A Multi-Objective ACS Algorithm to Optimize Cost, Performance, and Reliability in the Cloud

A4 Konferenspublikationer


Interna författare/redaktörer


Publikationens författare: Adnan Ashraf, Benjamin Byholm, Ivan Porres
Redaktörer: Omer Rana, Manish Parashar
Publiceringsår: 2015
Förläggare: ACM
Moderpublikationens namn: 8th IEEE/ACM International Conference on Utility and Cloud Computing
Artikelns första sida, sidnummer: 341
Artikelns sista sida, sidnummer: 347
ISBN: 978-1-4503-3890-5


Abstrakt

In this paper, we present a novel Multi-Objective Ant Colony System algorithm to optimize Cost, Performance, and Reliability (MOACS-CoPeR) in the cloud. The proposed algorithm provides a metaheuristic-based approach for the multi-objective cloud-based software component deployment problem. MOACS-CoPeR explores the search-space of architecture design alternatives with respect to several architectural degrees of freedom and produces a set of Pareto-optimal deployment configurations. We also present a Java-based implementation of our proposed algorithm and compare its results with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). We evaluate the two algorithms against a cloud-based storage service, which is loosely based on a real system.


Nyckelord

ant colony optimization (ACO), Cloud computing, Multi-objective optimization, Software component deployment


Dokument


Senast uppdaterad 2020-04-04 vid 05:36