TY - GEN
T1 - Poster abstract
T2 - 2020 IEEE INFOCOM Conference on Computer Communications Workshops, INFOCOM WKSHPS 2020
AU - Cohen, Itamar
AU - Einziger, Gil
AU - Goldstein, Maayan
AU - Sa'Ar, Yaniv
AU - Scalosub, Gabriel
AU - Waisbard, Erez
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Efficient on-demand deployment of VMs is at the core of cloud infrastructure but the existing resource management approaches are too slow to fulfill this promise. Parallel resource management is a promising direction for boosting performance, but when applied naïvely, it significantly increases the communication overhead and the decline ratio of deployment attempts. We propose a new dynamic and randomized algorithm, APSR, for parallel assignment of VMs to hosts in a cloud environment. APSR is guaranteed to satisfy an SLA containing decline ratio constraints, and communication overheads constraints. Furthermore, via extensive simulations, we show that APSR obtains a higher throughput than other commonly employed policies (including those used in OpenStack) while achieving a reduction of up to 13x in decline ratio and a reduction of over 85% in communication overheads.
AB - Efficient on-demand deployment of VMs is at the core of cloud infrastructure but the existing resource management approaches are too slow to fulfill this promise. Parallel resource management is a promising direction for boosting performance, but when applied naïvely, it significantly increases the communication overhead and the decline ratio of deployment attempts. We propose a new dynamic and randomized algorithm, APSR, for parallel assignment of VMs to hosts in a cloud environment. APSR is guaranteed to satisfy an SLA containing decline ratio constraints, and communication overheads constraints. Furthermore, via extensive simulations, we show that APSR obtains a higher throughput than other commonly employed policies (including those used in OpenStack) while achieving a reduction of up to 13x in decline ratio and a reduction of over 85% in communication overheads.
UR - https://www.scopus.com/pages/publications/85091480076
U2 - 10.1109/INFOCOMWKSHPS50562.2020.9162912
DO - 10.1109/INFOCOMWKSHPS50562.2020.9162912
M3 - Conference contribution
AN - SCOPUS:85091480076
T3 - IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2020
SP - 1298
EP - 1299
BT - IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2020
PB - Institute of Electrical and Electronics Engineers
Y2 - 6 July 2020 through 9 July 2020
ER -