cellular backhauling"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-4 (induced by source paper "economics of internet of things iot an information market approach"):
  with members:
    - "target tracking via crowdsourcing a mechanism design approach"

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)