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 "optimal age energy trade off via sleep wake scheduling"):
  Abstract: The problem of controlling and analyzing information updates has received significant recent attention. In particular, the past few years have seen a dramatic increase in the design of age-based multi-source scheduling policies. However, many information generating nodes are often battery operated where the lifetime of the network is a critical element. Thus, an important open question is how to minimize the age of information (AoI) in such energy constrained networks? #R##N#In this work, we address this question by leveraging carrier sensing in order to allow information sources to sleep when they are not transmitting, thereby saving precious battery power, and elongating the lifetime of the sources. Thus, a source sleeps if it senses that the channel is busy, or upon completing a packet transmission. The introduction of sleep periods, however, increases the AoI. Thus, we design sleeping periods to minimize the total weighted average peak age, while simultaneously meeting a per-source energy constraint. #R##N#The problem of minimizing the cumulative age of sources under energy constraints is a hard non-convex optimization problem. However, when the carrier sensing time is negligible compared to the packet transmission time, we are able to provide a near-optimal solution. Moreover, we represent our solution in a simple form that allows us to design a simple-to-implement algorithm to obtain its value. Finally, we show that the performance of our proposed algorithm is asymptotically no worse than the optimal synchronized scheduler.

Includes members:
  Member "fundamental limits of many user mac with finite payloads and fading":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "broadcast age of information in csma ca based wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "age of information for multicast transmission with fixed and random deadlines in iot systems")
  Member "energy efficient coded random access for the wireless uplink":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "massive access for future wireless communication systems")
  Member "minimizing the age of information in a csma environment":
    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 "timely status update in massive iot systems decentralized scheduling for wireless uplinks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the optimality of the whittle s index policy for minimizing the age of information")
  Member "sampling for data freshness optimization non linear age functions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "urgency of information for context aware timely status updates in remote control systems")
  Member "optimizing information freshness in wireless networks under general interference constraints":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")
  Member "optimizing age of information in wireless networks with perfect channel state information":
    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)