TY - GEN
T1 - Parameter setting and exploration of TAGS using a genetic algorithm
AU - Sarfati, Hagit
AU - Bachmat, Eitan
AU - Kedem-Yemini, Sagit
PY - 2007/9/25
Y1 - 2007/9/25
N2 - We consider the performance of TAGS, a multi-host job assignment policy. We use a genetic algorithm to compute the optimal parameter settings for the policy. We then explore the performance of the policy using the optimal parameters, when the job size distribution is a heavy-tailed Bounded Pareto distribution with parameter α. We show that TAGS only operates at low interarrival rates. At low rates it is very efficient in comparison with other standard policies. At high rates TAGS has to be combined with other policies to achieve good performance. We also show that the performance is nearly symmetrical around the value α = 1, with the best performance when α = 1.
AB - We consider the performance of TAGS, a multi-host job assignment policy. We use a genetic algorithm to compute the optimal parameter settings for the policy. We then explore the performance of the policy using the optimal parameters, when the job size distribution is a heavy-tailed Bounded Pareto distribution with parameter α. We show that TAGS only operates at low interarrival rates. At low rates it is very efficient in comparison with other standard policies. At high rates TAGS has to be combined with other policies to achieve good performance. We also show that the performance is nearly symmetrical around the value α = 1, with the best performance when α = 1.
KW - Genetic algorithm
KW - Heavy-tailed distributions
KW - Multiple host task assignment
UR - http://www.scopus.com/inward/record.url?scp=34548731789&partnerID=8YFLogxK
U2 - 10.1109/SCIS.2007.367702
DO - 10.1109/SCIS.2007.367702
M3 - Conference contribution
AN - SCOPUS:34548731789
SN - 1424407044
SN - 9781424407040
T3 - Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Scheduling, CI-Sched 2007
SP - 279
EP - 285
BT - Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Scheduling, CI-Sched 2007
T2 - 2007 IEEE Symposium on Computational Intelligence in Scheduling, CI-Sched 2007
Y2 - 1 April 2007 through 5 April 2007
ER -