Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
The cougar approach to in-network query processing in sensor networks
ACM SIGMOD Record
Providing Database as a Service
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Multiresolution storage and search in sensor networks
ACM Transactions on Storage (TOS)
A spatiotemporal uncertainty model of degree 1.5 for continuously changing data objects
Proceedings of the 2006 ACM symposium on Applied computing
Processing partially specified queries over high-dimensional databases
Data & Knowledge Engineering
Data Management in the Worldwide Sensor Web
IEEE Pervasive Computing
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Bigtable: A Distributed Storage System for Structured Data
ACM Transactions on Computer Systems (TOCS)
Intelligent Techniques for Warehousing and Mining Sensor Network Data
Intelligent Techniques for Warehousing and Mining Sensor Network Data
CAMS: OLAPing Multidimensional Data Streams Efficiently
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
PRESTO: feedback-driven data management in sensor networks
IEEE/ACM Transactions on Networking (TON)
The tornado model: uncertainty model for continuously changing data
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Event-based lossy compression for effective and efficient OLAP over data streams
Data & Knowledge Engineering
Big data and cloud computing: current state and future opportunities
Proceedings of the 14th International Conference on Extending Database Technology
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
Interpolating and using most likely trajectories in moving-objects databases
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
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Recent advances and innovations in smart sensor technologies, energy storage, data communications, and distributed computing paradigms are enabling technological breakthroughs in very large sensor networks. There is an emerging surge of next-generation sensor-rich computers in consumer mobile devices as well as tailor-made field platforms wirelessly connected to the Internet. Billions of such sensor computers are posing both challenges and opportunities in relation to scalable and reliable management of the peta- and exa-scale time series being generated over time. This paper presents a Cloud-computing approach to this issue based on the two well-known data storage and processing paradigms: Bigtable and MapReduce.