TY - GEN
T1 - Sysoptic
T2 - 13th IEEE International Conference on Service-Oriented System Engineering, SOSE 2019, 10th International Workshop on Joint Cloud Computing, JCC 2019 and 2019 IEEE International Workshop on Cloud Computing in Robotic Systems, CCRS 2019
AU - Liu, Pin
AU - Yang, Renyu
AU - Sun, Jie
AU - Liu, Xudong
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5/3
Y1 - 2019/5/3
N2 - Modern cloud datacenters indicate the frequent ex-istence of complex failure manifestation. Failures have becomethe norm, and not the exception. This is a key challengesince assumptions that underpin designing reliable systems aremonitoring systems status and detecting anomaly at runtime. Performance Monitoring Unit on CPU (PMU) can obtainfine-grained monitoring data by adopting interrupt samplingmethod based on hardware events. However, profilers in virtualmachines fail to receive PMU relevant information directlydue to the limited capacity of PMU virtualization. In thispaper, we present a fine-grained monitoring system SysOpticbased on PMU virtualization. First, we propose a method toexpose PMU information PMU and ensure the visibility ofsuch information at virtual machine level. Second, to maximizethe PMU reusability, SysOptic supports the PMU sharing andsimultaneous monitoring among multiple virtual machines. Furthermore, we also describe how to synchronize interruptson physical machines to virtual machines by using injectinginterrupts. Experimental results show that with the aid ofSysOptic, profiler tools in virtual machines manage to perceivethe existence of PMU and collect the monitoring data. Theadditional overhead incurred by SysOptic is at most 9.8%.
AB - Modern cloud datacenters indicate the frequent ex-istence of complex failure manifestation. Failures have becomethe norm, and not the exception. This is a key challengesince assumptions that underpin designing reliable systems aremonitoring systems status and detecting anomaly at runtime. Performance Monitoring Unit on CPU (PMU) can obtainfine-grained monitoring data by adopting interrupt samplingmethod based on hardware events. However, profilers in virtualmachines fail to receive PMU relevant information directlydue to the limited capacity of PMU virtualization. In thispaper, we present a fine-grained monitoring system SysOpticbased on PMU virtualization. First, we propose a method toexpose PMU information PMU and ensure the visibility ofsuch information at virtual machine level. Second, to maximizethe PMU reusability, SysOptic supports the PMU sharing andsimultaneous monitoring among multiple virtual machines. Furthermore, we also describe how to synchronize interruptson physical machines to virtual machines by using injectinginterrupts. Experimental results show that with the aid ofSysOptic, profiler tools in virtual machines manage to perceivethe existence of PMU and collect the monitoring data. Theadditional overhead incurred by SysOptic is at most 9.8%.
KW - Cloud computing
KW - PMU
KW - Performance monitoring
KW - Virtualizaiton
UR - https://www.scopus.com/pages/publications/85065979087
U2 - 10.1109/SOSE.2019.00042
DO - 10.1109/SOSE.2019.00042
M3 - 会议稿件
AN - SCOPUS:85065979087
T3 - Proceedings - 13th IEEE International Conference on Service-Oriented System Engineering, SOSE 2019, 10th International Workshop on Joint Cloud Computing, JCC 2019 and 2019 IEEE International Workshop on Cloud Computing in Robotic Systems, CCRS 2019
SP - 244
EP - 250
BT - Proceedings - 13th IEEE International Conference on Service-Oriented System Engineering, SOSE 2019, 10th International Workshop on Joint Cloud Computing, JCC 2019 and 2019 IEEE International Workshop on Cloud Computing in Robotic Systems, CCRS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 April 2019 through 9 April 2019
ER -