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: "distributed data storage in large scale sensor networks based on lt codes"
  Abstract: This paper proposes an algorithm for increasing data persistency in large-scale sensor networks. In the scenario considered here, k out of n nodes sense the phenomenon and produced ? information packets. Due to usually hazardous environment and limited resources, e.g. energy, sensors in the network are vulnerable. Also due to the large size of the network, gathering information from a few central hopes is not feasible. Flooding is not a desired option either due to limited memory of each node. Therefore the best approach to increase data persistency is propagating data throughout the network by random walks. The algorithm proposed here is based on distributed LT (Luby Transform) codes and it benefits from the low complexity of encoding and decoding of LT codes. In previous algorithms the essential global information (e.g., n and k) are estimated based on graph statistics, which requires excessive transmissions. In our proposed algorithm, these values are obtained without additional transmissions. Also the mixing time of random walk is enhanced by proposing a new scheme for generating the probabilistic forwarding table of random walk. The proposed method uses only local information and it is scalable to any network topology. By simulations the improved performance of developed algorithm compared to previous ones has been verified.

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)