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: "tofec achieving optimal throughput delay trade off of cloud storage using erasure codes"
  Abstract: Our paper presents solutions using erasure coding, parallel connections to storage cloud and limited chunking (i.e., dividing the object into a few smaller segments) together to significantly improve the delay performance of uploading and downloading data in and out of cloud storage. #R##N#TOFEC is a strategy that helps front-end proxy adapt to level of workload by treating scalable cloud storage (e.g. Amazon S3) as a shared resource requiring admission control. Under light workloads, TOFEC creates more smaller chunks and uses more parallel connections per file, minimizing service delay. Under heavy workloads, TOFEC automatically reduces the level of chunking (fewer chunks with increased size) and uses fewer parallel connections to reduce overhead, resulting in higher throughput and preventing queueing delay. Our trace-driven simulation results show that TOFEC's adaptation mechanism converges to an appropriate code that provides the optimal delay-throughput trade-off without reducing system capacity. Compared to a non-adaptive strategy optimized for throughput, TOFEC delivers 2.5x lower latency under light workloads; compared to a non-adaptive strategy optimized for latency, TOFEC can scale to support over 3x as many requests.

Connected through hyperedge HE-1 (induced by source paper "optimal load allocation for coded distributed computation in heterogeneous clusters"):
  with members:
    - "on the optimality of d2d coded caching with uncoded cache placement and one shot delivery"
    - "on model coding for distributed inference and transmission in mobile edge computing systems"
    - "coded matrix multiplication on a group based model"
    - "hierarchical coded computation"
    - "learning a code machine learning for approximate non linear coded computation"
    - "speeding up distributed machine learning using codes"
    - "speeding up distributed gradient descent by utilizing non persistent stragglers"
    - "hierarchical coding for distributed computing"

Connected through hyperedge HE-2 (induced by source paper "coded distributed computing performance limits and code designs"):
  with members:
    - "polar coded distributed matrix multiplication"
    - "speeding up distributed machine learning using codes"
    - "a low complexity recursive approach toward code domain noma for massive communications"
    - "rateless codes for near perfect load balancing in distributed matrix vector multiplication"
    - "almost optimal scaling of reed muller codes on bec and bsc channels"
    - "coded sparse matrix multiplication"
    - "coded computation over heterogeneous clusters"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"

Connected through hyperedge HE-3 (induced by source paper "delay optimal policies in partial fork join systems with redundancy and random slowdowns"):
  with members:
    - "mds coding is better than replication for job completion times"
    - "delay comparison of delivery and coding policies in data clusters"
    - "on delay optimal scheduling in queueing systems with replications"
    - "contrasting effects of replication in parallel systems from overload to underload and back"
    - "efficient redundancy techniques for latency reduction in cloud systems"
    - "using straggler replication to reduce latency in large scale parallel computing"
    - "efficient task replication for fast response times in parallel computation"
    - "when queueing meets coding optimal latency data retrieving scheme in storage clouds"

Connected through hyperedge HE-4 (induced by source paper "speeding up distributed machine learning using codes"):
  with members:
    - "a pliable index coding approach to data shuffling"
    - "coded computation over heterogeneous clusters"
    - "short dot computing large linear transforms distributedly using coded short dot products"
    - "minimizing latency for secure distributed computing"
    - "a fundamental tradeoff between computation and communication in distributed computing"
    - "a unified coding framework for distributed computing with straggling servers"
    - "on the worst case communication overhead for distributed data shuffling"
    - "information theoretic limits of data shuffling for distributed learning"

Connected through hyperedge HE-5 (induced by source paper "staircase pir universally robust private information retrieval"):
  with members:
    - "analyzing the download time of availability codes"
    - "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"

Connected through hyperedge HE-6 (induced by source paper "minimizing latency for secure coded computing using secret sharing via staircase codes"):
  with members:
    - "analyzing the download time of availability codes"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "coded computation over heterogeneous clusters"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "fundamental limits of coded linear transform"
    - "straggler mitigation in distributed matrix multiplication fundamental limits and optimal coding"
    - "on the optimal recovery threshold of coded matrix multiplication"
    - "rateless codes for near perfect load balancing in distributed matrix vector multiplication"
    - "a pliable index coding approach to data shuffling"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "coding for distributed fog computing"

Connected through hyperedge HE-8 (induced by source paper "latency analysis of coded computation schemes over wireless networks"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "a pliable index coding approach to data shuffling"
    - "coded computation over heterogeneous clusters"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "coding method for parallel iterative linear solver"
    - "coded convolution for parallel and distributed computing within a deadline"
    - "short dot computing large linear transforms distributedly using coded short dot products"
    - "a fundamental tradeoff between computation and communication in distributed computing"

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)