Correlated Resource Models of Internet End Hosts - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Reports (Research Report) Year : 2010

Correlated Resource Models of Internet End Hosts

Eric M. Heien
  • Function : Author
  • PersonId : 883116
Derrick Kondo
  • Function : Author
  • PersonId : 849131
David Anderson
  • Function : Author
  • PersonId : 883117

Abstract

Understanding and modelling resources of Internet end hosts is essential for the design of desktop software and Internet-distributed applications. In this paper we develop a correlated resource model of Internet end hosts based on real trace data taken from the SETI@home project. This data covers a 5-year period with statistics for 2.7 million hosts. The resource model is based on statistical analysis of host computational power, memory, and storage as well as how these resources change over time and the correlations between them. We find that resources with few discrete values (core count, memory) are well modeled by exponential laws governing the change of relative resource quantities over time. Resources with a continuous range of values are well modeled with either correlated normal distributions (processor speed for integer operations and floating point operations) or log-normal distributions (available disk space). We validate and show the utility of the models by applying them to a resource allocation problem for Internet-distributed applications, and demonstrate their value over other models. We also make our trace data and tool for automatically generating realistic Internet end hosts publicly available.
Fichier principal
Vignette du fichier
model_synth.pdf (375.73 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

inria-00538932 , version 1 (24-11-2010)

Identifiers

  • HAL Id : inria-00538932 , version 1
  • ARXIV : 1011.5568

Cite

Eric M. Heien, Derrick Kondo, David Anderson. Correlated Resource Models of Internet End Hosts. [Research Report] 2010. ⟨inria-00538932⟩
254 View
540 Download

Altmetric

Share

Gmail Facebook X LinkedIn More