Alouane - Architecte DOCKER
Ref : 211202N002-
Domicile
10000 RABAT (Maroc)
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Profil
Architecte, DevOps, Développeur (34 ans)
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MobilitéTélétravail uniquement
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StatutPas immatriculé
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Tarif Journalier MoyenVoir le tarif
EDUCATION
Master degree in Software engineering
Ibn tofail university – Kénitra – Morocco
June 2013
LINKS
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********-alouane
PUBLICATIONS
Online multi-instance acquisition for cost optimization in IaaS Clouds
********/ April 2016
Abstract - Amazon Ec2 service offers two diverse instance purchasing options. Users can either run instances by
using on-demand plan and pay only for the incurred instance-hours, or by renting instances for a long period,
while taking advantage of significant reductions (up to 60%). One of the major problems facing these users is cost
management. How to dynamically combine between these two options, to serve sporadic workload, without
knowledge of future demands? Many strategies in the literature, require either using exact historic workload as a
reference or relying on long-term predictions of future workload. Unlike existing works, we propose two practical
online deterministic algorithms for the multi-slope case, that incur no more than 1+1/1- and 2/1-α respectively,
compared to the cost obtained from an optimal offline algorithm, where α is the maximum saving ratio of a
reserved instance offer over on-demand plan.
A thick-cloud solution for data auditing in a cloud environment
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May 2016
Abstract - Protecting and auditing data is not an easy task, especially when it comes to cloud storage. As such, it is
essential to design an efficient data auditing scheme along with a recovery process while controlling the cloud fees,
in the literature, many works has been devoted to cloud storage security, but the majority did not consider the
cloud fees into account or provide a cost analysis of their solutions. Therefore, they cannot be deployed in a real
cloud environment. For this reason, we introduce a new regenerating code-based model for cloud data integrity
protection that can surely conduct data auditing operation with the minimum cost possible. We also give some
insights about some new threat models like data tracking problem, which can cause the total loss of customer's
data, and data loss insurance problem. The global evaluation of our model shows that our solution can save the
total cost incurred by data check operation when using on-demand instances by 16%, and up to 40% when using
reserved instance plan. While it incurs additional cost no more than 4% when triggering a repair operation for
different parameters.
How can we design a cost-effective model that ensures a high level of data integrity protection?
********/ May 2015
Abstract - Everyone agree that data is more secured locally than when it is outsourced far away from their owners.
But the growth of local data annually implies extra charges for the customers, which makes their business slowing
down. Cloud computing paradigm comes with new technologies that offer a very economic and cost-effective
solutions, but at the expense of security. So, designing a lightweight system that can achieve a balance between cost
and data security is really important. Several schemes and techniques have been proposed for securing, checking
and repairing data, but unfortunately the majority doesn't respect and preserve the cost efficiency and profitability
of cloud offers. In this paper we try to answer the question: how can we design a model that enables a high level of
integrity check while preserving a minimum cost? We try also to analyse a new threat model regards the tracking
of a file's fragments during a repair or a download operation, which can cause the total loss of customers data. The
solution given in this paper is based on redistributing fragments locations after every data operation using a set of
random values generated by a chaotic map. Finally, we provide a data loss insurance (data corruption as well)
approach based on user estimation of data importance level that helps in reducing user concerns about data loss.
Virtual Machines Online Acquisition
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June 2018
Abstract - Clouds basically offer a set of instance acquisition solutions, it’s either an on-demand plan where the
user has to pay the full VM hourly pricing or can go with a commitment for a X duration, then the user can benefit
from a Y percent of reduction over the total VM reservation period. That point of shifting or decision making
becomes more difficult during the last couple years, with this big number of service reservation offers with various
duration that we have on the market today and knowing the fact that not all workloads are easy to predict, it forces
the user to think about an optimal combination of these offers, while maintaining the same availability level,
consistency and latency of the on-demand solution. In this paper, we introduce two deterministic algorithms for
the multi-slope case, that incur no more than 1 + 1/1−α and 2/1−α respectively, compared to the cost obtained from
an optimal offline algorithm, where α is the maximum saving ratio of a reserved instance offer over on-demand
plan. Our simulation driven by the google cluster usage data-trace shows that more than 30% of cost savings can
be achieved when applied to a real cloud provider like amazon web services, while 40% when purchasing instances through a cloud broker service.
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