Cloud services emerged to provide easy and affordable access to computing resources over the Internet and doing so eliminated the need for managing the complex in-house IT environment. Data centers consume a significa...
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ISBN:
(纸本)9798350342154
Cloud services emerged to provide easy and affordable access to computing resources over the Internet and doing so eliminated the need for managing the complex in-house IT environment. Data centers consume a significant amount of power. According to a report, in 2020 the data center (DC) industry consumed around 196 to 400 terawatt-hours. In half a decade, the projected data center power consumption usage is going to be around 33% of total global electricity consumption which may be 20% of the entire energy consumed around the world. Cloud service spends a significant portion of its operational expense toward electricity usage. Therefore, efficient utilization of electricity in the DC sites is essential to reduce costs, energy consumption, carbon emissions and environmental impact for a sustainable cloud service which hinges heavily on efficient use of power consumed by the cooling system and the servers at different data centers in the cloud. The proposed system AYPOS, optimizes the Power Usage Effectiveness (PUE) of the overall cloud infrastructure by dynamically changing the virtual machine (VM) topology (by moving clusters of VMs within or across DC sites) to de-activate unnecessary IT components and thereby lowering cooling power utilization and tuning the DC Information Management (DCIM) in a cross-domain manner. The interrelations between the power consumed by the cooling system (aka the passive system) and that of IT components (aka active system) in each site must be properly modeled to predict and control data center power efficiency. One of the tools recently emerged for efficient operation of data centers is 'virtualization' that encompasses a wide array of technologies that creates slices of the physical computing, storage and networking that can be easily moved around and software-reconfigured. A virtual machine (VM) which is a partition of a physical computer that has all the functions of a server including its own operating system, improves the effic
Healthcare is a global pillar, with a surge in the adoption of information technology, particularly in hospital information systems (HIS). However, global protocols are needed to meet the growing demand for data inter...
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Silicon Physical Unclonable Functions (PUFs) generate challenge-response pairs that are unique to each die, allowing for secure identification, authentication and cryptographic keys generation. However, designing and ...
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Modern neural network models consume a large proportion of power in matrix-vector multiplications. At inference time, the trained network parameters are constant and organized in matrices. Knowing the constant matrice...
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ISBN:
(数字)9798350387179
ISBN:
(纸本)9798350387186
Modern neural network models consume a large proportion of power in matrix-vector multiplications. At inference time, the trained network parameters are constant and organized in matrices. Knowing the constant matrices in advance can significantly benefit hardware utilization, throughput and energy consumption of neural network implementations. This paper seeks to achieve hardware optimizations and reduce the computational cost of constant matrix multiplication by exploiting redundancies in sub-expressions common to several products and outputs. For FPGA implementation, our results show that the number of lookup tables can be decreased by up to 62% compared to a standard baseline version already optimized by vendor tools.
Proactive protection of software systems can be achieved through Moving Target Defense (MTD) techniques, which are designed based on addressing the questions of what to move, how to move, and when to move. However, th...
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Recently, machine learning (ML) has become very successful, which has triggered significant developments in the field of artificial intelligence (AI) and significant improvements in the predictive performance of ML al...
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As a result of industrial developments and revolutions, the importance of data has increased. The reflection of this increasing importance in process mining is the importance of scope expansion with perspective data c...
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Exploration in unknown and unstructured environments is a pivotal requirement for robotic applications. A robot’s exploration behavior can be inherently affected by the performance of its Simultaneous Localization an...
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The global surge in smartphone use and mobile applications has created a demand for skilled mobile program-mers. However, the complexity of Android programming poses challenges for teachers that underscore the need fo...
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Early and accurate segmentation of oral cancer is essential for timely diagnosis and treatment. Traditional methods like visual inspections and biopsies are often subjective and costly, which can hinder early detectio...
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