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 "task replication for deadline constrained vehicular cloud computing optimal policy performance analysis and implications on road traffic"):
  Abstract: In vehicular cloud computing (VCC) systems, the computational resources of moving vehicles are exploited and managed by infrastructures, e.g., roadside units, to provide computational services. The offloading of computational tasks and collection of results rely on successful transmissions between vehicles and infrastructures during encounters. In this paper, we investigate how to provide timely computational services in VCC systems. In particular, we seek to minimize the deadline violation probability given a set of tasks to be executed in vehicular clouds. Due to the uncertainty of vehicle movements, the task replication methodology is leveraged which allows one task to be executed by several vehicles, and thus trading computational resources for delay reduction. The optimal task replication policy is of key interest. We first formulate the problem as a finite-horizon sampled-time Markov decision problem and obtain the optimal policy by value iterations. To conquer the complexity issue, we propose the balanced-task-assignment (BETA) policy which is proved optimal and has a clear structure: it always assigns the task with the minimum number of replicas. Moreover, a tight closed-form performance upper bound for the BETA policy is derived, which indicates that the deadline violation probability follows the Rayleigh distribution approximately. Applying the vehicle speed-density relationship in the traffic flow theory, we find that vehicle mobility benefits VCC systems more compared with road traffic systems, by showing that the optimum vehicle speed to minimize the deadline violation probability is larger than the critical vehicle speed in traffic theory which maximizes traffic flow efficiency.

Includes members:
  Member "contrasting effects of replication in parallel systems from overload to underload and back":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "delay optimal policies in partial fork join systems with redundancy and random slowdowns")
  Member "energy efficient resource allocation for mobile edge computation offloading":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficient federated edge learning with joint communication and computation design")
  Member "provably delay efficient data retrieving in storage clouds":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "analyzing the download time of availability codes")
  Member "using straggler replication to reduce latency in large scale parallel computing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "codenet training large scale neural networks in presence of soft errors")
  Member "a high reliability asymptotic approach for packet inter delivery time optimization in cyber physical systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal age energy trade off via sleep wake scheduling")
  Member "when do redundant requests reduce latency":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "straggler resistant distributed matrix computation via coding theory")
  Member "on myopic sensing for multi channel opportunistic access structure optimality and performance":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deep learning based wireless resource allocation with application to vehicular networks")
  Member "femtocell networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "robust resource allocation for pd noma based miso heterogeneous networks with comp technology")

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.IT(Information Theory)