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: "joint optimization of radio and computational resources for multicell mobile edge computing"
  Abstract: Migrating computational intensive tasks from mobile devices to more resourceful cloud servers is a promising technique to increase the computational capacity of mobile devices while saving their battery energy. In this paper, we consider an MIMO multicell system where multiple mobile users (MUs) ask for computation offloading to a common cloud server. We formulate the offloading problem as the  joint  optimization of the radio resources—the transmit precoding matrices of the MUs—and the computational resources—the CPU cycles/second assigned by the cloud to each MU—in order to minimize the overall users’ energy consumption, while meeting latency constraints. The resulting optimization problem is nonconvex (in the objective function and constraints). Nevertheless, in the single-user case, we are able to compute the global optimal solution in closed form. In the more challenging multiuser scenario, we propose an iterative algorithm, based on a novel successive convex approximation technique, converging to a local optimal solution of the original nonconvex problem. We then show that the proposed algorithmic framework naturally leads to a distributed and parallel implementation across the radio access points, requiring only a limited coordination/signaling with the cloud. Numerical results show that the proposed schemes outperform disjoint optimization algorithms.

Connected through hyperedge HE-1 (induced by source paper "analysis on computation intensive status update in mobile edge computing"):
  with members:
    - "trading off computation with transmission in status update systems"
    - "age of information for computation intensive messages in mobile edge computing"
    - "timely cloud computing preemption and waiting"
    - "age of information in a network of preemptive servers"
    - "the age of information in networks moments distributions and sampling"
    - "joint status sampling and updating for minimizing age of information in the internet of things"
    - "joint information freshness and completion time optimization for vehicular networks"
    - "a survey on mobile edge computing the communication perspective"

Connected through hyperedge HE-2 (induced by source paper "joint optimization of signal design and resource allocation in wireless d2d edge computing"):
  with members:
    - "joint task assignment and resource allocation for d2d enabled mobile edge computing"
    - "joint computation and communication cooperation for energy efficient mobile edge computing"
    - "decentralized computation offloading for multi user mobile edge computing a deep reinforcement learning approach"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "multiuser resource allocation for mobile edge computation offloading"
    - "the interplay between massive mimo and underlaid d2d networking"
    - "on feasibility of interference alignment in mimo interference networks"
    - "on feasibility of interference alignment in mimo interference networks"

Connected through hyperedge HE-3 (induced by source paper "from megabits to cpu ticks enriching a demand trace in the age of mec"):
  with members:
    - "cellular network traces towards 5g usage analysis and generation"
    - "the price of fog a data driven study on caching architectures in vehicular networks"
    - "a sharing and competition aware framework for cellular network evolution planning"
    - "efficient multi user computation offloading for mobile edge cloud computing"
    - "living on the edge the role of proactive caching in 5g wireless networks"
    - "data for development the d4d challenge on mobile phone data"

Connected through hyperedge HE-4 (induced by source paper "let s share a game theoretic framework for resource sharing in mobile edge clouds"):
  with members:
    - "a game theoretic framework for resource sharing in clouds"
    - "a game theoretic approach to multi objective resource sharing and allocation in mobile edge"
    - "computing resource allocation in three tier iot fog networks a joint optimization approach combining stackelberg game and matching"
    - "energy efficient resource allocation for mobile edge computation offloading"

Connected through hyperedge HE-5 (induced by source paper "computation offloading for iot in c ran optimization and deep learning"):
  with members:
    - "non stationarities in extra large scale massive mimo"
    - "cross layer design for mission critical iot in mobile edge computing systems"
    - "two timescale hybrid compression and forward for massive mimo aided c ran"
    - "learning to optimize training deep neural networks for interference management"
    - "beyond massive mimo the potential of positioning with large intelligent surfaces"
    - "applications of deep reinforcement learning in communications and networking a survey"
    - "performance analysis of large intelligence surfaces liss asymptotic data rate and channel hardening effects"
    - "deep learning in mobile and wireless networking a survey"

Connected through hyperedge HE-6 (induced by source paper "joint task assignment and resource allocation for d2d enabled mobile edge computing"):
  with members:
    - "energy efficient mobile edge computation offloading for applications with shared data"
    - "joint computation and communication cooperation for energy efficient mobile edge computing"
    - "exploiting physical layer security for multiuser multicarrier computation offloading"
    - "resource sharing of a computing access point for multi user mobile cloud offloading with delay constraints"
    - "exploiting massive d2d collaboration for energy efficient mobile edge computing"
    - "a survey on mobile edge computing the communication perspective"
    - "joint task offloading scheduling and transmit power allocation for mobile edge computing systems"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"

Connected through hyperedge HE-7 (induced by source paper "wireless caching helper system with heterogeneous traffic and random availability"):
  with members:
    - "modeling and performance analysis of full duplex communications in cache enabled d2d networks"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "optimal caching and scheduling for cache enabled d2d communications"
    - "cache enabled device to device communications offloading gain and energy cost"
    - "spatially correlated content caching for device to device communications"
    - "wireless caching technical misconceptions and business barriers"
    - "on the delay of geographical caching methods in two tiered heterogeneous networks"
    - "content caching and distribution in smart grid enabled wireless networks"

Connected through hyperedge HE-8 (induced by source paper "bandit convex optimization for scalable and dynamic iot management"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "an online secretary framework for fog network formation with minimal latency"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "online learning for wireless distributed computing"
    - "online optimization competing with dynamic comparators"
    - "an optimal algorithm for bandit and zero order convex optimization with two point feedback"
    - "efficient multi user computation offloading for mobile edge cloud computing"

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)