TY - GEN
T1 - DIAL
T2 - 14th IEEE International Conference on Autonomic Computing, ICAC 2017
AU - Javadi, Seyyed Ahmad
AU - Gandhi, Anshul
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/8
Y1 - 2017/8/8
N2 - Many online application services are now provided by cloud-deployed VM clusters. Although economical, VMs in the cloud are prone to interference due to contention for physical resources among colocated users. Worse, this interference is dynamic and unpredictable. Current provider-centric solutions are application-oblivious and are thus not always aware of the user's SLO requirements or application bottlenecks. Further, such solutions rely on VM scheduling and migration, approaches that are not agile enough to mitigate volatile interference.This paper presents DIAL, an interference-aware load balancer that can be employed by cloud users without requiring any assistance from the provider. DIAL addresses timevarying interference by dynamically shifting load away from compromised VMs without violating the application's tail latency SLOs. The key idea behind DIAL is to infer the demand for contended resources on the physical hosts, which is otherwise hidden from users. Estimates of the colocated load are then used to drive the load distribution for the application VMs. Our experimental results on OpenStack and AWS clouds show that DIAL can reduce application tail latencies by as much as 70% and 48% compared to interference-oblivious and existing interference-aware load balancers, respectively.
AB - Many online application services are now provided by cloud-deployed VM clusters. Although economical, VMs in the cloud are prone to interference due to contention for physical resources among colocated users. Worse, this interference is dynamic and unpredictable. Current provider-centric solutions are application-oblivious and are thus not always aware of the user's SLO requirements or application bottlenecks. Further, such solutions rely on VM scheduling and migration, approaches that are not agile enough to mitigate volatile interference.This paper presents DIAL, an interference-aware load balancer that can be employed by cloud users without requiring any assistance from the provider. DIAL addresses timevarying interference by dynamically shifting load away from compromised VMs without violating the application's tail latency SLOs. The key idea behind DIAL is to infer the demand for contended resources on the physical hosts, which is otherwise hidden from users. Estimates of the colocated load are then used to drive the load distribution for the application VMs. Our experimental results on OpenStack and AWS clouds show that DIAL can reduce application tail latencies by as much as 70% and 48% compared to interference-oblivious and existing interference-aware load balancers, respectively.
UR - https://www.scopus.com/pages/publications/85034452996
U2 - 10.1109/ICAC.2017.17
DO - 10.1109/ICAC.2017.17
M3 - Conference contribution
AN - SCOPUS:85034452996
T3 - Proceedings - 2017 IEEE International Conference on Autonomic Computing, ICAC 2017
SP - 135
EP - 144
BT - Proceedings - 2017 IEEE International Conference on Autonomic Computing, ICAC 2017
A2 - Wang, Xiaorui
A2 - Lei, Hui
A2 - Stewart, Christopher
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 July 2017 through 21 July 2017
ER -