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 "follow me at the edge mobility aware dynamic service placement for mobile edge computing"):
  Abstract: Mobile edge computing is a new computing paradigm, which pushes cloud computing capabilities away from the centralized cloud to the network edge. However, with the sinking of computing capabilities, the new challenge incurred by user mobility arises: since end-users typically move erratically, the services should be dynamically migrated among multiple edges to maintain the service performance, i.e., user-perceived latency. Tackling this problem is non-trivial since frequent service migration would greatly increase the operational cost. To address this challenge in terms of the performance-cost trade-off, in this paper we study the mobile edge service performance optimization problem under long-term cost budget constraint. To address user mobility which is typically unpredictable, we apply Lyapunov optimization to decompose the long-term optimization problem into a series of real-time optimization problems which do not require a priori knowledge such as user mobility. As the decomposed problem is NP-hard, we first design an approximation algorithm based on Markov approximation to seek a near-optimal solution. To make our solution scalable and amenable to future 5G application scenario with large-scale user devices, we further propose a distributed approximation scheme with greatly reduced time complexity, based on the technique of best response update. Rigorous theoretical analysis and extensive evaluations demonstrate the efficacy of the proposed centralized and distributed schemes.

Includes members:
  Member "edge intelligence on demand deep learning model co inference with device edge synergy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mdldroid a chainsgd reduce approach to mobile deep learning for personal mobile sensing")
  Member "efficient resource allocation for on demand mobile edge cloud computing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "edge ai on demand accelerating deep neural network inference via edge computing")
  Member "exploiting massive d2d collaboration for energy efficient mobile edge computing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "edge intelligence paving the last mile of artificial intelligence with edge computing")
  Member "emm energy aware mobility management for mobile edge computing in ultra dense networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi agent meta reinforcement learning for self powered and sustainable edge computing systems")
  Member "mobile edge computing a survey on architecture and computation offloading":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fog computing systems state of the art research issues and future trends")
  Member "toward hierarchical mobile edge computing an auction based profit maximization approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "all one needs to know about fog computing and related edge computing paradigms a complete survey")
  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 "a non stochastic learning approach to energy efficient mobility management":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "adaptive learning based task offloading for vehicular edge computing systems")

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.NI(Networking and Internet Architecture)