TY - GEN
T1 - Task deployment recommendation with worker availability
AU - Wei, Dong
AU - Roy, Senjuti Basu
AU - Amer-Yahia, Sihem
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/4
Y1 - 2020/4
N2 - We study recommendation of deployment strategies to task requesters that are consistent with their deployment parameters: a lower-bound on the quality of the crowd contribution, an upper-bound on the latency of task completion, and an upper-bound on the cost incurred by paying workers. We propose BatchStrat, an optimization-driven middle layer that recommends deployment strategies to a batch of requests by accounting for worker availability. We develop computationally efficient algorithms to recommend deployments that maximize task throughput and pay-off, and empirically validate its quality and scalability.
AB - We study recommendation of deployment strategies to task requesters that are consistent with their deployment parameters: a lower-bound on the quality of the crowd contribution, an upper-bound on the latency of task completion, and an upper-bound on the cost incurred by paying workers. We propose BatchStrat, an optimization-driven middle layer that recommends deployment strategies to a batch of requests by accounting for worker availability. We develop computationally efficient algorithms to recommend deployments that maximize task throughput and pay-off, and empirically validate its quality and scalability.
UR - http://www.scopus.com/inward/record.url?scp=85085866156&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85085866156&partnerID=8YFLogxK
U2 - 10.1109/ICDE48307.2020.00175
DO - 10.1109/ICDE48307.2020.00175
M3 - Conference contribution
AN - SCOPUS:85085866156
T3 - Proceedings - International Conference on Data Engineering
SP - 1806
EP - 1809
BT - Proceedings - 2020 IEEE 36th International Conference on Data Engineering, ICDE 2020
PB - IEEE Computer Society
T2 - 36th IEEE International Conference on Data Engineering, ICDE 2020
Y2 - 20 April 2020 through 24 April 2020
ER -