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 "statistical guarantee optimization for aoi in single hop and two hop systems with periodic arrivals"):
  Abstract: Age of Information (AoI) has proven to be a useful metric in networked systems where timely information updates are of importance. In the literature, minimizing "average age" has received considerable attention. However, various applications pose stricter age requirements on the updates which demand knowledge of the AoI distribution. Furthermore, the analysis of AoI distribution in a multi-hop setting, which is important for the study of Wireless Networked Control Systems (WNCS), has not been addressed before. Toward this end, we study the distribution of AoI in a WNCS with two hops and devise a problem of minimizing the tail of the AoI distribution with respect to the frequency of generating information updates, i.e., the sampling rate of monitoring a process, under first-come-first-serve (FCFS) queuing discipline. We argue that computing an exact expression for the AoI distribution may not always be feasible; therefore, we opt for computing upper bounds on the tail of the AoI distribution. Using these upper bounds we formulate Upper Bound Minimization Problems (UBMP), namely, Chernoff-UBMP and alpha-relaxed Upper BoundMinimization Problem (alpha-UBMP), where alpha > 1 is an approximation factor, and solve them to obtain "good" heuristic rate solutions. We demonstrate the efficacy of our approach by solving the proposed UBMPs for three service distributions: geometric, exponential, and Erlang. Simulation results show that the rate solutions obtained are near-optimal for minimizing the tail of the AoI distribution for the considered distributions.

Includes members:
  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-1 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "optimal status updating with a finite battery energy harvesting source":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimized age of information tail for ultra reliable low latency communications in vehicular networks")
  Member "on the distribution of aoi for the gi gi 1 1 and gi gi 1 2 systems exact expressions and bounds":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "non linear age of information in a discrete time queue stationary distribution and average performance analysis")
  Member "age of information in g g 1 1 systems age expressions bounds special cases and optimization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "who should google scholar update more often")
  Member "status updates through m g 1 1 queues with harq":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "who should google scholar update more often")
  Member "age optimal information updates in multihop networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "update or wait how to keep your data fresh":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "who should google scholar update more often")
  Member "age of information in the presence of error":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")

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)