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 "multi hop routing and scheduling in wireless networks in the sinr model"):
  Abstract: We present an algorithm for multi-hop routing and scheduling of requests in wireless networks in the \sinr\ model. The goal of our algorithm is to maximize the throughput or maximize the minimum ratio between the flow and the demand. #R##N#Our algorithm partitions the links into buckets. Every bucket consists of a set of links that have nearly equivalent reception powers. We denote the number of nonempty buckets by $\sigdiv$. Our algorithm obtains an approximation ratio of $O(\sigdiv \cdot \log n)$, where $n$ denotes the number of nodes. For the case of linear powers $\sigdiv =1$, hence the approximation ratio of the algorithm is $O(\log n)$. This is the first practical approximation algorithm for linear powers with an approximation ratio that depends only on $n$ (and not on the max-to-min distance ratio). #R##N#If the transmission power of each link is part of the input (and arbitrary), then $\sigdiv = O(\log\Gamma + \log \Delta)$, where $\Gamma$ denotes the ratio of the max-to-min power, and $\Delta$ denotes the ratio of the max-to-min distance. Hence, the approximation ratio is $O(\log n \cdot (\log\Gamma + \log \Delta))$. #R##N#Finally, we consider the case that the algorithm needs to assign powers to each link in a range $[\pmin,\pmax]$. An extension of the algorithm to this case achieves an approximation ratio of $O[(\log n + \log \log \Gamma) \cdot (\log\Gamma + \log \Delta)]$.

Includes members:
  Member "nearly optimal bounds for distributed wireless scheduling in the sinr model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spanning trees with edge conflicts and wireless connectivity")
  Member "algorithms for scheduling with power control in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "beyond geometry towards fully realistic wireless models")
  Member "algorithms for scheduling with power control in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "beyond geometry towards fully realistic wireless models")
  Member "wireless capacity with oblivious power in general metrics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "reception capacity definitions game theory and hardness")
  Member "a constant factor approximation for wireless capacity maximization with power control in the sinr model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reception capacity definitions game theory and hardness")
  Member "wireless scheduling with power control":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "effective wireless scheduling via hypergraph sketches")

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.DS(Data Structures and Algorithms)