15,215 research outputs found
PERFORMANCE EVALUATION ON QUALITY OF ASIAN AIRLINES WEBSITES – AN AHP PPROACH
In recent years, many people have devoted their efforts to the issue of quality of Web site. The concept of quality is consisting of many criteria: quality of service perspective, a user perspective, a content perspective or indeed a usability perspective. Because of its possible instant worldwide audience a Website’s quality and reliability are crucial. The very special nature of the web applications and websites pose unique software testing challenges. Webmasters, Web applications developers, and Website quality assurance managers need tools and methods that can match up to the new needs. This research conducts some tests to measure the quality web site of Asian flag carrier airlines via web diagnostic tools online. We propose a methodology for determining and evaluate the best airlines websites based on many criteria of website quality. The approach has been implemented using Analytical Hierarchy Process (AHP) to generate the weights for the criteria which are much better and guarantee more fairly preference of criteria. The proposed model uses the AHP pairwise comparisons and the measure scale to generate the weights for the criteria which are much better and guarantee
more fairly preference of criteria. The result of this study confirmed that the airlines websites of Asian are neglecting performance and quality criteria
AIOps for a Cloud Object Storage Service
With the growing reliance on the ubiquitous availability of IT systems and
services, these systems become more global, scaled, and complex to operate. To
maintain business viability, IT service providers must put in place reliable
and cost efficient operations support. Artificial Intelligence for IT
Operations (AIOps) is a promising technology for alleviating operational
complexity of IT systems and services. AIOps platforms utilize big data,
machine learning and other advanced analytics technologies to enhance IT
operations with proactive actionable dynamic insight.
In this paper we share our experience applying the AIOps approach to a
production cloud object storage service to get actionable insights into
system's behavior and health. We describe a real-life production cloud scale
service and its operational data, present the AIOps platform we have created,
and show how it has helped us resolving operational pain points.Comment: 5 page
A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing
The overwhelmingly increasing amount of stored data has spurred researchers
seeking different methods in order to optimally take advantage of it which
mostly have faced a response time problem as a result of this enormous size of
data. Most of solutions have suggested materialization as a favourite solution.
However, such a solution cannot attain Real- Time answers anyhow. In this paper
we propose a framework illustrating the barriers and suggested solutions in the
way of achieving Real-Time OLAP answers that are significantly used in decision
support systems and data warehouses
Impliance: A Next Generation Information Management Appliance
ably successful in building a large market and adapting to the changes of the
last three decades, its impact on the broader market of information management
is surprisingly limited. If we were to design an information management system
from scratch, based upon today's requirements and hardware capabilities, would
it look anything like today's database systems?" In this paper, we introduce
Impliance, a next-generation information management system consisting of
hardware and software components integrated to form an easy-to-administer
appliance that can store, retrieve, and analyze all types of structured,
semi-structured, and unstructured information. We first summarize the trends
that will shape information management for the foreseeable future. Those trends
imply three major requirements for Impliance: (1) to be able to store, manage,
and uniformly query all data, not just structured records; (2) to be able to
scale out as the volume of this data grows; and (3) to be simple and robust in
operation. We then describe four key ideas that are uniquely combined in
Impliance to address these requirements, namely the ideas of: (a) integrating
software and off-the-shelf hardware into a generic information appliance; (b)
automatically discovering, organizing, and managing all data - unstructured as
well as structured - in a uniform way; (c) achieving scale-out by exploiting
simple, massive parallel processing, and (d) virtualizing compute and storage
resources to unify, simplify, and streamline the management of Impliance.
Impliance is an ambitious, long-term effort to define simpler, more robust, and
more scalable information systems for tomorrow's enterprises.Comment: This article is published under a Creative Commons License Agreement
(http://creativecommons.org/licenses/by/2.5/.) You may copy, distribute,
display, and perform the work, make derivative works and make commercial use
of the work, but, you must attribute the work to the author and CIDR 2007.
3rd Biennial Conference on Innovative Data Systems Research (CIDR) January
710, 2007, Asilomar, California, US
Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web
If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches
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A framework for feeding Linked Data to Complex Event Processing engines
A huge volume of Linked Data has been published on the Web, yet is not processable by Complex Event Processing (CEP) or Event Stream Processing (ESP) engines. This paper presents a frame-work to bridge this gap, under which Linked Data are first translated into events conforming to a lightweight ontology, and then fed to CEP engines. The event processing results will also be published back onto the Web of Data. In this way, CEP engines are connected to the Web of Data, and the ontological reasoning is integrated with event processing. Finally, the implementation method and a case study of the framework are presented
Parallel Simulations for Analysing Portfolios of Catastrophic Event Risk
At the heart of the analytical pipeline of a modern quantitative
insurance/reinsurance company is a stochastic simulation technique for
portfolio risk analysis and pricing process referred to as Aggregate Analysis.
Support for the computation of risk measures including Probable Maximum Loss
(PML) and the Tail Value at Risk (TVAR) for a variety of types of complex
property catastrophe insurance contracts including Cat eXcess of Loss (XL), or
Per-Occurrence XL, and Aggregate XL, and contracts that combine these measures
is obtained in Aggregate Analysis.
In this paper, we explore parallel methods for aggregate risk analysis. A
parallel aggregate risk analysis algorithm and an engine based on the algorithm
is proposed. This engine is implemented in C and OpenMP for multi-core CPUs and
in C and CUDA for many-core GPUs. Performance analysis of the algorithm
indicates that GPUs offer an alternative HPC solution for aggregate risk
analysis that is cost effective. The optimised algorithm on the GPU performs a
1 million trial aggregate simulation with 1000 catastrophic events per trial on
a typical exposure set and contract structure in just over 20 seconds which is
approximately 15x times faster than the sequential counterpart. This can
sufficiently support the real-time pricing scenario in which an underwriter
analyses different contractual terms and pricing while discussing a deal with a
client over the phone.Comment: Proceedings of the Workshop at the International Conference for High
Performance Computing, Networking, Storage and Analysis (SC), 2012, 8 page
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