Δημοσιεύσεις

Project Acronym: ScaleSciCompIII
Title: Scientific Computing and Large Scale Simulation
Affiliation: democritus university of thrace
Pi: George Gravvanis
Research Field: mathematics and computer sciences

Towards simulation and optimization of cache placement on large virtual content distribution networks
by Christos K. Filelis-Papadopoulos, Patricia Takako Endo, Malika Bendechache, Sergej Svorobej, Konstantinos M. Giannoutakis, George A. Gravvanis, Dimitrios Tzovaras, James Byrne and Theo Lynn
Abstract:
IP video traffic is forecast to be 82% of all IP traffic by 2022. Traditionally, content distribution networks (CDN) were used extensively to meet quality of service levels for IP video services. To handle the dramatic growth in video traffic, CDN operators are migrating their infrastructure to the cloud and fog in order to leverage its greater availability and flexibility. For hyperscale deployments, energy consumption, cache placement, and resource availability can be analyzed using simulation in order to improve resource utilization and performance. Recently, a discrete-time simulator for modelling hierarchical virtual CDNs (vCDNs) was proposed with reduced memory requirements and increased performance using multi-core systems to cater for the scale and complexity of these networks. The first iteration of this discrete-time simulator featured a number of limitations impacting accuracy and applicability: it supports only tree-based topology structures, the results are computed per level, and requests of the same content differ only in time duration. In this paper, we present an improved simulation framework that (a) supports graph-based network topologies, (b) requests have been reconstituted for differentiation of requirements, and (c) statistics are now computed per site and network metrics per link, improving granularity and parallel performance. Moreover, we also propose a two phase optimization scheme that makes use of simulation outputs to guide the search for optimal cache placements. In order to evaluate our proposal, we simulate a vCDN network based on real traces obtained from the BT vCDN infrastructure, and analyze performance and scalability aspects.
Reference:
Towards simulation and optimization of cache placement on large virtual content distribution networks (Christos K. Filelis-Papadopoulos, Patricia Takako Endo, Malika Bendechache, Sergej Svorobej, Konstantinos M. Giannoutakis, George A. Gravvanis, Dimitrios Tzovaras, James Byrne and Theo Lynn), In Journal of Computational Science, volume 39, 2020.
Bibtex Entry:
@article{FILELISPAPADOPOULOS2020101052,
 title = {Towards simulation and optimization of cache placement on large virtual content distribution networks},
 journal = {Journal of Computational Science},
 volume = {39},
 pages = {101052},
 year = {2020},
 bibyear = {2020},
 issn = {1877-7503},
 doi = {10.1016/j.jocs.2019.101052},
 url = {http://www.sciencedirect.com/science/article/pii/S1877750319302406},
 author = {Christos K. Filelis-Papadopoulos and Patricia Takako Endo and Malika Bendechache and Sergej Svorobej and Konstantinos M. Giannoutakis and George A. Gravvanis and Dimitrios Tzovaras and James Byrne and Theo Lynn},
 abstract = {IP video traffic is forecast to be 82% of all IP traffic by 2022. Traditionally, content distribution networks (CDN) were used extensively to meet quality of service levels for IP video services. To handle the dramatic growth in video traffic, CDN operators are migrating their infrastructure to the cloud and fog in order to leverage its greater availability and flexibility. For hyperscale deployments, energy consumption, cache placement, and resource availability can be analyzed using simulation in order to improve resource utilization and performance. Recently, a discrete-time simulator for modelling hierarchical virtual CDNs (vCDNs) was proposed with reduced memory requirements and increased performance using multi-core systems to cater for the scale and complexity of these networks. The first iteration of this discrete-time simulator featured a number of limitations impacting accuracy and applicability: it supports only tree-based topology structures, the results are computed per level, and requests of the same content differ only in time duration. In this paper, we present an improved simulation framework that (a) supports graph-based network topologies, (b) requests have been reconstituted for differentiation of requirements, and (c) statistics are now computed per site and network metrics per link, improving granularity and parallel performance. Moreover, we also propose a two phase optimization scheme that makes use of simulation outputs to guide the search for optimal cache placements. In order to evaluate our proposal, we simulate a vCDN network based on real traces obtained from the BT vCDN infrastructure, and analyze performance and scalability aspects.},
}