TY - GEN
T1 - Distributed genetic algorithm on graphX
AU - Mishra, Seemran
AU - Lee, Young Choon
AU - Nayak, Abhaya
PY - 2016
Y1 - 2016
N2 - In this paper we explore the application of a recent breed of distributed systems, graph processing frameworks in particular, to solving complex research problems. These frameworks are designed to take full advantage of today’s abundant resources with their inherent distributed computing functionalities. Abstraction of many technical details, such as networking and coordination of multiple compute nodes is a desirable feature provided by these graph-processing frameworks. While these frameworks are largely used to process and analyse the web graphs and social networks, their capacity is not limited to this direct application. This paper is based on design and implementation of a genetic algorithm (GA) using a graph processing tool, GraphX for the task scheduling problem as a case study. Our experimental results show that GraphX can significantly aid in devising distributed solutions for complex problems.
AB - In this paper we explore the application of a recent breed of distributed systems, graph processing frameworks in particular, to solving complex research problems. These frameworks are designed to take full advantage of today’s abundant resources with their inherent distributed computing functionalities. Abstraction of many technical details, such as networking and coordination of multiple compute nodes is a desirable feature provided by these graph-processing frameworks. While these frameworks are largely used to process and analyse the web graphs and social networks, their capacity is not limited to this direct application. This paper is based on design and implementation of a genetic algorithm (GA) using a graph processing tool, GraphX for the task scheduling problem as a case study. Our experimental results show that GraphX can significantly aid in devising distributed solutions for complex problems.
UR - http://www.scopus.com/inward/record.url?scp=85007198129&partnerID=8YFLogxK
UR - http://purl.org/au-research/grants/arc/LP140100980
UR - http://purl.org/au-research/grants/arc/DP150104133
U2 - 10.1007/978-3-319-50127-7_48
DO - 10.1007/978-3-319-50127-7_48
M3 - Conference proceeding contribution
AN - SCOPUS:85007198129
SN - 9783319501260
VL - 9992 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 548
EP - 554
BT - AI 2016: Advances in Artificial Intelligence - 29th Australasian Joint Conference, Proceedings
PB - Springer, Springer Nature
CY - Cham, Switzerland
T2 - 29th Australasian Joint Conference on Artificial Intelligence, AI 2016
Y2 - 5 December 2016 through 8 December 2016
ER -