human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "imbalance measure and proactive channel rebalancing algorithm for the lightning network"):
  Abstract: Making a payment in a privacy-aware payment channel network is achieved by trying several payment paths until one succeeds. With a large network, such as the Lightning Network, a completion of a single payment can take up to several minutes. We introduce a network imbalance measure and formulate the optimization problem of improving the balance of the network as a sequence of rebalancing operations of the funds within the channels along circular paths within the network. As the funds and balances of channels are not globally known, we introduce a greedy heuristic with which every node despite the uncertainty can improve its own local balance. In an empirical simulation on a recent snapshot of the Lightning Network we demonstrate that the imbalance distribution of the network has a Kolmogorov-Smirnoff distance of 0.74 in comparison to the imbalance distribution after the heuristic is applied. We further show that the success rate of a single unit payment increases from 11.2% on the imbalanced network to 98.3% in the balanced network. Similarly, the median possible payment size across all pairs of participants increases from 0 to 0.5 mBTC for initial routing attempts on the cheapest possible path. We provide an empirical evidence that routing fees should be dropped for proactive rebalancing operations. Executing 4 different strategies for selecting rebalancing cycles lead to similar results indicating that a collaborative approach within the friend of a friend network might be preferable from a practical point of view

Includes members:
  Member "boomerang redundancy improves latency and throughput in payment networks":
    also connected through other hyperedges:
      (none)
  Member "ant routing algorithm for the lightning network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hushrelay a privacy preserving efficient and scalable routing algorithm for off chain payments")
  Member "routing cryptocurrency with the spider network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hushrelay a privacy preserving efficient and scalable routing algorithm for off chain payments")
  Member "high throughput cryptocurrency routing in payment channel networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the strength of connectivity of inhomogeneous random k out graphs")

Question: Please tell me which class the source paper 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.SI(Social and Information Networks)