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: "dynamic service migration in mobile edge clouds"
  Abstract: We study the dynamic service migration problem in mobile edge-clouds that host cloud-based services at the network edge. This offers the benefits of reduction in network overhead and latency but requires service migrations as user locations change over time. It is challenging to make these decisions in an optimal manner because of the uncertainty in node mobility as well as possible non-linearity of the migration and transmission costs. In this paper, we formulate a sequential decision making problem for service migration using the framework of Markov Decision Process (MDP). Our formulation captures general cost models and provides a mathematical framework to design optimal service migration policies. In order to overcome the complexity associated with computing the optimal policy, we approximate the underlying state space by the distance between the user and service locations. We show that the resulting MDP is exact for uniform one-dimensional mobility while it provides a close approximation for uniform two-dimensional mobility with a constant additive error term. We also propose a new algorithm and a numerical technique for computing the optimal solution which is significantly faster in computation than traditional methods based on value or policy iteration. We illustrate the effectiveness of our approach by simulation using real-world mobility traces of taxis in San Francisco.

Connected through hyperedge HE-1 (induced by source paper "upper confidence primal dual optimization stochastically constrained markov decision processes with adversarial losses and unknown transitions"):
  with members:
    - "constrained upper confidence reinforcement learning"
    - "provably efficient safe exploration via primal dual policy optimization"
    - "exploration enhanced politex"
    - "neural proximal trust region policy optimization attains globally optimal policy"
    - "model free reinforcement learning in infinite horizon average reward markov decision processes"
    - "online convex optimization in adversarial markov decision processes"
    - "optimality and approximation with policy gradient methods in markov decision processes"
    - "introduction to online convex optimization"

Connected through hyperedge HE-2 (induced by source paper "retrorenting an online policy for service caching at the edge"):
  with members:
    - "budget constrained edge service provisioning with demand estimation via bandit learning"
    - "service placement with provable guarantees in heterogeneous edge computing systems"
    - "joint optimization of service caching placement and computation offloading in mobile edge computing system"
    - "joint service caching and task offloading for mobile edge computing in dense networks"
    - "a survey on mobile edge computing the communication perspective"
    - "collaborative service caching for edge computing in dense small cell networks"
    - "a comprehensive survey on fog computing state of the art and research challenges"
    - "optimal content placement for peer to peer video on demand systems"

Connected through hyperedge HE-3 (induced by source paper "meeting qos of users in a edge to cloud platform via optimally placing services and scheduling tasks"):
  with members:
    - "qos aware dynamic fog service provisioning"
    - "on optimal and fair service allocation in mobile cloud computing"

Connected through hyperedge HE-4 (induced by source paper "follow me at the edge mobility aware dynamic service placement for mobile edge computing"):
  with members:
    - "edge intelligence on demand deep learning model co inference with device edge synergy"
    - "efficient resource allocation for on demand mobile edge cloud computing"
    - "exploiting massive d2d collaboration for energy efficient mobile edge computing"
    - "emm energy aware mobility management for mobile edge computing in ultra dense networks"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "toward hierarchical mobile edge computing an auction based profit maximization approach"
    - "dynamic service placement for mobile micro clouds with predicted future costs"
    - "a non stochastic learning approach to energy efficient mobility management"

Connected through hyperedge HE-5 (induced by source paper "addressing the challenges in federating edge resources"):
  with members:
    - "online learning for offloading and autoscaling in energy harvesting mobile edge computing"
    - "enorm a framework for edge node resource management"
    - "edge as a service towards distributed cloud architectures"
    - "challenges and opportunities in edge computing"
    - "software defined networking state of the art and research challenges"

Connected through hyperedge HE-6 (induced by source paper "edge cloud offloading algorithms issues methods and perspectives"):
  with members:
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "fog radio access networks mobility management interference mitigation and resource optimization"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "joint optimization of radio and computational resources for multicell mobile edge computing"

Connected through hyperedge HE-7 (induced by source paper "a manifesto for future generation cloud computing research directions for the next decade"):
  with members:
    - "cloud benchmarking for maximising performance of scientific applications"
    - "hpc cloud for scientific and business applications taxonomy vision and research challenges"
    - "in datacenter performance analysis of a tensor processing unit"
    - "knowledge infused and consistent complex event processing over real time and persistent streams"
    - "enorm a framework for edge node resource management"
    - "serverless computing current trends and open problems"
    - "demystifying fog computing characterizing architectures applications and abstractions"
    - "snafu function as a service faas runtime design and implementation"

Connected through hyperedge HE-8 (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"
    - "online placement of multi component applications in edge computing environments"
    - "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"

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)