TY - GEN
T1 - Reversing the supermarket
T2 - 2016 IEEE/IFIP Network Operations and Management Symposium, NOMS 2016
AU - Nahir, Amir
AU - Orda, Ariel
AU - Raz, Danny
N1 - Publisher Copyright: © 2016 IEEE.
PY - 2016/6/30
Y1 - 2016/6/30
N2 - A fundamental capability of cloud computing is elasticity, i.e., the ability to dynamically change the amount of allocated resources. This is typically done by adjusting the number of Virtual Machines (VMs) running a service based on the current demand for that service. For large services, centralized management is impractical and distributed methods are employed. In such settings, no single component has full information on the overall demand and service quality, thus elasticity becomes a real challenge. We address this challenge by proposing a novel elasticity scheme that enables fully distributed management of large cloud services. Our scheme is based on three main components, namely, a task assignment policy, a VM scale-up policy and a VM scale-down policy. The task assignment policy strives to pack VMs while maintaining SLA requirements. The VM scale-up policy is based on local activation of new VMs and the VM scale-down policy is based on self-deactivation of VMs that are idle for some duration of time. Through simulations and an implementation we establish that our scheme quickly adapts to changes in job arrival rates and minimizes the number of active VMs so as to reduce the operational costs of the service, while adhering to strict SLA requirements.
AB - A fundamental capability of cloud computing is elasticity, i.e., the ability to dynamically change the amount of allocated resources. This is typically done by adjusting the number of Virtual Machines (VMs) running a service based on the current demand for that service. For large services, centralized management is impractical and distributed methods are employed. In such settings, no single component has full information on the overall demand and service quality, thus elasticity becomes a real challenge. We address this challenge by proposing a novel elasticity scheme that enables fully distributed management of large cloud services. Our scheme is based on three main components, namely, a task assignment policy, a VM scale-up policy and a VM scale-down policy. The task assignment policy strives to pack VMs while maintaining SLA requirements. The VM scale-up policy is based on local activation of new VMs and the VM scale-down policy is based on self-deactivation of VMs that are idle for some duration of time. Through simulations and an implementation we establish that our scheme quickly adapts to changes in job arrival rates and minimizes the number of active VMs so as to reduce the operational costs of the service, while adhering to strict SLA requirements.
UR - http://www.scopus.com/inward/record.url?scp=84979740224&partnerID=8YFLogxK
U2 - 10.1109/NOMS.2016.7502800
DO - 10.1109/NOMS.2016.7502800
M3 - منشور من مؤتمر
T3 - Proceedings of the NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium
SP - 87
EP - 95
BT - Proceedings of the NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium
A2 - Badonnel, Sema Oktug
A2 - Ulema, Mehmet
A2 - Cavdar, Cicek
A2 - Granville, Lisandro Zambenedetti
A2 - dos Santos, Carlos Raniery P.
Y2 - 25 April 2016 through 29 April 2016
ER -