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: "analyzing the download time of availability codes"
  Abstract: Availability codes have recently been proposed to facilitate efficient storage, management, and retrieval of frequently accessed data in distributed storage systems. Such codes provide multiple disjoint recovery groups for each data object, which makes it possible for multiple users to access the same object in a non-overlapping way. However in the presence of server-side performance variability, downloading an object using a recovery group takes longer than using a single server hosting the object. Therefore it is not immediately clear whether availability codes reduce latency to access hot data. Accordingly, the goal of this paper is to analyze, using a queuing theoretical approach, the download time in storage systems that employ availability codes. For data access, we consider the widely adopted Fork-Join model with redundancy. In this model, each request arrival splits into multiple copies and completes as soon as any one of the copies finishes service. We first carry out the analysis under the low-traffic regime in which case the system consists of at most one download request at any time. In this setting, we compare the download time in systems with availability, maximum distance separable (MDS), and replication codes. Our results indicate that availability codes can reduce download time in some settings, but are not always optimal. When the low-traffic assumption does not hold, system consists of multiple inter-dependent Fork-Join queues operating in parallel, which makes the exact analysis intractable. For this case we present upper and lower bounds on the download time. These bounds yield insight on system performance with respect to varying popularities over the stored objects. We also derive an M/G/1 queue approximation for the system, and show with simulations that it performs well in estimating the actual system performance.

Connected through hyperedge HE-1 (induced by source paper "a combinatorial view of the service rates of codes problem its equivalence to fractional matching and its connection with batch codes"):
  with members:
    - "a geometric view of the service rates of codes problem and its application to the service rate of the first order reed muller codes"
    - "load balancing performance in distributed storage with regular balanced redundancy"
    - "service rate region of content access from erasure coded storage"
    - "simplex queues for hot data download"
    - "batch and pir codes and their connections to locally repairable codes"
    - "on distributed storage allocations of large files for maximum service rate"
    - "on the service capacity region of accessing erasure coded content"
    - "on storage allocation for maximum service rate in distributed storage systems"

Connected through hyperedge HE-2 (induced by source paper "stochastic gradient coding for straggler mitigation in distributed learning"):
  with members:
    - "fundamental limits of approximate gradient coding"
    - "distributed stochastic gradient descent using ldgm codes"
    - "erasurehead distributed gradient descent without delays using approximate gradient coding"
    - "coded cooperative computation for internet of things"
    - "speeding up distributed machine learning using codes"
    - "anytime stochastic gradient descent a time to hear from all the workers"
    - "speeding up distributed gradient descent by utilizing non persistent stragglers"
    - "fundamental limits of coded linear transform"

Connected through hyperedge HE-3 (induced by source paper "private and rateless adaptive coded matrix vector multiplication"):
  with members:
    - "codedprivateml a fast and privacy preserving framework for distributed machine learning"
    - "secure coded cooperative computation at the heterogeneous edge against byzantine attacks"
    - "an application of storage optimal matdot codes for coded matrix multiplication fast k nearest neighbors estimation"
    - "speeding up distributed machine learning using codes"
    - "anytime stochastic gradient descent a time to hear from all the workers"
    - "gasp codes for secure distributed matrix multiplication"
    - "speeding up distributed gradient descent by utilizing non persistent stragglers"
    - "rate efficiency and straggler robustness through partition in distributed two sided secure matrix computation"

Connected through hyperedge HE-4 (induced by source paper "staircase pir universally robust private information retrieval"):
  with members:
    - "robust private information retrieval from coded systems with byzantine and colluding servers"
    - "speeding up distributed machine learning using codes"
    - "lifting private information retrieval from two to any number of messages"
    - "polynomially coded regression optimal straggler mitigation via data encoding"
    - "minimizing latency for secure coded computing using secret sharing via staircase codes"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "the capacity of private information retrieval from byzantine and colluding databases"
    - "coded convolution for parallel and distributed computing within a deadline"

Connected through hyperedge HE-5 (induced by source paper "minimizing latency for secure coded computing using secret sharing via staircase codes"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "private learning on networks part ii"
    - "coded convolution for parallel and distributed computing within a deadline"
    - "short dot computing large linear transforms distributedly using coded short dot products"
    - "revisiting distributed synchronous sgd"
    - "improving distributed gradient descent using reed solomon codes"
    - "a fundamental tradeoff between computation and communication in distributed computing"

Connected through hyperedge HE-6 (induced by source paper "simplex queues for hot data download"):
  with members:
    - "on the service capacity region of accessing erasure coded content"
    - "efficient redundancy techniques for latency reduction in cloud systems"
    - "locality and availability in distributed storage"
    - "a family of optimal locally recoverable codes"
    - "xoring elephants novel erasure codes for big data"
    - "on the delay storage trade off in content download from coded distributed storage systems"
    - "on the locality of codeword symbols"

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.PF(Performance)