Managing massive time series streams with multi-scale compressed trickles

Authors:
Galen Reeves;Jie Liu;Suman Nath;Feng Zhao
Affiliations:
University of California, Berkeley, CA;Microsoft Research, Redmond, WA;Microsoft Research, Redmond, WA;Microsoft Research, Redmond, WA
Venue:
Proceedings of the VLDB Endowment
Year:
2009

Citing 21
Cited 9

Approximate nearest neighbors: towards removing the curse of dimensionality

STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Database-friendly random projections

PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Random projection in dimensionality reduction: applications to image and text data

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Dynamic multidimensional histograms

Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Wavelet synopses with error guarantees

Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Identifying Representative Trends in Massive Time Series Data Sets Using Sketches

VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
One-Pass Wavelet Decompositions of Data Streams

IEEE Transactions on Knowledge and Data Engineering
Performance debugging for distributed systems of black boxes

SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
BRAID: stream mining through group lag correlations

Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Fast window correlations over uncooperative time series

Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Streaming pattern discovery in multiple time-series

VLDB '05 Proceedings of the 31st international conference on Very large data bases
Indexing Multidimensional Time-Series

The VLDB Journal — The International Journal on Very Large Data Bases
Power provisioning for a warehouse-sized computer

Proceedings of the 34th annual international symposium on Computer architecture
StatStream: statistical monitoring of thousands of data streams in real time

VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Counter braids: a novel counter architecture for per-flow measurement

SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Querying continuous functions in a database system

Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Energy-aware server provisioning and load dispatching for connection-intensive internet services

NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
iSAX: indexing and mining terabyte sized time series

Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
GAMPS: compressing multi sensor data by grouping and amplitude scaling

Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Compressed sensing

IEEE Transactions on Information Theory
Signal Reconstruction From Noisy Random Projections

IEEE Transactions on Information Theory

Fast approximate correlation for massive time-series data

Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Parsimonious linear fingerprinting for time series

Proceedings of the VLDB Endowment
DataGarage: warehousing massive performance data on commodity servers

Proceedings of the VLDB Endowment
Finding semantics in time series

Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
A case-study on learning from large-scale intracranial EEG data using multi-core machines and clusters

Proceedings of the Third Workshop on Large Scale Data Mining: Theory and Applications
Approximate query on historical stream data

DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
RainMon: an integrated approach to mining bursty timeseries monitoring data

Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Time-series data mining

ACM Computing Surveys (CSUR)
Pattern discovery in data streams under the time warping distance

The VLDB Journal — The International Journal on Very Large Data Bases

Quantified Score

Hi-index	0.01

Visualization

Abstract

We present Cypress, a novel framework to archive and query massive time series streams such as those generated by sensor networks, data centers, and scientific computing. Cypress applies multi-scale analysis to decompose time series and to obtain sparse representations in various domains (e.g. frequency domain and time domain). Relying on the sparsity, the time series streams can be archived with reduced storage space. We then show that many statistical queries such as trend, histogram and correlations can be answered directly from compressed data rather than from reconstructed raw data. Our evaluation with server utilization data collected from real data centers shows significant benefit of our framework.