TY - GEN
T1 - Optimal Resource Allocation for Crowdsourced Image Processing
AU - Wheatman, Kristina Sorensen
AU - Mehmeti, Fidan
AU - Mahon, Mark
AU - Qiu, Hang
AU - Chan, Kevin
AU - La Porta, Thomas
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - Crowdsourced image processing has the potential to vastly impact response timeliness in various emergency situations. Because images can provide extremely important information regarding an event of interest, sending the right images to an analyzer as soon as possible is of crucial importance. In this paper, we consider the problem of optimally assigning resources, both local (CPUs in phones) and remote (network-based GPUs) to mobile devices for processing images, ultimately sending those of interest to a centralized entity while also accounting for the energy consumption. To that end, we use the Network Utility Maximization (NUM) framework, coupled with a hit-ratio estimator and energy costs, to enable a distributed implementation of the system. Our results are validated using both synthetic simulations and real-life traces.
AB - Crowdsourced image processing has the potential to vastly impact response timeliness in various emergency situations. Because images can provide extremely important information regarding an event of interest, sending the right images to an analyzer as soon as possible is of crucial importance. In this paper, we consider the problem of optimally assigning resources, both local (CPUs in phones) and remote (network-based GPUs) to mobile devices for processing images, ultimately sending those of interest to a centralized entity while also accounting for the energy consumption. To that end, we use the Network Utility Maximization (NUM) framework, coupled with a hit-ratio estimator and energy costs, to enable a distributed implementation of the system. Our results are validated using both synthetic simulations and real-life traces.
UR - http://www.scopus.com/inward/record.url?scp=85091997522&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091997522&partnerID=8YFLogxK
U2 - 10.1109/SECON48991.2020.9158417
DO - 10.1109/SECON48991.2020.9158417
M3 - Conference contribution
AN - SCOPUS:85091997522
T3 - Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks workshops
BT - 2020 17th IEEE International Conference on Sensing, Communication and Networking, SECON 2020
PB - IEEE Computer Society
T2 - 17th IEEE International Conference on Sensing, Communication and Networking, SECON 2020
Y2 - 22 June 2020 through 25 June 2020
ER -