human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "joint service caching and task offloading for mobile edge computing in dense networks"):
  Abstract: Mobile Edge Computing (MEC) pushes computing functionalities away from the centralized cloud to the network edge, thereby meeting the latency requirements of many emerging mobile applications and saving backhaul network bandwidth. Although many existing works have studied computation offloading policies, service caching is an equally, if not more important, design topic of MEC, yet receives much less attention. Service caching refers to caching application services and their related databases/libraries in the edge server (e.g. MEC-enabled BS), thereby enabling corresponding computation tasks to be executed. Because only a small number of application services can be cached in resource-limited edge server at the same time, which services to cache has to be judiciously decided to maximize the edge computing performance. In this paper, we investigate the extremely compelling but much less studied problem of dynamic service caching in MEC-enabled dense cellular networks. We propose an efficient online algorithm, called OREO, which jointly optimizes dynamic service caching and task offloading to address a number of key challenges in MEC systems, including service heterogeneity, unknown system dynamics, spatial demand coupling and decentralized coordination. Our algorithm is developed based on Lyapunov optimization and Gibbs sampling, works online without requiring future information, and achieves provable close-to-optimal performance. Simulation results show that our algorithm can effectively reduce computation latency for end users while keeping energy consumption low.

Includes members:
  Member "online learning for offloading and autoscaling in energy harvesting mobile edge computing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi agent meta reinforcement learning for self powered and sustainable edge computing systems")
  Member "a survey on mobile edge computing the communication perspective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "emm energy aware mobility management for mobile edge computing in ultra dense networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi agent meta reinforcement learning for self powered and sustainable edge computing systems")
  Member "socially trusted collaborative edge computing in ultra dense networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "all one needs to know about fog computing and related edge computing paradigms a complete survey")
  Member "energy efficient mobile edge computing in dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "edge computing enabled smart cities a comprehensive survey")
  Member "context aware proactive content caching with service differentiation in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "aoi delay tradeoff in mobile edge caching with freshness aware content refreshing")
  Member "dynamic service placement for mobile micro clouds with predicted future costs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "cooperative service caching and workload scheduling in mobile edge computing")
  Member "delay optimal computation task scheduling for mobile edge computing systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "analysis on computation intensive status update in mobile edge computing")

Question: Please tell me which class the source paper 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)