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: "energy efficient scheduling and grouping for machine type communications over cellular networks"
  Abstract: Abstract   In this paper, energy-efficient scheduling and grouping for battery-driven machine-type devices in cellular networks is investigated. We introduce a scheduling-based cooperation incentive scheme which enables machine nodes to organize themselves locally, create machine groups, and communicate through group representatives to the base station. This scheme benefits from a novel scheduler design which takes into account the cooperation level of each node, reimburses the extra energy consumptions of group representatives, and maximizes the network lifetime. As reusing cellular uplink resources for communications inside the groups degrades the Quality of Service (QoS) of the primary users, analytical results are provided which present a tradeoff between maximum allowable number of simultaneously active machine groups in a given cell and QoS of the primary users. Furthermore, we extend our derived solutions for the existing cellular networks, propose a cooperation-incentive LTE scheduler, and present our simulation results in the context of LTE. The simulation results show that the proposed solutions significantly prolong the network lifetime. Also, it is shown that under certain circumstances, reusing uplink resource by machine devices can degrade the outage performance of the primary users significantly, and hence, coexistence management of machine devices and cellular users is of paramount importance for next generations of cellular networks in order to enable group-based machine-type communications while guaranteeing QoS for the primary users.

Connected through hyperedge HE-1 (induced by source paper "optimized resource provisioning and operation control for low power wide area iot networks"):
  with members:
    - "poisson cluster process bridging the gap between ppp and 3gpp hetnet models"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "grant free radio access iot networks scalability analysis in coexistence scenarios"
    - "multiple access for 5g new radio categorization evaluation and challenges"
    - "wireless access for ultra reliable low latency communication urllc principles and building blocks"
    - "non orthogonal multiple access noma in cellular uplink and downlink challenges and enabling techniques"
    - "2d time frequency interference modelling using stochastic geometry for performance evaluation in low power wide area networks"
    - "interference and outage in clustered wireless ad hoc networks"

Connected through hyperedge HE-2 (induced by source paper "self organized low power iot networks a distributed learning approach"):
  with members:
    - "iot security techniques based on machine learning"
    - "optimized resource provisioning and operation control for low power wide area iot networks"
    - "grant free radio access iot networks scalability analysis in coexistence scenarios"
    - "low power wide area network analysis can lora scale"
    - "the best of both worlds stochastic and adversarial bandits"

Connected through hyperedge HE-3 (induced by source paper "aggregation and resource scheduling in machine type communication networks a stochastic geometry approach"):
  with members:
    - "massive multiple access based on superposition raptor codes for cellular m2m communications"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "grant free massive noma outage probability and throughput"
    - "data aggregation and packet bundling of uplink small packets for monitoring applications in lte"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "a delay optimal mac and packet scheduler for heterogeneous m2m uplink"
    - "massive machine type communication with data aggregation and resource scheduling"
    - "maximizing the link throughput between smart meters and aggregators as secondary users under power and outage constraints"

Connected through hyperedge HE-4 (induced by source paper "network lifetime maximization for cellular based m2m networks"):
  with members:
    - "e 2 mac energy efficient medium access for massive m2m communications"
    - "design of a scalable hybrid mac protocol for heterogeneous m2m networks"
    - "power efficient system design for cellular based machine to machine communications"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-5 (induced by source paper "massive machine type communication with data aggregation and resource scheduling"):
  with members:
    - "massive multiple access based on superposition raptor codes for cellular m2m communications"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "a delay optimal mac and packet scheduler for heterogeneous m2m uplink"
    - "e 2 mac energy efficient medium access for massive m2m communications"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "random cell association and void probability in poisson distributed cellular networks"
    - "aggregation and trunking of m2m traffic via d2d connections"

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.IT(Information Theory)