TY - GEN
T1 - Rhizoma
T2 - ACM/IFIP/USENIX 10th International Middleware Conference
AU - Yin, Qin
AU - Schüpbach, Adrian
AU - Cappos, Justin
AU - Baumann, Andrew
AU - Roscoe, Timothy
PY - 2009
Y1 - 2009
N2 - The trend towards cloud and utility computing infrastructures raises challenges not only for application development, but also for management: diverse resources, changing resource availability, and differing application requirements create a complex optimization problem. Most existing cloud applications are managed externally, and this separation can lead to increased response time to failures, and slower or less appropriate adaptation to resource availability and pricing changes. In this paper, we explore a different approach more akin to P2P systems: we closely couple a decentralized management runtime ("Rhizoma") with the application itself. The application expresses its resource requirements to the runtime as a constrained optimization problem. Rhizoma then fuses multiple real-time sources of resource availability data, from which it decides to acquire or release resources (such as virtual machines), redeploying the system to continually maximize its utility. Using PlanetLab as a challenging "proving ground" for cloud-based services, we present results showing Rhizoma's performance, overhead, and efficiency versus existing approaches, as well the system's ability to react to unexpected large-scale changes in resource availability.
AB - The trend towards cloud and utility computing infrastructures raises challenges not only for application development, but also for management: diverse resources, changing resource availability, and differing application requirements create a complex optimization problem. Most existing cloud applications are managed externally, and this separation can lead to increased response time to failures, and slower or less appropriate adaptation to resource availability and pricing changes. In this paper, we explore a different approach more akin to P2P systems: we closely couple a decentralized management runtime ("Rhizoma") with the application itself. The application expresses its resource requirements to the runtime as a constrained optimization problem. Rhizoma then fuses multiple real-time sources of resource availability data, from which it decides to acquire or release resources (such as virtual machines), redeploying the system to continually maximize its utility. Using PlanetLab as a challenging "proving ground" for cloud-based services, we present results showing Rhizoma's performance, overhead, and efficiency versus existing approaches, as well the system's ability to react to unexpected large-scale changes in resource availability.
UR - http://www.scopus.com/inward/record.url?scp=70549109057&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70549109057&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-10445-9_10
DO - 10.1007/978-3-642-10445-9_10
M3 - Conference contribution
AN - SCOPUS:70549109057
SN - 3642104444
SN - 9783642104442
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 184
EP - 204
BT - Middleware 2009
Y2 - 30 November 2009 through 4 December 2009
ER -