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: "wireless networks for mobile edge computing spatial modeling and latency analysis extended version"
  Abstract: It is envisioned that next-generation wireless networks will provide users ubiquitous low-latency computing services using devices at the network edge, called mobile edge computing (MEC). The key operation of MEC, mobile computation offloading (MCO), is to offload computation intensive tasks from users. Since each edge device comprises an access point (AP) and a computer server (CS), a MEC network can be decomposed as a radio access network (RAN) cascaded with a CS network (CSN). Based on the architecture, we investigate network constrained latency performance, namely communication latency (comm-latency) and computation latency (comp-latency) under the constraints of RAN coverage and CSN stability. To this end, a spatial random network is constructed featuring random node distribution, parallel computing, non-orthogonal multiple access, and random computation-task generation. Based on the model and under the said network constraints, we derive the scaling laws of comm-latency and comp-latency with respect to network-load parameters (including density of mobiles and their task-generation rates) and network-resource parameters (including bandwidth, density of APs and co-located CSs, CS computation rate). For instance, the comm-latency grows inversely with the bandwidth and sub-linearly with the expected number of mobiles per AP/CS, but decreases with the allowed fraction of mobiles following a power function with a negative exponent. Essentially, the analysis involves the interplay of theories of stochastic geometry, queueing, and parallel computing. Combining the derived scaling laws quantifies the tradeoffs between the latency, network coverage and network stability. The results provide useful guidelines for MEC-network provisioning and planning to minimize the latency by avoiding either cascaded RAN or CSN being a performance bottleneck.

Connected through hyperedge HE-1 (induced by source paper "survey on multi access edge computing for internet of things realization"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "network slicing based 5g and future mobile networks mobility resource management and challenges"
    - "knowledge defined networking"
    - "hyperprofile based computation offloading for mobile edge networks"
    - "a survey on mobile edge computing the communication perspective"
    - "emm energy aware mobility management for mobile edge computing in ultra dense networks"
    - "realizing icn in 3gpp s 5g nextgen core architecture"

Connected through hyperedge HE-2 (induced by source paper "mobile edge computing enabled heterogeneous networks"):
  with members:
    - "sir coverage analysis in cellular networks with temporal traffic a stochastic geometry approach"
    - "multiuser computation offloading and downloading for edge computing with virtualization"
    - "a survey on mobile edge computing the communication perspective"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "latency and reliability aware task offloading and resource allocation for mobile edge computing"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "heterogeneous cellular networks with los and nlos transmissions the role of massive mimo and small cells"
    - "delay optimal computation task scheduling for mobile edge computing systems"

Connected through hyperedge HE-3 (induced by source paper "stochastic control of computation offloading to a helper with a dynamically loaded cpu"):
  with members:
    - "exploiting massive d2d collaboration for energy efficient mobile edge computing"
    - "a survey on mobile edge computing the communication perspective"
    - "energy efficient mobile edge computing in dense cellular networks"
    - "exploiting non causal cpu state information for energy efficient mobile cooperative computing"
    - "joint computation and communication cooperation for mobile edge computing"
    - "delay optimal computation task scheduling for mobile edge computing systems"
    - "less is more participation incentives in d2d enhanced mobile edge computing under infectious ddos attacks"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"

Connected through hyperedge HE-4 (induced by source paper "communication computing and caching for mobile vr delivery modeling and trade off"):
  with members:
    - "design and optimization of vod schemes with client caching in wireless multicast networks"
    - "optimal task scheduling in communication constrained mobile edge computing systems for wireless virtual reality"
    - "the three primary colors of mobile systems"
    - "on content centric wireless delivery networks"

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)