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 "alvec auto scaling by lotka volterra elastic cloud a qos aware non linear dynamical allocation model"):
  Abstract: Elasticity in resource allocation is still a relevant problem in cloud computing. There are many academic and white papers which have investigated the problem and offered solutions.\textbf{Unfortunately, there are scant evidence of determining scaling number dynamically.} Elasticity is defined as the ability to adapt with the changing workloads by provisioning and de-provisioning Cloud resources. We propose ALVEC, a novel model of resource allocation in Cloud data centers, inspired by population dynamics and Mathematical Biology, which addresses dynamic allocation by auto-tuning model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better in Service level agreement (SLA) management and Quality of Services (QoS). We show evidence of true elasticity, in theory and empirical comparisons. Additionally, ALVEC is able to predict the future load and allocate VM's accordingly. The proposed model, ALVEC is the first example of unsupervised resource allocation scheme.

Includes members:
  Member "sustainable cloud computing foundations and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "transformative effects of iot blockchain and artificial intelligence on cloud computing evolution vision trends and open challenges")
  Member "a comparison of reinforcement learning techniques for fuzzy cloud auto scaling":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reinforcement learning based autoscaling of workflows in the cloud a survey")
  Member "qos guaranteed intelligent routing using hybrid pso ga in wireless mesh networks":
    also connected through other hyperedges:
      (none)
  Member "scads scale independent storage for social computing applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the case for learned index structures")

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.NI(Networking and Internet Architecture)