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: "subspace properties of network coding and their applications"
  Abstract: Systems that employ network coding for content distribution convey to the receivers linear combinations of the source packets. If we assume randomized network coding, during this process, the network nodes collect random subspaces of the space spanned by the source packets. We establish several fundamental properties of the random subspaces induced in such a system and show that these subspaces implicitly carry topological information about the network and its state that can be passively collected and inferred. We leverage this information toward a number of applications that are interesting in their own right, such as topology inference, bottleneck discovery in peer-to-peer systems, and locating Byzantine attackers. We thus argue that randomized network coding, apart from its better known properties for improving information delivery rate, can additionally facilitate network management and control.

Connected through hyperedge HE-1 (induced by source paper "coded load balancing in cache networks"):
  with members:
    - "network coding approach for information centric networking"
    - "network coding for critical infrastructure networks"
    - "caching at the edge with lt codes"
    - "storage communication and load balancing trade off in distributed cache networks"
    - "optimizing mds codes for caching at the edge"
    - "network coding meets multimedia a review"
    - "fundamental limits of caching"
    - "energy aware load balancing in content delivery networks"

Connected through hyperedge HE-2 (induced by source paper "a survey on network tomography with network coding"):
  with members:
    - "active topology inference using network coding"
    - "dce a novel delay correlation measurement for tomography with passive realization"
    - "passive network tomography for erroneous networks a network coding approach"
    - "a survey on network codes for distributed storage"

Connected through hyperedge HE-3 (induced by source paper "multi terminal secrecy in a linear non coherent packetized networks"):
  with members:
    - "universal secure network coding via rank metric codes"
    - "communication over finite field matrix channels"
    - "on wiretap networks ii"

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.IT(Information Theory)