human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "balanced allocation on graphs"
  Abstract: In this paper, we study the two choice balls and bins process when balls are not allowed to choose any two random bins, but only bins that are connected by an edge in an underlying graph. We show that for $n$ balls and $n$ bins, if the graph is almost regular with degree $n^\epsilon$, where $\epsilon$ is not too small, the previous bounds on the maximum load continue to hold. Precisely, the maximum load is $\log \log n + O(1/\epsilon) + O(1)$. For general $\Delta$-regular graphs, we show that the maximum load is $\log\log n + O(\frac{\log n}{\log (\Delta/\log^4 n)}) + O(1)$ and also provide an almost matching lower bound of $\log \log n + \frac{\log n}{\log (\Delta \log n)}$. #R##N#V{\"o}cking [Voc99] showed that the maximum bin size with $d$ choice load balancing can be further improved to $O(\log\log n /d)$ by breaking ties to the left. This requires $d$ random bin choices. We show that such bounds can be achieved by making only two random accesses and querying $d/2$ contiguous bins in each access. By grouping a sequence of $n$ bins into $2n/d$ groups, each of $d/2$ consecutive bins, if each ball chooses two groups at random and inserts the new ball into the least-loaded bin in the lesser loaded group, then the maximum load is $O(\log\log n/d)$ with high probability.

Connected through hyperedge HE-1 (induced by source paper "load balancing performance in distributed storage with regular balanced redundancy"):
  with members:
    - "redundancy scheduling in systems with bi modal job service time distribution"
    - "service rate region of content access from erasure coded storage"
    - "on the service capacity region of accessing erasure coded content"
    - "optimal combinatorial batch codes based on block designs"
    - "interactive analytical processing in big data systems a cross industry study of mapreduce workloads"
    - "memory allocation in distributed storage networks"

Connected through hyperedge HE-2 (induced by source paper "storage communication and load balancing trade off in distributed cache networks"):
  with members:
    - "proximity aware balanced allocations in cache networks"
    - "speeding up future video distribution via channel aware caching aided coded multicast"
    - "order optimal rate of caching and coded multicasting with random demands"
    - "balanced allocation on graphs a random walk approach"
    - "asymptotic laws for joint content replication and delivery in wireless networks"
    - "fundamental limits of caching"
    - "femtocaching wireless video content delivery through distributed caching helpers"
    - "tight bounds for parallel randomized load balancing"

Connected through hyperedge HE-3 (induced by source paper "towards balanced clustering part 1 preliminaries"):
  with members:
    - "fixed parameter approximations for k center problems in low highway dimension graphs"
    - "on the parameterized complexity of computing balanced partitions in graphs"
    - "towards combinatorial clustering preliminary research survey"
    - "multiset estimates and combinatorial synthesis"
    - "recent advances in graph partitioning"
    - "fast balanced partitioning is hard even on grids and trees"
    - "a complete anytime algorithm for balanced number partitioning"

Connected through hyperedge HE-4 (induced by source paper "proximity aware balanced allocations in cache networks"):
  with members:
    - "multi server coded caching"
    - "hierarchical coded caching"
    - "balanced allocation on graphs a random walk approach"
    - "fundamental limits of caching in wireless d2d networks"
    - "fundamental limits of caching"
    - "femtocaching wireless video content delivery through distributed caching helpers"
    - "tight bounds for parallel randomized load balancing"
    - "practical load balancing for content requests in peer to peer networks"

Connected through hyperedge HE-5 (induced by source paper "locally optimal load balancing"):
  with members:
    - "tight bounds for randomized load balancing on arbitrary network topologies"
    - "almost stable matchings by truncating the gale shapley algorithm"
    - "a primal dual parallel approximation technique applied to weighted set and vertex covers"

Connected through hyperedge HE-6 (induced by source paper "balanced allocation on graphs a random walk approach"):
  with members:
    - "storage communication and load balancing trade off in distributed cache networks"

Connected through hyperedge HE-7 (induced by source paper "balanced allocations and double hashing"):
  with members:
    - "fast pseudo random fingerprints"
    - "the power of simple tabulation hashing"

Connected through hyperedge HE-8 (induced by source paper "tight bounds for randomized load balancing on arbitrary network topologies"):
  with members:
    - "distributed random walks"
    - "quasirandom load balancing"

Question: Please tell me which class the center node 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)