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 "broadcast in radio networks time vs energy tradeoffs"):
  Abstract: In wireless networks, consisting of battery-powered devices, energy is a costly resource and most of it is spent on transmitting and receiving messages. Broadcast is a problem where a message needs to be transmitted from one node to all other nodes of the network. We study algorithms that can work under limited energy measured as the maximum number of transmissions by a single station. The goal of the paper is to study tradeoffs between time and energy complexity of broadcast problem in multi-hop radio networks. We consider a model where the topology of the network is unknown and if two neighbors of a station are transmitting in the same discrete time slot, then the signals collide and the receiver cannot distinguish the collided signals from silence. #R##N#We observe that existing, time efficient, algorithms are not optimized with respect to energy expenditure. We then propose and analyse two new randomized energy-efficient algorithms. Our first algorithm works in time $O((D+\varphi)\cdot n^{1/\varphi}\cdot \varphi)$ with high probability and uses $O(\varphi)$ energy per station for any $\varphi \leq \log n/(2\log\log n)$ for any graph with $n$ nodes and diameter $D$. Our second algorithm works in time $O((D+\log n)\log n)$ with high probability and uses $O(\log n/\log\log n)$ energy. #R##N#We prove that our algorithms are almost time-optimal for given energy limits for graphs with constant diameters by constructing lower bound on time of $\Omega(n^{1/\varphi} \cdot \varphi)$. The lower bound shows also that any algorithm working in polylogaritmic time in $n$ for all graphs needs energy $\Omega(\log n/\log\log n)$.

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 "fully dynamic connectivity in o log n log log n 2 amortized expected time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond")
  Member "exponential separations in the energy complexity of leader election":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-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)