caa a22 4500 445327154 CHVBK 20180317142724.0 cr unu---uuuuu 170323e20110901xx s 000 0 eng 10.1007/s10723-011-9180-5 doi (NATIONALLICENCE)springer-10.1007/s10723-011-9180-5 Swarm Intelligence Approaches for Grid Load Balancing [Elektronische Daten] [Simone Ludwig, Azin Moallem] With the rapid growth of data and computational needs, distributed systems and computational Grids are gaining more and more attention. The huge amount of computations a Grid can fulfill in a specific amount of time cannot be performed by the best supercomputers. However, Grid performance can still be improved by making sure all the resources available in the Grid are utilized optimally using a good load balancing algorithm. This research proposes two new distributed swarm intelligence inspired load balancing algorithms. One algorithm is based on ant colony optimization and the other algorithm is based on particle swarm optimization. A simulation of the proposed approaches using a Grid simulation toolkit (GridSim) is conducted. The performance of the algorithms are evaluated using performance criteria such as makespan and load balancing level. A comparison of our proposed approaches with a classical approach called State Broadcast Algorithm and two random approaches is provided. Experimental results show the proposed algorithms perform very well in a Grid environment. Especially the application of particle swarm optimization, can yield better performance results in many scenarios than the ant colony approach. Springer Science+Business Media B.V., 2011 Ant colony optimization nationallicence Particle swarm optimization nationallicence Ludwig Simone Department of Computer Science, North Dakota State University, Fargo, ND, USA aut Moallem Azin Department of Computer Science, North Dakota State University, Fargo, ND, USA aut Journal of Grid Computing Springer Netherlands 9/3(2011-09-01), 279-301 1570-7873 9:3<279 2011 9 10723 https://doi.org/10.1007/s10723-011-9180-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10723-011-9180-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ludwig Simone Department of Computer Science, North Dakota State University, Fargo, ND, USA aut NATIONALLICENCE 700 1- Moallem Azin Department of Computer Science, North Dakota State University, Fargo, ND, USA aut NATIONALLICENCE 773 0- Journal of Grid Computing Springer Netherlands 9/3(2011-09-01), 279-301 1570-7873 9:3<279 2011 9 10723 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer