TY - GEN
T1 - Improvements to online distributed monitoring systems
AU - Wang, Bo
AU - Song, Ying
AU - Sun, Yuzhong
AU - Liu, Jun
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016
Y1 - 2016
N2 - Online monitoring, providing the real-time status information of servers, is indispensable for the management of distributed systems, e.g. failure detection and resource scheduling. The main design challenges for distributed monitoring systems include scalability, fine granularity, reliability and low overheads. And the challenges are growing with the increase of the scales of the distributed systems. To address the above problems, this paper studies improvements to online distributed monitoring systems (ODMSs) from three aspects: online compression algorithm, online compression reliability, and data representation for information interchanges. We summarize and classify the existing online compression algorithms to identify some research gaps that may represent opportunities for future research. A simple solution is proposed to address the problem that the inaccuracy of compression algorithms may be caused by some failures of distributed systems. A bitmap-like data format is presented to reduce the per-node overheads and the overheads of the management node in ODMSs, and compared with other existing formats used in the monitoring system both in mathematical analysis and practical experiment. The results show that the bitmap-like data format achieves best performance overall.
AB - Online monitoring, providing the real-time status information of servers, is indispensable for the management of distributed systems, e.g. failure detection and resource scheduling. The main design challenges for distributed monitoring systems include scalability, fine granularity, reliability and low overheads. And the challenges are growing with the increase of the scales of the distributed systems. To address the above problems, this paper studies improvements to online distributed monitoring systems (ODMSs) from three aspects: online compression algorithm, online compression reliability, and data representation for information interchanges. We summarize and classify the existing online compression algorithms to identify some research gaps that may represent opportunities for future research. A simple solution is proposed to address the problem that the inaccuracy of compression algorithms may be caused by some failures of distributed systems. A bitmap-like data format is presented to reduce the per-node overheads and the overheads of the management node in ODMSs, and compared with other existing formats used in the monitoring system both in mathematical analysis and practical experiment. The results show that the bitmap-like data format achieves best performance overall.
KW - Distributed systems
KW - Format
KW - Monitoring
KW - Online compression algorithms
UR - https://www.scopus.com/pages/publications/85015232403
U2 - 10.1109/TrustCom.2016.0180
DO - 10.1109/TrustCom.2016.0180
M3 - 会议稿件
AN - SCOPUS:85015232403
T3 - Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016
SP - 1093
EP - 1100
BT - Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Joint 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016
Y2 - 23 August 2016 through 26 August 2016
ER -