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 "fast and resource competitive broadcast in multi channel radio networks"):
  Abstract: Consider a single-hop, multi-channel, synchronous radio network in which a source node needs to disseminate a message to all other $n-1$ nodes. An adversary called Eve, which captures environmental noise and potentially malicious interference, aims to disrupt this process via jamming. Assume sending, listening, or jamming on one channel for one time slot costs unit energy. The question is, if Eve spends $T$ units of energy on jamming, can we devise broadcast algorithms in which each node's cost is $o(T)$? Previous results show such resource competitive algorithms do exist in the single-channel setting: each node can receive the message within $\tilde{O}(T+n)$ time slots while spending only $\tilde{O}(\sqrt{T/n}+1)$ energy. #R##N#In this paper, we show that when Eve is oblivious, the existence of multiple channels allows even faster message dissemination, while preserving resource competitiveness. Specifically, we have identified an efficient "epidemic broadcast" scheme in the multi-channel setting that is robust again jamming. Extending this scheme leads to a randomized algorithm called MultiCast which uses $n/2$ channels, and accomplishes broadcast in $\tilde{O}(T/n+1)$ time slots while costing each node only $\tilde{O}(\sqrt{T/n}+1)$ energy. When the value of $n$ is unknown, we further propose MultiCastAdv, in which each node's running time is $\tilde{O}(T/(n^{1-2\alpha})+n^{2\alpha})$, and each node's cost is $\tilde{O}(\sqrt{T/(n^{1-2\alpha})}+n^{2\alpha})$. Here, $0<\alpha<1/4$ is a tunable parameter affecting the constant hiding behind the big-$O$ notation. #R##N#To handle the issue of limited channel availability, we have also devised variants for both MultiCast and MultiCastAdv that can work in networks in which only $C$ channels are available, for any $C\geq 1$. These variants remain to be resource competitive, and have (near) optimal time complexity in many cases.

Includes members:
  Member "the energy complexity of broadcast":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "competitive broadcast against adaptive adversary in multi channel radio networks")
  Member "exploiting spontaneous transmissions for broadcasting and leader election in radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "competitive broadcast against adaptive adversary in multi channel radio networks")
  Member "randomized broadcast in radio networks with collision detection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "competitive broadcast against adaptive adversary in multi channel radio networks")
  Member "making evildoers pay resource competitive broadcast in sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "competitive broadcast against adaptive adversary in multi channel radio networks")
  Member "a resource competitive jamming defense":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "competitive broadcast against adaptive adversary in multi channel radio networks")

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.DC(Distributed, Parallel, and Cluster Computing)