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 "virtual machine migration a resource intensive outsourcing mechanism for mobile cloud computing"):
  Abstract: In Mobile Cloud Computing (MCC), Virtual Machine (VM) migration based process offloading is a dominant approach to enhance Smart Mobile Devices (SMDs). A challenging aspect of VM deployment is the additional computing resources usage in the deployment and management of VM which obliges computing resources for VM creation and configuration. The management of VM comprises computing resources exploitation in the monitoring of VM in entire lifecycle and physical resources management for VM on SMDs. Therefore, VM migration based application offloading requires additional computing resource. Consequently computing resources demand and execution time of the application increases respectively. In this paper, we empirically review the impact of VM deployment and management on the execution time of application in diverse scenarios. We investigate VM deployment and management for application processing in simulation environment by employing CloudSim: a simulation toolkit that provides an extensible simulation framework to model VM deployment and management for application processing in cloud infrastructure. The significance of this work is to ensure that VM deployment and management necessitates additional computing resources on SMD for application offloading. We evaluate VM deployment and management in application processing by analyzing Key Performance Parameters (KPPs) in different scenarios; such as VM deployment, the execution time of applications, and total execution time of the simulation. We use KPPs to assess deviations in the results of diverse experimental scenarios. The empirical analysis concludes that VM deployment and management oblige additional resources on computing host which make it a heavyweight approach for process offloading on smart mobile device.

Includes members:
  Member "mobile cloud computing a review on smartphone augmentation approaches":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cloud based augmentation for mobile devices motivation taxonomies and open challenges")
  Member "tripod of requirements in horizontal heterogeneous mobile cloud computing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cloud based augmentation for mobile devices motivation taxonomies and open 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.DC(Distributed, Parallel, and Cluster Computing)