Communication complexity
The space complexity of approximating the frequency moments
Journal of Computer and System Sciences
Min-wise independent permutations
Journal of Computer and System Sciences - 30th annual ACM symposium on theory of computing
Estimating simple functions on the union of data streams
Proceedings of the thirteenth annual ACM symposium on Parallel algorithms and architectures
Sampling from a moving window over streaming data
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Maintaining Stream Statistics over Sliding Windows
SIAM Journal on Computing
Maintaining variance and k-medians over data stream windows
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
TAG: a Tiny AGgregation service for ad-hoc sensor networks
ACM SIGOPS Operating Systems Review - OSDI '02: Proceedings of the 5th symposium on Operating systems design and implementation
Tight Lower Bounds for the Distinct Elements Problem
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Approximate Aggregation Techniques for Sensor Databases
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Synopsis diffusion for robust aggregation in sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Approximate counts and quantiles over sliding windows
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A Survey on Data Compression in Wireless Sensor Networks
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02
Space efficient mining of multigraph streams
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
In-Network Data Processing forWireless Sensor Networks
MDM '06 Proceedings of the 7th International Conference on Mobile Data Management
A simpler and more efficient deterministic scheme for finding frequent items over sliding windows
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On biased reservoir sampling in the presence of stream evolution
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Data streams: algorithms and applications
Foundations and Trends® in Theoretical Computer Science
Spatially-decaying aggregation over a network
Journal of Computer and System Sciences
Variance estimation over sliding windows
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Range-Efficient Counting of Distinct Elements in a Massive Data Stream
SIAM Journal on Computing
Smooth Histograms for Sliding Windows
FOCS '07 Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science
Improved Algorithms for Polynomial-Time Decay and Time-Decay with Additive Error
Theory of Computing Systems
Maintaining time-decaying stream aggregates
Journal of Algorithms
A deterministic algorithm for summarizing asynchronous streams over a sliding window
STACS'07 Proceedings of the 24th annual conference on Theoretical aspects of computer science
IEEE Communications Magazine
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We present a new sketch for summarizing network data. The sketch has the following properties which make it useful in communication-efficient aggregation in distributed streaming scenarios, such as sensor networks: the sketch is duplicate insensitive, i.e., reinsertions of the same data will not affect the sketch and hence the estimates of aggregates. Unlike previous duplicate-insensitive sketches for sensor data aggregation [S. Nath et al., Synposis diffusion for robust aggregation in sensor networks, in Proceedings of the 2nd International Conference on Embedded Network Sensor Systems, (2004), pp. 250-262], [J. Considine et al., Approximate aggregation techniques for sensor databases, in Proceedings of the 20th International Conference on Data Engineering (ICDE), 2004, pp. 449-460], it is also time decaying, so that the weight of a data item in the sketch can decrease with time according to a user-specified decay function. The sketch can give provably approximate guarantees for various aggregates of data, including the sum, median, quantiles, and frequent elements. The size of the sketch and the time taken to update it are both polylogarithmic in the size of the relevant data. Further, multiple sketches computed over distributed data can be combined without loss of accuracy. To our knowledge, this is the first sketch that combines all the above properties.