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 "genomics as a service a joint computing and networking perspective"):
  Abstract: Abstract   This paper shows a global picture of the deployment of networked processing services for genomic data sets. Many current research and medical activities make an extensive use of genomic data, which are massive and rapidly increasing over time. They are typically stored in remote databases, accessible by using Internet connections. For this reason, the quality of the available network services could be a significant issue for effectively handling genomic data through networks. A first contribution of this paper consists in identifying the still unexploited features of genomic data that could allow optimizing their networked management. The second and main contribution is a methodological classification of computing and networking alternatives, which can be used to deploy what we call the Genomics-as-a-Service (GaaS) paradigm. In more detail, we analyze the main genomic processing applications, and classify both the computing alternatives to run genomics workflows, in either a local machine or a distributed cloud environment, and the main software technologies available to develop genomic processing services. Since an analysis encompassing only the computing aspects would provide only a partial view of the issues for deploying GaaS systems, we present also the main networking technologies that are available to efficiently support a GaaS solution. We first focus on existing service platforms, and analyze them in terms of service features, such as scalability, flexibility, and efficiency. Then, we present a taxonomy for both wide area and datacenter network technologies that may fit the GaaS requirements. It emerges that virtualization, both in computing and networking, is the key for a successful large-scale exploitation of genomic data, by pushing ahead the adoption of the GaaS paradigm. Finally, the paper illustrates a short and long-term vision on future research challenges in the field.

Includes members:
  Member "network slicing for 5g with sdn nfv concepts architectures and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "sdxvpn a software defined solution for vpn service providers":
    also connected through other hyperedges:
      (none)
  Member "efficient image deployment in cloud environments":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an efficient cloud scheduler design supporting preemptible instances")
  Member "a signaling protocol for service function localization":
    also connected through other hyperedges:
      (none)
  Member "predicting the popularity of online content":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "online convex optimization for caching 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.DC(Distributed, Parallel, and Cluster Computing)