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: "fast cloud pushing the envelope on delay performance of cloud storage with coding"
  Abstract: Our paper presents solutions that can significantly improve the delay performance of putting and retrieving data in and out of cloud storage. We first focus on measuring the delay performance of a very popular cloud storage service Amazon S3. We establish that there is significant randomness in service times for reading and writing small and medium size objects when assigned distinct keys. We further demonstrate that using erasure coding, parallel connections to storage cloud and limited chunking (i.e., dividing the object into a few smaller objects) together pushes the envelope on service time distributions significantly (e.g., 76%, 80%, and 85% reductions in mean, 90th, and 99th percentiles for 2 Mbyte files) at the expense of additional storage (e.g., 1.75x). However, chunking and erasure coding increase the load and hence the queuing delays while reducing the supportable rate region in number of requests per second per node. Thus, in the second part of our paper we focus on analyzing the delay performance when chunking, FEC, and parallel connections are used together. Based on this analysis, we develop load adaptive algorithms that can pick the best code rate on a per request basis by using off-line computed queue backlog thresholds. The solutions work with homogeneous services with fixed object sizes, chunk sizes, operation type (e.g., read or write) as well as heterogeneous services with mixture of object sizes, chunk sizes, and operation types. We also present a simple greedy solution that opportunistically uses idle connections and picks the erasure coding rate accordingly on the fly. Both backlog and greedy solutions support the full rate region and provide best mean delay performance when compared to the best fixed coding rate policy. Our evaluations show that backlog based solutions achieve better delay performance at higher percentile values than the greedy solution.

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"
    - "analyzing the download time of availability codes"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "parity models a general framework for coding based resilience in ml inference"):
  with members:
    - "collage inference tolerating stragglers in distributed neural network inference using coding"
    - "pretzel opening the black box of machine learning prediction serving systems"
    - "mobilenetv2 inverted residuals and linear bottlenecks"
    - "learning a code machine learning for approximate non linear coded computation"
    - "leveraging coding techniques for speeding up distributed computing"
    - "speeding up distributed machine learning using codes"
    - "rafiki machine learning as an analytics service system"
    - "tvm an automated end to end optimizing compiler for deep learning"

Connected through hyperedge HE-3 (induced by source paper "analyzing the download time of availability codes"):
  with members:
    - "straggler mitigation at scale"
    - "simplex queues for hot data download"
    - "on the service capacity region of accessing erasure coded content"
    - "rate optimal binary linear locally repairable codes with small availability"
    - "efficient redundancy techniques for latency reduction in cloud systems"
    - "provably delay efficient data retrieving in storage clouds"
    - "repair locality with multiple erasure tolerance"
    - "locality and availability in distributed storage"

Connected through hyperedge HE-4 (induced by source paper "multi tier caching analysis in cdn based over the top video streaming systems"):
  with members:
    - "fasttrack minimizing stalls for cdn based over the top video streaming systems"
    - "optimized video streaming over cloud a stall quality trade off"
    - "generalization of lru cache replacement policy with applications to video streaming"
    - "video streaming in distributed erasure coded storage systems stall duration analysis"
    - "joint latency and cost optimization for erasure coded data center storage"
    - "sprout a functional caching approach to minimize service latency in erasure coded storage"
    - "a unified approach to the performance analysis of caching systems"
    - "on the delay storage trade off in content download from coded distributed storage systems"

Connected through hyperedge HE-5 (induced by source paper "learning a code machine learning for approximate non linear coded computation"):
  with members:
    - "rateless codes for near perfect load balancing in distributed matrix vector multiplication"
    - "coded sparse matrix multiplication"
    - "coded computation over heterogeneous clusters"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "coded convolution for parallel and distributed computing within a deadline"
    - "short dot computing large linear transforms distributedly using coded short dot products"
    - "fashion mnist a novel image dataset for benchmarking machine learning algorithms"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-6 (induced by source paper "on the service capacity region of accessing erasure coded content"):
  with members:
    - "simplex queues for hot data download"
    - "on storage allocation for maximum service rate in distributed storage systems"
    - "repair locality with multiple erasure tolerance"
    - "locality and availability in distributed storage"
    - "bounds on locally recoverable codes with multiple recovering sets"
    - "coding for fast content download"
    - "the mds queue analysing the latency performance of erasure codes"
    - "on the locality of codeword symbols"

Connected through hyperedge HE-7 (induced by source paper "taming tail latency for erasure coded distributed storage systems"):
  with members:
    - "joint latency and cost optimization for erasure coded data center storage"
    - "sprout a functional caching approach to minimize service latency in erasure coded storage"
    - "when queueing meets coding optimal latency data retrieving scheme in storage clouds"
    - "xoring elephants novel erasure codes for big data"
    - "tofec achieving optimal throughput delay trade off of cloud storage using erasure codes"
    - "on the delay storage trade off in content download from coded distributed storage systems"

Connected through hyperedge HE-8 (induced by source paper "joint latency and cost optimization for erasure coded data center storage"):
  with members:
    - "when queueing meets coding optimal latency data retrieving scheme in storage clouds"
    - "on the latency of erasure coded cloud storage systems"
    - "xoring elephants novel erasure codes for big data"
    - "tofec achieving optimal throughput delay trade off of cloud storage using erasure codes"
    - "on the delay storage trade off in content download from coded distributed storage systems"
    - "the mds queue analysing the latency performance of erasure codes"
    - "enabling node repair in any erasure code for distributed storage"
    - "a survey on network codes for distributed storage"

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.NI(Networking and Internet Architecture)