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: "online placement of multi component applications in edge computing environments"
  Abstract: Mobile edge computing is a new cloud computing paradigm, which makes use of small-sized edge clouds to provide real-time services to users. These mobile edge-clouds (MECs) are located in close proximity to users, thus enabling users to seamlessly access applications running on MECs. Due to the co-existence of the core (centralized) cloud, users, and one or multiple layers of MECs, an important problem is to decide where (on which computational entity) to place different components of an application. This problem, known as the application or workload placement problem, is notoriously hard, and therefore, heuristic algorithms without performance guarantees are generally employed in common practice, which may unknowingly suffer from poor performance as compared with the optimal solution. In this paper, we address the application placement problem and focus on developing algorithms with provable performance bounds. We model the user application as an application graph and the physical computing system as a physical graph, with resource demands/availabilities annotated on these graphs. We first consider the placement of a linear application graph and propose an algorithm for finding its optimal solution. Using this result, we then generalize the formulation and obtain online approximation algorithms with polynomial-logarithmic (poly-log) competitive ratio for tree application graph placement. We jointly consider node and link assignment, and incorporate multiple types of computational resources at nodes.

Connected through hyperedge HE-1 (induced by source paper "secure cloud edge deployments with trust"):
  with members:
    - "how to place your apps in the fog state of the art and open challenges"
    - "explainable security"
    - "demystifying fog computing characterizing architectures applications and abstractions"

Connected through hyperedge HE-2 (induced by source paper "guardians of the deep fog failure resilient dnn inference from edge to cloud"):
  with members:
    - "all one needs to know about fog computing and related edge computing paradigms a complete survey"
    - "wireless network intelligence at the edge"
    - "edge intelligence on demand deep learning model co inference with device edge synergy"
    - "adaptive federated learning in resource constrained edge computing systems"
    - "horovod fast and easy distributed deep learning in tensorflow"
    - "distributed deep neural networks over the cloud the edge and end devices"
    - "deepiot compressing deep neural network structures for sensing systems with a compressor critic framework"
    - "tensorflow a system for large scale machine learning"

Connected through hyperedge HE-3 (induced by source paper "how to place your apps in the fog state of the art and open challenges"):
  with members:
    - "a survey of energy efficiency in sdn software based methods and optimization models"
    - "fogstore toward a distributed data store for fog computing"
    - "computing resource allocation in three tier iot fog networks a joint optimization approach combining stackelberg game and matching"

Connected through hyperedge HE-4 (induced by source paper "a geo aware server assignment problem for mobile edge computing"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "energy efficient resource allocation for mobile edge computing based augmented reality applications"
    - "an improved approximation for k median and positive correlation in budgeted optimization"

Connected through hyperedge HE-5 (induced by source paper "a survey on mobile edge computing the communication perspective"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "joint energy minimization and resource allocation in c ran with mobile cloud"
    - "latency optimization for resource allocation in mobile edge computation offloading"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "proactive edge computing in latency constrained fog networks"
    - "computation peer offloading for energy constrained mobile edge computing in small cell networks"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "joint computation and communication cooperation for mobile edge computing"

Connected through hyperedge HE-6 (induced by source paper "mobile edge computing a survey on architecture and computation offloading"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "resource management in cloud networking using economic analysis and pricing models a survey"
    - "dynamic service placement for mobile micro clouds with predicted future costs"
    - "delay optimal computation task scheduling for mobile edge computing systems"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "multiuser resource allocation for mobile edge computation offloading"
    - "power delay tradeoff in multi user mobile edge computing systems"

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.DC(Distributed, Parallel, and Cluster Computing)