25,588 research outputs found
Computing server power modeling in a data center: survey,taxonomy and performance evaluation
Data centers are large scale, energy-hungry infrastructure serving the
increasing computational demands as the world is becoming more connected in
smart cities. The emergence of advanced technologies such as cloud-based
services, internet of things (IoT) and big data analytics has augmented the
growth of global data centers, leading to high energy consumption. This upsurge
in energy consumption of the data centers not only incurs the issue of surging
high cost (operational and maintenance) but also has an adverse effect on the
environment. Dynamic power management in a data center environment requires the
cognizance of the correlation between the system and hardware level performance
counters and the power consumption. Power consumption modeling exhibits this
correlation and is crucial in designing energy-efficient optimization
strategies based on resource utilization. Several works in power modeling are
proposed and used in the literature. However, these power models have been
evaluated using different benchmarking applications, power measurement
techniques and error calculation formula on different machines. In this work,
we present a taxonomy and evaluation of 24 software-based power models using a
unified environment, benchmarking applications, power measurement technique and
error formula, with the aim of achieving an objective comparison. We use
different servers architectures to assess the impact of heterogeneity on the
models' comparison. The performance analysis of these models is elaborated in
the paper
Configuration of Distributed Message Converter Systems using Performance Modeling
To find a configuration of a distributed system satisfying performance goals is a complex search problem that involves many design parameters, like hardware selection, job distribution and process configuration. Performance models are a powerful tools to analyse potential system configurations, however, their evaluation is expensive, such that only a limited number of possible configurations can be evaluated. In this paper we present a systematic method to find a satisfactory configuration with feasible effort, based on a two-step approach. First, using performance estimates a hardware configuration is determined and then the software configuration is incrementally optimized evaluating Layered Queueing Network models. We applied this method to the design of performant EDI converter systems in the financial domain, where increasing message volumes need to be handled due to the increasing importance of B2B interaction
Leveraging Monopoly Power by Degrading Interoperability: Theory and Evidence from Computer Markets
When will a monopolist have incentives to foreclose a complementary market by degrading compatibility/interoperability of his products with those of rivals? We develop a framework where leveraging extracts more rents from the monopoly market by "restoring" second degree price discrimination. In a random coefficient model with complements we derive a policy test for when incentives to reduce rival quality will hold. Our application is to Microsoft's strategic incentives to leverage market power from personal computer to server operating systems. We estimate a structural random coefficients demand system which allows for complements (PCs and servers). Our estimates suggest that there were incentives to reduce interoperability which were particularly strong at the turn of the 21st Century.Foreclosure, anti-trust, demand estimation, interoperability
Architecture-based Qualitative Risk Analysis for Availability of IT Infrastructures
An IT risk assessment must deliver the best possible quality of results in a time-effective way. Organisations are used to customise the general-purpose standard risk assessment methods in a way that can satisfy their requirements. In this paper we present the QualTD Model and method, which is meant to be employed together with standard risk assessment methods for the qualitative assessment of availability risks of IT architectures, or parts of them. The QualTD Model is based on our previous quantitative model, but geared to industrial practice since it does not require quantitative data which is often too costly to acquire. We validate the model and method in a real-world case by performing a risk assessment on the authentication and authorisation system of a large multinational company and by evaluating the results w.r.t. the goals of the stakeholders of the system. We also perform a review of the most popular standard risk assessment methods and an analysis of which one can be actually integrated with our QualTD Model
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