مجال
التميز
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تميز دراسي وبحثي
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البحوث المنشورة
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البحث (1):
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عنوان البحث:
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Energy-aware
cost prediction and pricing of virtual machines in cloud computing
environments
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رابط إلى البحث:
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Click
Here
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تاريخ النشر:
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09/11/2018
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موجز عن البحث:
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With
the increasing cost of electricity, Cloud providers consider energy
consumption as one of the major cost factors to be maintained within their
infrastructure. Consequently, various proactive and reactive management
mechanisms are used to efficiently manage the cloud resources and reduce the
energy consumption and cost. These mechanisms support energy-awareness at the
level of Physical Machines (PM) as well as Virtual Machines (VM) to make
corrective decisions. This paper introduces a novel Cloud system architecture
that facilitates an energy aware and efficient cloud operation methodology
and presents a cost prediction framework to estimate the total cost of VMs
based on their resource usage and power consumption. The evaluation on a
Cloud testbed show that the proposed energy-aware cost prediction framework
is capable of predicting the workload, power consumption and estimating total
cost of the VMs with good prediction accuracy for various Cloud application
workload patterns. Furthermore, a set of energy-based pricing schemes are
defined, intending to provide the necessary incentives to create an
energy-efficient and economically sustainable ecosystem. Further evaluation
results show that the adoption of energy-based pricing by cloud and
application providers creates additional economic value to both under
different market conditions.
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المؤتمرات العلمية:
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المؤتمر (1):
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عنوان المؤتمر:
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The
9th Saudi Student Conference
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تاريخ الإنعقاد:
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13-14 February
2016
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مكان
الإنعقاد:
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Birmingham, United Kingdom
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طبيعة المشاركة:
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Poster Presentation
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عنوان المشاركة:
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The
Relationship between Pricing, Profitability and Customer Satisfaction in
Cloud Computing
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ملخص المشاركة:
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Cloud
computing represents a paradigm of information technology with a promise to revolutionize
the traditional approach to delivery of information technology services.
Cloud computing as a business sector is still nascent and growing, yet it has
attracted the attention of many researchers. In this regard, the role of
cloud computing within the IT sector is significantly influenced by pricing
mechanisms. Thus, the uptake of cloud computing services is substantially
determined by the pricing mechanisms that are employed by different service
providers.
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المؤتمر (2):
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عنوان المؤتمر:
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32nd Annual UK
Performance Engineering Workshop
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تاريخ الإنعقاد:
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8-9
September 2016
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مكان
الإنعقاد:
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Bradford, United Kingdom
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طبيعة المشاركة:
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Paper Presentation
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عنوان المشاركة:
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Energy
Consumption-based Pricing Model for Cloud Computing
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ملخص المشاركة:
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Pricing
mechanisms that are employed by different service providers significantly
influence the role of cloud computing within the IT industry. The purpose of
this paper is to investigate how different pricing models influence the
energy consumption, performance and cost of cloud services. Therefore, we
propose a novel Energy-Aware Pricing Model that considers energy consumption
as a key parameter with respect to performance and cost. Experimental results
show that the implementation of the Energy- Aware Pricing Model achieves up
to 63.3% reduction of the total cost as compared to current pricing models
like those advertised by Rackspace.
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المؤتمر (3):
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عنوان المؤتمر:
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14th International
Conference on Economics of Grids, Clouds, Systems & Services
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تاريخ الإنعقاد:
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19-21
September 2017
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مكان
الإنعقاد:
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Biarritz-Anglet-Bayonne, France
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طبيعة المشاركة:
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Paper Presentation
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عنوان المشاركة:
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Towards
Virtual Machine Energy-Aware Cost Prediction in Clouds
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ملخص المشاركة:
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Pricing
mechanisms employed by different service providers significantly influence
the role of cloud computing within the IT industry. With the increasing cost
of electricity, Cloud providers consider power consumption as one of the
major cost factors to be maintained within their infrastructures.
Consequently, modelling a new pricing mechanism that allow Cloud providers to
determine the potential cost of resource usage and power consumption has
attracted the attention of many researchers. Furthermore, predicting the
future cost of Cloud services can help the service providers to offer the
suitable services to the customers that meet their requirements. This paper
introduces an Energy-Aware Cost Prediction Framework to estimate the total
cost of Virtual Machines (VMs) by considering the resource usage and power
consumption. The VMs’ workload is firstly predicted based on an
Autoregressive Integrated Moving Average (ARIMA) model. The power consumption
is then predicted using regression models. The comparison between the
predicted and actual results obtained in a real Cloud testbed shows that this
framework is capable of predicting the workload, power consumption and total
cost for different VMs with good prediction accuracy, e.g. with 0.06 absolute
percentage error for the predicted total cost of the VM.
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المؤتمر (4):
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عنوان المؤتمر:
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8th International Conference on Cloud Computing and Services
Science
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تاريخ الإنعقاد:
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19-21 March 2018
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مكان
الإنعقاد:
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Funchal,
Madeira, Portugal
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طبيعة المشاركة:
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Paper
Presentation
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عنوان المشاركة:
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Performance
and Energy-based Cost Prediction of Virtual Machines Live Migration in Clouds
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ملخص المشاركة:
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Virtual
Machines (VMs) live migration is one of the important approaches to improve
resource utilisation and support energy efficiency in Clouds. However, VMs
live migration leads to performance loss and additional costs due to
increased migration time and energy overhead. This paper introduces a
Performance and Energy-based Cost Prediction Framework to estimate the total cost
of VMs live migration by considering the resource usage and power
consumption, while maintaining the expected level of performance. A series of
experiments conducted on a Cloud testbed show that this framework is capable
of predicting the workload, power consumption and total cost for
heterogeneous VMs before and after live migration, with the possibility of
recovering the migration cost e.g. 28.48% for the predicted cost recovery of
the VM.
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المؤتمر (5):
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عنوان المؤتمر:
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The
Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
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تاريخ الإنعقاد:
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29-31 August 2018
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مكان
الإنعقاد:
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Prague,
Czech Republic
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طبيعة المشاركة:
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Paper
Presentation
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عنوان المشاركة:
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Performance
and Energy-based Cost Prediction of Virtual Machines Auto-Scaling in Clouds
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ملخص المشاركة:
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Virtual
Machines (VMs) auto-scaling is an important technique to provision additional
resource capacity in a Cloud environment. It allows the VMs to dynamically
increase or decrease the amount of resources as needed in order to meet
Quality of Service (QoS) requirements. However, the auto-scaling mechanism
can be time-consuming to initiate (e.g. in the order of a minute), which is
unacceptable for VMs that need to scale up/out during the computation,
besides additional costs due to the increase of the energy overhead. This
paper introduces a Performance and Energy-based Cost Prediction Framework to
estimate the total cost of VMs auto-scaling by considering the resource usage
and power consumption, while maintaining the expected level of performance. A
series of experiments conducted on a Cloud testbed show that this framework
is capable of predicting the auto-scaling workload, power consumption and
total cost for heterogeneous VMs, with a cost-saving of up to 25% for the
predicted total cost of VM self-configuration as compared to the current
approaches in literature.
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المؤتمر (6):
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عنوان المؤتمر:
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The Fifth
International Symposium on Innovation in Information and Communication
Technology (ISIICT 2018)
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تاريخ الإنعقاد:
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31 Oct – 1 Nov 2018
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مكان
الإنعقاد:
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Amman,
Jordan
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طبيعة المشاركة:
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Paper Presentation
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عنوان المشاركة:
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Energy-based
Cost Model of Virtual Machines in a Cloud Environment
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ملخص المشاركة:
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The cost
mechanisms employed by different service providers significantly influence
the role of cloud computing within the IT industry. With the increasing cost
of electricity, Cloud providers consider power consumption as one of the
major cost factors to be maintained within their infrastructures.
Consequently, modelling a new cost mechanism for Cloud services that can be
adjusted to the actual energy costs has attracted the attention of many
researchers. This paper introduces an Energy- based Cost Model that considers
energy consumption as a key parameter with respect to the actual resource
usage and the total cost of the Virtual Machines (VMs). A series of
experiments conducted on a Cloud testbed show that this model is capable of
estimating the actual cost for heterogeneous VMs based on their resource
usage with consideration of their energy consumption.
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الرابط:
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Click
Here
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