TY - GEN
T1 - Efficient on-demand operations in dynamic distributed infrastructures
AU - Ko, Steven Y.
AU - Gupta, Indranil
PY - 2009
Y1 - 2009
N2 - In a large-scale distributed infrastructure, users and administrators typically desire to perform on-demand operations that act upon the most up-to-date state of the infrastructure. These on-demand operations range from monitoring the up-to-date machine properties in the infrastructure, to making Grid scheduling decisions for different tasks based on the current status of the infrastructure. However, the scale and dynamism present in the operating environment make it challenging to support these operations efficiently. This paper discusses several on-demand operations that we have been studying, challenges associated with them, and how to meet the challenges. Specifically, we build techniques for 1) on-demand group monitoring that allows users and administrators of an infrastructure to query and aggregate the up-to-date state of the machines (e.g., CPU utilization) in a group or multiple groups, 2) an on-demand Grid scheduling strategy that makes scheduling decisions based on the current availability of compute nodes, 3) another on-demand Grid scheduling strategy that chooses the best algorithm for the current input data set among multiple algorithms available. We also present our ongoing work.
AB - In a large-scale distributed infrastructure, users and administrators typically desire to perform on-demand operations that act upon the most up-to-date state of the infrastructure. These on-demand operations range from monitoring the up-to-date machine properties in the infrastructure, to making Grid scheduling decisions for different tasks based on the current status of the infrastructure. However, the scale and dynamism present in the operating environment make it challenging to support these operations efficiently. This paper discusses several on-demand operations that we have been studying, challenges associated with them, and how to meet the challenges. Specifically, we build techniques for 1) on-demand group monitoring that allows users and administrators of an infrastructure to query and aggregate the up-to-date state of the machines (e.g., CPU utilization) in a group or multiple groups, 2) an on-demand Grid scheduling strategy that makes scheduling decisions based on the current availability of compute nodes, 3) another on-demand Grid scheduling strategy that chooses the best algorithm for the current input data set among multiple algorithms available. We also present our ongoing work.
UR - http://www.scopus.com/inward/record.url?scp=77953840283&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77953840283&partnerID=8YFLogxK
U2 - 10.1145/1529974.1529986
DO - 10.1145/1529974.1529986
M3 - Conference contribution
AN - SCOPUS:77953840283
SN - 9781605582962
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 2nd Workshop on Large-Scale Distributed Systems and Middleware, LADIS'08
T2 - 2nd Workshop on Large-Scale Distributed Systems and Middleware, LADIS'08
Y2 - 15 September 2008 through 17 September 2008
ER -