Snapshot Provisioning of Cloud Application Stacks to Face Traffic Surges

Traffic surges, like the Slashdot effect, occur when a web application is overloaded by a huge number of requests, potentially leading to unavailability. Unfortunately, such traffic variations are generally totally unplanned, of great amplitude, within a very short period, and a variable delay to return to a normal regime. In this report, we introduce PeakForecast as an elastic middleware solution to detect and absorb a traffic surge. In particular, PeakForecast can, from a trace of queries received in the last seconds, minutes or hours, to detect if the underlying system is facing a traffic surge or not, and then estimate the future traffic using a forecast model with an acceptable precision, thereby calculating the number of resources required to absorb the remaining traffic to come. We validate our solution by experimental results demonstrating that it can provide instantaneous elasticity of resources for traffic surges observed on the Japanese version of Wikipedia during the Fukushima Daiichi nuclear disaster in March 2011.

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Source https://inria.hal.science/hal-00820959
Author Pewo Fouomene, Daniel, Rouvoy, Romain, Seinturier, Lionel
Maintainer CCSD
Last Updated May 11, 2026, 04:59 (UTC)
Created May 11, 2026, 04:59 (UTC)
Identifier Report N°: RR-8299
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Adaptive Distributed Applications and Middleware (ADAM) ; Laboratoire d'Informatique Fondamentale de Lille (LIFL) ; Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de l'Université de Lille ; Institut National de Recherche en Informatique et en Automatique (Inria)
creator Pewo Fouomene, Daniel
date 2013-05-07T00:00:00
harvest_object_id 0ad0f562-3049-4876-9f54-d9e585141c90
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-02-26T00:00:00
set_spec type:REPORT