83 research outputs found
An analysis of software aging in cloud environment
Cloud Computing is the environment in which several virtual machines (VM) run concurrently on physical machines. The cloud computing infrastructure hosts multiple cloud service segments that communicate with each other using the interfaces. This creates distributed computing environment. During operation, the software systems accumulate errors or garbage that leads to system failure and other hazardous consequences. This status is called software aging. Software aging happens because of memory fragmentation, resource consumption in large scale and accumulation of numerical error. Software aging degrads the performance that may result in system failure. This happens because of premature resource exhaustion. This issue cannot be determined during software testing phase because of the dynamic nature of operation. The errors that cause software aging are of special types. These errors do not disturb the software functionality but target the response time and its environment. This issue is to be resolved only during run time as it occurs because of the dynamic nature of the problem. To alleviate the impact of software aging, software rejuvenation technique is being used. Rejuvenation process reboots the system or re-initiates the softwares. This avoids faults or failure. Software rejuvenation removes accumulated error conditions, frees up deadlocks and defragments operating system resources like memory. Hence, it avoids future failures of system that may happen due to software aging. As service availability is crucial, software rejuvenation is to be carried out at defined schedules without disrupting the service. The presence of Software rejuvenation techniques can make software systems more trustworthy. Software designers are using this concept to improve the quality and reliability of the software. Software aging and rejuvenation has generated a lot of research interest in recent years. This work reviews some of the research works related to detection of software aging and identifies research gaps
The design of an indirect method for the human presence monitoring in the intelligent building
This article describes the design and verification of the indirect method of predicting the course of CO2 concentration (ppm) from the measured temperature variables Tindoor (degrees C) and the relative humidity rH(indoor) (%) and the temperature T-outdoor (degrees C) using the Artificial Neural Network (ANN) with the Bayesian Regulation Method (BRM) for monitoring the presence of people in the individual premises in the Intelligent Administrative Building (IAB) using the PI System SW Tool (PI-Plant Information enterprise information system). The CA (Correlation Analysis), the MSE (Root Mean Squared Error) and the DTW (Dynamic Time Warping) criteria were used to verify and classify the results obtained. Within the proposed method, the LMS adaptive filter algorithm was used to remove the noise of the resulting predicted course. In order to verify the method, two long-term experiments were performed, specifically from February 1 to February 28, 2015, from June 1 to June 28, 2015 and from February 8 to February 14, 2015. For the best results of the trained ANN BRM within the prediction of CO2, the correlation coefficient R for the proposed method was up to 92%. The verification of the proposed method confirmed the possibility to use the presence of people of the monitored IAB premises for monitoring. The designed indirect method of CO2 prediction has potential for reducing the investment and operating costs of the IAB in relation to the reduction of the number of implemented sensors in the IAB within the process of management of operational and technical functions in the IAB. The article also describes the design and implementation of the FEIVISUAL visualization application for mobile devices, which monitors the technological processes in the IAB. This application is optimized for Android devices and is platform independent. The application requires implementation of an application server that communicates with the data server and the application developed. The data of the application developed is obtained from the data storage of the PI System via a PI Web REST API (Application Programming Integration) client.Web of Science8art. no. 2
Proactive software rejuvenation solution for web enviroments on virtualized platforms
The availability of the Information Technologies for everything, from everywhere, at all times is a growing requirement. We use information Technologies from common and social tasks to critical tasks like managing nuclear power plants or even the International Space Station (ISS). However, the availability of IT infrastructures is still a huge challenge nowadays. In a quick look around news, we can find reports of corporate outage, affecting millions of users and impacting on the revenue and image of the companies.
It is well known that, currently, computer system outages are more often due to software faults, than hardware faults. Several studies have reported that one of the causes of unplanned software outages is the software aging phenomenon. This term refers to the accumulation of errors, usually causing resource contention, during long running application executions, like web applications, which normally cause applications/systems to hang or crash. Gradual performance degradation could also accompany software aging phenomena. The software aging phenomena are often related to memory bloating/ leaks, unterminated threads, data corruption, unreleased file-locks or overruns. We can find several examples of software aging in the industry.
The work presented in this thesis aims to offer a proactive and predictive software rejuvenation solution for Internet Services against software aging caused by resource exhaustion. To this end, we first present a threshold based proactive rejuvenation to avoid the consequences of software aging. This first approach has some limitations, but the most important of them it is the need to know a priori the resource or resources involved in the crash and the critical condition values. Moreover, we need some expertise to fix the threshold value to trigger the rejuvenation action. Due to these limitations, we have evaluated the use of Machine Learning to overcome the weaknesses of our first approach to obtain a proactive and predictive solution.
Finally, the current and increasing tendency to use virtualization technologies to improve the resource utilization has made traditional data centers turn into virtualized data centers or platforms. We have used a Mathematical Programming approach to virtual machine allocation and migration to optimize the resources, accepting as many services as possible on the platform while at the same time, guaranteeing the availability (via our software rejuvenation proposal) of the services deployed against the software aging phenomena.
The thesis is supported by an exhaustive experimental evaluation that proves the effectiveness and feasibility of our proposals for current systems
Entrega de conteúdos multimédia em over-the-top: caso de estudo das gravações automáticas
Doutoramento em Engenharia EletrotécnicaOver-The-Top (OTT) multimedia delivery is a very appealing approach for providing
ubiquitous,
exible, and globally accessible services capable of low-cost
and unrestrained device targeting. In spite of its appeal, the underlying delivery
architecture must be carefully planned and optimized to maintain a high Qualityof-
Experience (QoE) and rational resource usage, especially when migrating from
services running on managed networks with established quality guarantees. To address
the lack of holistic research works on OTT multimedia delivery systems, this
Thesis focuses on an end-to-end optimization challenge, considering a migration
use-case of a popular Catch-up TV service from managed IP Television (IPTV)
networks to OTT. A global study is conducted on the importance of Catch-up
TV and its impact in today's society, demonstrating the growing popularity of
this time-shift service, its relevance in the multimedia landscape, and tness as
an OTT migration use-case. Catch-up TV consumption logs are obtained from
a Pay-TV operator's live production IPTV service containing over 1 million subscribers
to characterize demand and extract insights from service utilization at a
scale and scope not yet addressed in the literature. This characterization is used
to build demand forecasting models relying on machine learning techniques to enable
static and dynamic optimization of OTT multimedia delivery solutions, which
are able to produce accurate bandwidth and storage requirements' forecasts, and
may be used to achieve considerable power and cost savings whilst maintaining a
high QoE. A novel caching algorithm, Most Popularly Used (MPU), is proposed,
implemented, and shown to outperform established caching algorithms in both
simulation and experimental scenarios. The need for accurate QoE measurements
in OTT scenarios supporting HTTP Adaptive Streaming (HAS) motivates the creation
of a new QoE model capable of taking into account the impact of key HAS
aspects. By addressing the complete content delivery pipeline in the envisioned
content-aware OTT Content Delivery Network (CDN), this Thesis demonstrates
that signi cant improvements are possible in next-generation multimedia delivery
solutions.A entrega de conteúdos multimédia em Over-The-Top (OTT) e uma proposta
atractiva para fornecer um serviço flexível e globalmente acessível, capaz de alcançar qualquer dispositivo, com uma promessa de baixos custos. Apesar das suas vantagens, e necessario um planeamento arquitectural detalhado e optimizado para manter níveis elevados de Qualidade de Experiência (QoE), em particular aquando da migração dos serviços suportados em redes geridas com garantias de qualidade pré-estabelecidas. Para colmatar a falta de trabalhos de investigação na área de sistemas de entrega de conteúdos multimédia em OTT, esta Tese foca-se na optimização destas soluções como um todo, partindo do caso de uso de migração de um serviço popular de Gravações Automáticas suportado em redes de Televisão sobre IP (IPTV) geridas, para um cenário de entrega em OTT. Um estudo global para aferir a importância das Gravações Automáticas revela a sua relevância no panorama de serviços multimédia e a sua adequação enquanto caso de uso de
migração para cenários OTT. São obtidos registos de consumos de um serviço
de produção de Gravações Automáticas, representando mais de 1 milhão de assinantes,
para caracterizar e extrair informação de consumos numa escala e âmbito
não contemplados ate a data na literatura. Esta caracterização e utilizada para
construir modelos de previsão de carga, tirando partido de sistemas de machine
learning, que permitem optimizações estáticas e dinâmicas dos sistemas de entrega
de conteúdos em OTT através de previsões das necessidades de largura de banda e
armazenamento, potenciando ganhos significativos em consumo energético e custos.
Um novo mecanismo de caching, Most Popularly Used (MPU), demonstra um
desempenho superior as soluções de referencia, quer em cenários de simulação quer
experimentais. A necessidade de medição exacta da QoE em streaming adaptativo
HTTP motiva a criaçao de um modelo capaz de endereçar aspectos específicos
destas tecnologias adaptativas. Ao endereçar a cadeia completa de entrega através
de uma arquitectura consciente dos seus conteúdos, esta Tese demonstra que são
possíveis melhorias de desempenho muito significativas nas redes de entregas de
conteúdos em OTT de próxima geração
International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance: Building the Future of Public Health Surveillance
Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-04204pubpub1117
EG-ICE 2021 Workshop on Intelligent Computing in Engineering
The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways
EG-ICE 2021 Workshop on Intelligent Computing in Engineering
The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways
Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm
Abstract— Online transportation has become a basic
requirement of the general public in support of all activities to go
to work, school or vacation to the sights. Public transportation
services compete to provide the best service so that consumers
feel comfortable using the services offered, so that all activities
are noticed, one of them is the search for the shortest route in
picking the buyer or delivering to the destination. Node
Combination method can minimize memory usage and this
methode is more optimal when compared to A* and Ant Colony
in the shortest route search like Dijkstra algorithm, but can’t
store the history node that has been passed. Therefore, using
node combination algorithm is very good in searching the
shortest distance is not the shortest route. This paper is
structured to modify the node combination algorithm to solve the
problem of finding the shortest route at the dynamic location
obtained from the transport fleet by displaying the nodes that
have the shortest distance and will be implemented in the
geographic information system in the form of map to facilitate
the use of the system.
Keywords— Shortest Path, Algorithm Dijkstra, Node
Combination, Dynamic Location (key words
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