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: "power delay tradeoff with predictive scheduling in integrated cellular and wi fi networks"
  Abstract: The explosive growth of global mobile traffic has lead to a rapid growth in the energy consumption in communication networks. In this paper, we focus on the energy-aware design of the network selection, subchannel, and power allocation in cellular and Wi-Fi networks, while taking into account the traffic delay of mobile users. The problem is particularly challenging due to the two-timescale operations for the network selection (large timescale) and subchannel and power allocation (small timescale). Based on the two-timescale Lyapunov optimization technique, we first design an online Energy-Aware Network Selection and Resource Allocation (ENSRA) algorithm. The ENSRA algorithm yields a power consumption within O(1/V) bound of the optimal value, and guarantees an O(V) traffic delay for any positive control parameter V. Motivated by the recent advancement in the accurate estimation and prediction of user mobility, channel conditions, and traffic demands, we further develop a novel predictive Lyapunov optimization technique to utilize the predictive information, and propose a Predictive Energy-Aware Network Selection and Resource Allocation (P-ENSRA) algorithm. We characterize the performance bounds of P-ENSRA in terms of the power-delay tradeoff theoretically. To reduce the computational complexity, we finally propose a Greedy Predictive Energy-Aware Network Selection and Resource Allocation (GP-ENSRA) algorithm, where the operator solves the problem in P-ENSRA approximately and iteratively. Numerical results show that GP-ENSRA significantly improves the power-delay performance over ENSRA in the large delay regime. For a wide range of system parameters, GP-ENSRA reduces the traffic delay over ENSRA by 20~30% under the same power consumption.

Connected through hyperedge HE-1 (induced by source paper "cross layer scheduling and beamforming in smart grid powered cellular networks with heterogeneous energy coordination"):
  with members:
    - "deep reinforcement learning for adaptive caching in hierarchical content delivery networks"
    - "optimal 3d trajectory design and resource allocation for solar powered uav communication systems"
    - "robust energy efficient beamforming in misome swipt systems with proportional secrecy rate"
    - "dynamic cross layer beamforming in hybrid powered communication systems with harvest use trade strategy"
    - "a hybrid energy sharing framework for green cellular networks"
    - "an overview of sustainable green 5g networks"
    - "ergodic energy management leveraging resource variability in distribution grids"
    - "comp meets smart grid a new communication and energy cooperation paradigm"

Connected through hyperedge HE-2 (induced by source paper "cross layer scheduling and beamforming in smart grid powered small cell networks"):
  with members:
    - "robust energy efficient beamforming in misome swipt systems with proportional secrecy rate"
    - "dynamic cross layer beamforming in hybrid powered communication systems with harvest use trade strategy"
    - "a hybrid energy sharing framework for green cellular networks"
    - "an overview of sustainable green 5g networks"
    - "a general utility optimization framework for energy harvesting based wireless communications"
    - "transmit power minimization in small cell networks under time average qos constraints"

Connected through hyperedge HE-3 (induced by source paper "resource allocation in cloud radio access networks with device to device communications"):
  with members:
    - "energy efficient joint resource allocation and power control for d2d communications"
    - "energy efficient resource allocation optimization for multimedia heterogeneous cloud radio access networks"
    - "fog computing based radio access networks issues and challenges"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "energy efficient joint congestion control and resource optimization in heterogeneous cloud radio access networks"
    - "queue aware energy efficient joint remote radio head activation and beamforming in cloud radio access networks"
    - "inter tier interference suppression in heterogeneous cloud radio access networks"
    - "fronthaul constrained cloud radio access networks insights and challenges"

Connected through hyperedge HE-4 (induced by source paper "timely throughput optimal scheduling with prediction"):
  with members:
    - "a new backpressure algorithm for joint rate control and routing with vanishing utility optimality gaps and finite queue lengths"
    - "online convex optimization using predictions"
    - "decentralized throughput maximizing policies for deadline constrained wireless networks"
    - "scheduling periodic real time tasks with heterogeneous reward requirements"
    - "novel architectures and algorithms for delay reduction in back pressure scheduling and routing"

Connected through hyperedge HE-5 (induced by source paper "link selection in hybrid rf vlc systems under statistical queueing constraints"):
  with members:
    - "effective capacity in cognitive radio broadcast channels"
    - "effective capacity analysis of cognitive radio channels for quality of service provisioning"
    - "on the capacity of free space optical intensity channels"
    - "outage probability of the gaussian mimo free space optical channel with ppm"

Connected through hyperedge HE-6 (induced by source paper "a survey of anticipatory mobile networking context based classification prediction methodologies and optimization techniques"):
  with members:
    - "context aware scheduling of joint millimeter wave and microwave resources for dual mode base stations"
    - "anticipatory radio resource management for mobile video streaming with linear programming"
    - "kernel based adaptive online reconstruction of coverage maps with side information"
    - "on characterization of feasible interference regions in cognitive radio networks"
    - "spatial wireless channel prediction under location uncertainty"
    - "a control theoretic approach to adaptive video streaming in dense wireless networks"
    - "5g cellular key enabling technologies and research challenges"
    - "context aware small cell networks how social metrics improve wireless resource allocation"

Connected through hyperedge HE-7 (induced by source paper "two scale stochastic control for multipoint communication systems with renewables"):
  with members:
    - "decentralized energy allocation for wireless networks with renewable energy powered base stations"
    - "cooperative energy trading in comp systems powered by smart grids"
    - "group sparse beamforming for green cloud ran"
    - "optimal power cost management using stored energy in data centers"
    - "linear precoding in cooperative mimo cellular networks with limited coordination clusters"
    - "stability and capacity regions or discrete time queueing networks"
    - "networked mimo with clustered linear precoding"

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)