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 "optimizing information freshness through computation transmission tradeoff and queue management in edge computing"):
  Abstract: Edge computing applications typically require generated data to be preprocessed at the source and then transmitted to an edge server. In such cases, transmission time and preprocessing time are coupled, yielding a tradeoff between them to achieve the targeted objective. This paper presents analysis of such a system with the objective of optimizing freshness of received data at the edge server. We model this system as two queues in tandem whose service times are independent over time but the transmission service time is monotonically dependent on the computation service time in mean value. This dependence captures the natural decrease in transmission time due to lower offloaded computation. We analyze various queue management schemes in this tandem queue where the first queue has a single server, Poisson packet arrivals, general independent service and no extra buffer to save incoming status update packets. The second queue has a single server receiving packets from the first queue and service is memoryless. We consider the second queue in two forms: (i) No data buffer and (ii) One unit data buffer and last come first serve with discarding. We analyze various non-preemptive as well as preemptive cases. We perform stationary distribution analysis and obtain closed form expressions for average age of information (AoI) and average peak AoI. Our numerical results illustrate analytical findings on how computation and transmission times could be traded off to optimize AoI and reveal a consequent tradeoff between average AoI and average peak AoI.

Includes members:
  Member "optimizing information freshness in computing enabled iot networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "timely status updating through intermittent sensing and transmission")
  Member "a general formula for the stationary distribution of the age of information and its application to single server queues":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "trading off computation with transmission in status update systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "who should google scholar update more often")
  Member "waiting before serving a companion to packet management in status update systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the optimality of the whittle s index policy for minimizing the age of information")
  Member "reducing age of information for computation intensive messages via packet replacement":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "who should google scholar update more often")
  Member "relative age of information a new metric for status update systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "trading off computation with transmission in status update systems")
  Member "the age of information in networks moments distributions and sampling":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "can determinacy minimize age of information":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "timely status updating through intermittent sensing and transmission")

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)