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: "mapping the gnutella network properties of large scale peer to peer systems and implications for system design"
  Abstract: Despite recent excitement generated by the peer-to-peer (P2P) paradigm and the surprisingly rapid deployment of some P2P applications, there are few quantitative evaluations of P2P systems behavior. The open architecture, achieved scale, and self-organizing structure of the Gnutella network make it an interesting P2P architecture to study. Like most other P2P applications, Gnutella builds, at the application level, a virtual network with its own routing mechanisms. The topology of this virtual network and the routing mechanisms used have a significant influence on application properties such as performance, reliability, and scalability. We have built a "crawler" to extract the topology of Gnutella's application level network. In this paper we analyze the topology graph and evaluate generated network traffic. Our two major findings are that: (1) although Gnutella is not a pure power-law network, its current configuration has the benefits and drawbacks of a power-law structure, and (2) the Gnutella virtual network topology does not match well the underlying Internet topology, hence leading to ineffective use of the physical networking infrastructure. These findings guide us to propose changes to the Gnutella protocol and implementations that may bring significant performance and scalability improvements. We believe that our findings as well as our measurement and analysis techniques have broad applicability to P2P systems and provide unique insights into P2P system design tradeoffs.

Connected through hyperedge HE-1 (induced by source paper "network interdiction using adversarial traffic flows"):
  with members:
    - "prospect theory for enhanced cyber physical security of drone delivery systems a network interdiction game"
    - "on the power of randomization in network interdiction"

Connected through hyperedge HE-2 (induced by source paper "p2p pl a pattern language to design efficient and robust peer to peer systems"):
  with members:
    - "reputation based probabilistic resource allocation for avoiding free riding and formation of common interest groups in unstructured p2p networks"
    - "rarest first and choke algorithms are enough"

Connected through hyperedge HE-3 (induced by source paper "simplified biased contribution index sbci a mechanism to make p2p network fair and efficient for resource sharing"):
  with members:
    - "generalized analysis of convergence of absolute trust in peer to peer networks"
    - "biased contribution index a simpler mechanism to maintain fairness in peer to peer network"
    - "asynchronous gossip for averaging and spectral ranking"
    - "a game theoretic analysis of incentives in content production and sharing over peer to peer networks"

Connected through hyperedge HE-4 (induced by source paper "an efficient algorithm for enumerating all possible input nodes in controlling complex networks"):
  with members:
    - "input graph the hidden geometry in controlling complex networks"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"

Connected through hyperedge HE-5 (induced by source paper "centrality measures for networks with community structure"):
  with members:
    - "community based immunization strategies for epidemic control"
    - "nonlinear spread of rumor and inoculation strategies in the nodes with degree dependent tie strength in complex networks"
    - "fast multi scale community detection based on local criteria within a multi threaded algorithm"
    - "comparative evaluation of community detection algorithms a topological approach"

Connected through hyperedge HE-6 (induced by source paper "characterizing complex networks with forman ricci curvature and associated geometric flows"):
  with members:
    - "forman ricci flow for change detection in large dynamic data sets"
    - "ricci curvature of the internet topology"
    - "discovering social circles in ego networks"

Connected through hyperedge HE-7 (induced by source paper "input graph the hidden geometry in controlling complex networks"):
  with members:
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"
    - "controllability metrics limitations and algorithms for complex networks"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"

Connected through hyperedge HE-8 (induced by source paper "forman ricci flow for change detection in large dynamic data sets"):
  with members:
    - "ricci curvature of the internet topology"

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.DC(Distributed, Parallel, and Cluster Computing)