TY - GEN
T1 - An estimation-based task load balancing scheduling in spot clouds
AU - Jung, Daeyong
AU - Choi, Hee Seok
AU - Lee, Dae Won
AU - Yu, Heonchang
AU - Lee, Eunyoung
PY - 2014
Y1 - 2014
N2 - Cloud computing is a computing paradigm in which users can rent computing resources from service providers according to their requirements. Cloud computing based on the spot market helps a user to obtain resources at a lower cost. However, these resources may be unreliable. In this paper, we propose an estimation-based distributed task workflow scheduling scheme that reduces the estimated generation compared to Genetic Algorithm (GA). Moreover, our scheme executes a user's job within selected instances and stretches the user's cost. The simulation results, based on a before-and-after estimation comparison, reveal that the task size is determined based on the performance of each instance and the task is distributed among the different instances. Therefore, our proposed estimation-based task load balancing scheduling technique achieves the task load balancing according to the performance of instances.
AB - Cloud computing is a computing paradigm in which users can rent computing resources from service providers according to their requirements. Cloud computing based on the spot market helps a user to obtain resources at a lower cost. However, these resources may be unreliable. In this paper, we propose an estimation-based distributed task workflow scheduling scheme that reduces the estimated generation compared to Genetic Algorithm (GA). Moreover, our scheme executes a user's job within selected instances and stretches the user's cost. The simulation results, based on a before-and-after estimation comparison, reveal that the task size is determined based on the performance of each instance and the task is distributed among the different instances. Therefore, our proposed estimation-based task load balancing scheduling technique achieves the task load balancing according to the performance of instances.
UR - http://www.scopus.com/inward/record.url?scp=84906766949&partnerID=8YFLogxK
U2 - 10.1007/978-3-662-44917-2_55
DO - 10.1007/978-3-662-44917-2_55
M3 - Conference contribution
AN - SCOPUS:84906766949
SN - 9783662449165
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 571
EP - 574
BT - Network and Parallel Computing - 11th IFIP WG 10.3 International Conference, NPC 2014, Proceedings
PB - Springer Verlag
T2 - 11th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2014
Y2 - 18 September 2014 through 20 September 2014
ER -