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Data center power consumption is among the largest commodity expenditures for many organizations. Reduction of power used in cloud data centres with heterogeneous physical resources can be achieved through Virtual-Machine (VM) consolidation which reduces the number of Physical Machines (PMs) used, subject to Quality of Service (QoS) constraints. This paper provides an in-depth survey of the most recent...
This work presents a useful standard management tool called Broadband Condition Index (BCI), which measures WAN network condition. It is a functional indicator resulting from an analysis of different unrelated factors (such as current WAN architecture and number of users) to obtain an overview of WAN condition as a numerical value. The proposed BCI has been developed based on “knowledge-based” approach...
The required broadband for school and school board depends on curriculum delivery, the administrative and operational needs of the school and many other factors. These represent very different usage patterns, but both require a high level of reliability and performance. Therefore, there are no standards define what is the suitable broadband for the school and school board. This article is the first...
Technology becomes more and more involved in the learning process (specifically blending learning) of K-12 schools. The broadband requirements must be assessed for cost-effective and efficient (a reasonable download wait time) access to the Internet. With the arrival of videoconferencing, collaborative tools besides, social media, the amount of data incoming and outgoing based on students' activities...
In order to perform optimal Virtual Machine (VM) consolidation under QoS constraints based on energy consumption in Cloud Data Centres (CDCs) containing heterogeneous physical resources, one must build a framework that combines many subsystem algorithms, including prediction, selection, placement, etc. Several energy minimization strategies can be used in CDCs, but the most importantly is one in which...
This paper presents an Extreme Learning Machine (ELM) time series prediction strategy to estimate the current and voltage behaviour of an Electric Arc Furnace (EAF). The proposed ELM predictor is designed for both long and short term predictions of the v-i characteristics of an EAF. The proposed predictor is evaluated using two real sensors' outputs collected over different time periods with a rate...
Data centre prediction models can be used to forecast future loads for a given centre in terms of CPU, memory, VM requests, and other parameters. An effective and efficient model can not only be used to optimize resource allocation, but can also be used as part of a strategy to conserve energy, improve performance and increase profits for both clients and service providers. In this paper, we have...
In the cloud computing paradigm, Infrastructure-as-a-Service (IaaS) providers can provision virtualized hardware and resources to users, removing the need for users to own and operate these resources, which can lead to lower costs and improved performance. This paper gives a general description of most commonly used open source IaaS service platforms. It includes descriptions and comparisons of OpenNebula,...
Cloud service providers (CSPs) offer a utility computing service model in which users are expected to only pay for the resources that they use. However, a lack of common standards used by different cloud providers and the complexity of cloud resource distribution and orchestration often lead to an excess in resource pool allocation and overall inefficiencies. This complexity percolates throughout...
One of the most important applications of machine learning systems is the diagnosis of heart disease which affect the lives of millions of people. Patients suffering from heart disease have lot of independent factors such as age, sex, serum cholesterol, blood sugar, etc. in common which can be used very effectively for diagnosis. In this paper an Extreme Learning Machine (ELM) algorithm is used to...
Software Defined Networks (SDNs) are gaining success in modern IT. While using SDN, enterprises and the research sector have encountered many challenges related to security and exposed weaknesses in heavy load management systems. In this paper, three architectures are proposed which are designed to work with all existing OpenFlow, OpenStack and OpenDaylight platforms. These architectures improve the...
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