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 "analysis on computation intensive status update in mobile edge computing"):
  Abstract: In status update scenarios, the freshness of information is measured in terms of age-of-information (AoI), which essentially reflects the timeliness for real-time applications to transmit status update messages to a remote controller. For some applications, computational expensive and time consuming data processing is inevitable for status information of messages to be displayed. Mobile edge servers are equipped with adequate computation resources and they are placed close to users. Thus, mobile edge computing (MEC) can be a promising technology to reduce AoI for computation-intensive messages. In this paper, we study the AoI for computation-intensive messages with MEC, and consider three computing schemes: local computing, remote computing at the MEC server, and partial computing, i.e., some part of computing tasks are performed locally, and the rest is executed at the MEC server. Zero-wait policy is adopted in all three schemes. Specifically, in local computing, a new message is generated immediately after the previous one is revealed by computing. While in remote computing and partial computing, a new message is generated once the previous one is received by the remote MEC server. With infinite queue size and exponentially distributed transmission time, closed-form average AoI for exponentially distributed computing time is derived for the three computing schemes. For deterministic computing time, the average AoI is analyzed numerically. Simulation results show that by carefully partitioning the computing tasks, the average AoI in partial computing is the smallest compared to local computing and remote computing. The results also indicate numerically the conditions on which remote computing attains smaller average AoI compared with local computing.

Includes members:
  Member "trading off computation with transmission in status update systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "who should google scholar update more often")
  Member "age of information for computation intensive messages in mobile edge computing":
    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 "timely cloud computing preemption and waiting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "who should google scholar update more often")
  Member "age of information in a network of preemptive servers":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "non linear age of information in a discrete time queue stationary distribution and average performance analysis")
  Member "the age of information in networks moments distributions and sampling":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "joint status sampling and updating for minimizing age of information in the internet of things":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "age of information with gilbert elliot servers and samplers")
  Member "joint information freshness and completion time optimization for vehicular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "timely status updating through intermittent sensing and transmission")
  Member "a survey on mobile edge computing the communication perspective":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")

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)