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 "exploring microservices for enhancing internet qos"):
  Abstract: With the enhancements in the field of software-defined networking and virtualization technologies, novel networking paradigms such as network function virtualization (NFV) and the Internet of things (IoT) are rapidly gaining ground. Development of IoT as well as 5G networks and explosion in online services has resulted in an exponential growth of devices connected to the network. As a result, application service providers (ASPs) and Internet service providers (ISPs) are being confronted with the unprecedented challenge of accommodating increasing service and traffic demands from the geographically distributed users. To tackle this problem, many ASPs and ISPs, such as Netflix, Facebook, AT&T and others are increasingly adopting micro-services (MS) application architecture. Despite the success of MS in the industry, there is no specific standard or research work for service providers as guidelines, especially from the perspective of basic micro-service operations. In this work, we aim to bridge this gap between industry and academia and discuss different micro-service deployment, discovery and communication options for service providers as a means to forming complete service chains. In addition, we address the problem of scheduling micro-services across multiple clouds, including micro-clouds. We consider different user-level SLAs, such as latency and cost, while scheduling such services. We aim to reduce overall turnaround time as well as costs for the deployment of complete end-to-end service. In this work, we present a novel affinity-based fair weighted scheduling heuristic to solve this problem. We also compare the results of proposed solution with standard greedy scheduling algorithms presented in the literature and observe significant improvements.

Includes members:
  Member "optimal virtual network function placement in multi cloud service function chaining architecture":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cybersecurity for industrial control systems a survey")
  Member "an nfv and microservice based architecture for on the fly component provisioning in content delivery networks":
    also connected through other hyperedges:
      (none)
  Member "about microservices containers and their underestimated impact on network performance":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on representing and eliciting resilience requirements of microservice architecture systems")
  Member "circuit breakers discovery and api gateways in microservices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on representing and eliciting resilience requirements of microservice architecture systems")
  Member "virtual machine placement literature review":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on the use of preferences for virtual machine placement in cloud data centers")
  Member "migrating to cloud native architectures using microservices an experience report":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "open source rans in practice an over the air deployment for 5g mec")
  Member "specifying and placing chains of virtual network functions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a virtual network customization framework for multicast services in nfv enabled core networks")

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)