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 "collaborative service caching for edge computing in dense small cell networks"):
  Abstract: Mobile Edge Computing (MEC) pushes computing functionalities away from the centralized cloud to the proximity of data sources, thereby reducing service provision latency and saving backhaul network bandwidth. Although computation offloading has been extensively studied in the literature, 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 data (libraries/databases) in the edge server, e.g. MEC-enabled Base Station (BS), enabling corresponding computation tasks to be executed. Since only a small number of 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 system performance. In this paper, we investigate collaborative service caching in MEC-enabled dense small cell (SC) networks. We propose an efficient decentralized algorithm, called CSC (Collaborative Service Caching), where a network of small cell BSs optimize service caching collaboratively to address a number of key challenges in MEC systems, including service heterogeneity, spatial demand coupling, and decentralized coordination. Our algorithm is developed based on parallel Gibbs sampling by exploiting the special structure of the considered problem using graphing coloring. The algorithm significantly improves the time efficiency compared to conventional Gibbs sampling, yet guarantees provable convergence and optimality. CSC is further extended to the SC network with selfish BSs, where a coalitional game is formulated to incentivize collaboration. A coalition formation algorithm is developed by employing the merge-and-split rules and ensures the stability of the SC coalitions.

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 "socially trusted collaborative edge computing in ultra dense networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "all one needs to know about fog computing and related edge computing paradigms a complete survey")
  Member "caching policy toward maximal success probability and area spectral efficiency of cache enabled hetnets":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the design of dynamic probabilistic caching with time varying content popularity")
  Member "context aware proactive content caching with service differentiation in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (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-7 (induced by source paper "analysis on computation intensive status update in mobile edge computing")
  Member "5g ultra dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")

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.GT(Computer Science and Game Theory)