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 "exploiting the past to reduce delay in csma scheduling a high order markov chain approach"):
  Abstract: Recently several CSMA algorithms based on the Glauber dynamics model have been proposed for multihop wireless scheduling, as viable solutions to achieve the throughput optimality, yet are simple to implement. However, their delay performances still remain unsatisfactory, mainly due to the nature of the underlying Markov chains that imposes a fundamental constraint on how the link state can evolve over time. In this paper, we propose a new approach toward better queueing and delay performance, based on our observation that the algorithm needs not be Markovian, as long as it can be implemented in a distributed manner, achieve the same throughput optimality, while offering far better delay performance for general network topologies. Our approach hinges upon utilizing past state information observed by local link and then constructing a high-order Markov chain for the evolution of the feasible link schedules. We show in theory and simulation that our proposed algorithm, named delayed CSMA, adds virtually no additional overhead onto the existing CSMA-based algorithms, achieves the throughput optimality under the usual choice of link weight as a function of local queue length, and also provides much better delay performance by effectively `de-correlating' the link state process (thus removing link starvation) under any arbitrary network topology. From our extensive simulations we observe that the delay under our algorithm can be often reduced by a factor of 20 over a wide range of scenarios, compared to the standard Glauber-dynamics-based CSMA algorithm.

Includes members:
  Member "on the design of efficient csma algorithms for wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the power of randomization for scheduling real time traffic in wireless networks")
  Member "throughput optimal random access with order optimal delay":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient csma using regional free energy approximations")
  Member "fast mixing of parallel glauber dynamics and low delay csma scheduling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "effective wireless scheduling via hypergraph sketches")
  Member "q csma queue length based csma ca algorithms for achieving maximum throughput and low delay in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the power of randomization for scheduling real time traffic in wireless networks")
  Member "randomized scheduling algorithm for queueing networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on non preemptive vm scheduling in the cloud")
  Member "distributed link scheduling with constant overhead":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "heat diffusion pareto optimal dynamic routing for time varying wireless 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.NI(Networking and Internet Architecture)