Testbeds and Research Infrastructure: Development of Networks and Communities. 9th International ICST Conference, TridentCom 2014, Guangzhou, China, May 5-7, 2014, Revised Selected Papers

Research Article

The Tradeoff Between Single Aggregate and Multiple Aggregates in Designing GENI Experiments

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  • @INPROCEEDINGS{10.1007/978-3-319-13326-3_3,
        author={Zongming Fei and Ping Yi and Jianjun Yang},
        title={The Tradeoff Between Single Aggregate and Multiple Aggregates in Designing GENI Experiments},
        proceedings={Testbeds and Research Infrastructure: Development of Networks and Communities. 9th International ICST Conference, TridentCom 2014, Guangzhou, China, May 5-7, 2014, Revised Selected Papers},
        proceedings_a={TRIDENTCOM},
        year={2014},
        month={11},
        keywords={GENI Network testbed Network measurement Experiment design},
        doi={10.1007/978-3-319-13326-3_3}
    }
    
  • Zongming Fei
    Ping Yi
    Jianjun Yang
    Year: 2014
    The Tradeoff Between Single Aggregate and Multiple Aggregates in Designing GENI Experiments
    TRIDENTCOM
    Springer
    DOI: 10.1007/978-3-319-13326-3_3
Zongming Fei1,*, Ping Yi1,*, Jianjun Yang2,*
  • 1: University of Kentucky
  • 2: University of North Georgia
*Contact email: fei@netlab.uky.edu, yiping@netlab.uky.edu, jianjun.yang@ung.edu

Abstract

The Global Environment for Network Innovations (GENI) provides a virtual laboratory for exploring future internets at scale. It consists of many geographically distributed aggregates for providing computing and networking resources for setting up network experiments. A key design question for GENI experimenters is where they should reserve the resources, and in particular whether they should reserve the resources from a single aggregate or from multiple aggregates. This not only depends on the nature of the experiment, but needs a better understanding of underlying GENI networks as well. This paper studies the performance of GENI networks, with a focus on the tradeoff between single aggregate and multiple aggregates in the design of GENI experiments from the performance perspective. The analysis of data collected will shed light on the decision process for designing GENI experiments.