research-article

Top-k and Skyline for Cloud Services Research and Selection System

Authors:

Abdellah Idrissi,

Kaoutar EL HANDRI,

Manar AbourezqAuthors Info & Claims

BDAW '16: Proceedings of the International Conference on Big Data and Advanced Wireless Technologies

Article No.: 40, Pages 1 - 10

https://doi.org/10.1145/3010089.3010125

Published: 10 November 2016 Publication History

Editorial Notes

A corrigendum was issued for this article on December 10, 2019. This can be found under the Source Materials tab.

Abstract

Cloud Services remain one of the largest segments in the world because it has experienced very rapid growth published, which makes the service selection and recommendation a difficult task for users and service providers, evenly they are a big growth opportunity for companies. For this reason, how to select the best and optimal services will be a great challenge. In this paper we present a new approach for Cloud service selection. We use a top K query, which returns k services that dominate the largest number of services returned by the Skyline query. This request is based on a method that is among the most important and commonly used to compute scoring functions: The weighted sum method, also called linear. Our application is an important decision support tool, because it provides an efficient decision making tool to help decision makers to meet the most suitable services to their preferences. In addition, it combines the advantages of Top-k and Skyline queries without sharing their disadvantages. On the other hand, our results on real data show the relevance of this designed specific algorithm and fully exploit the characteristics of the problem.

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Corrigendum to "Top-k and Skyline for Cloud Services Research and Selection System", by Idrissi, et al., BDAW '16 Proceedings of the International Conference on Big Data and Advanced Wireless Technologies

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BDAW '16: Proceedings of the International Conference on Big Data and Advanced Wireless Technologies

November 2016

398 pages

ISBN:9781450347792

DOI:10.1145/3010089

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Published: 10 November 2016

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BDAW '16: International Conference on Big Data and Advanced Wireless Technologies

November 10 - 11, 2016

Blagoevgrad, Bulgaria

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EL Handri KBenedress LWakrim LLamzabi SIdrissi A(2024)AI-Based QoS Optimization in Post-Disaster Ad Hoc Networks: Top-K Path Enumeration with Multicriteria Decision Analysis2024 IEEE 4th International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA)10.1109/MI-STA61267.2024.10599698(561-566)Online publication date: 19-May-2024
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