Size-estimation framework with applications to transitive closure and reachability
Journal of Computer and System Sciences
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Distributed streams algorithms for sliding windows
Proceedings of the fourteenth annual ACM symposium on Parallel algorithms and architectures
Maintaining Stream Statistics over Sliding Windows
SIAM Journal on Computing
Maintaining time-decaying stream aggregates
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Maintaining variance and k-medians over data stream windows
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Better streaming algorithms for clustering problems
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Spatially-decaying aggregation over a network: model and algorithms
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Spatially-decaying aggregation over a network: model and algorithms
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Maintaining time-decaying stream aggregates
Journal of Algorithms
Spatially-decaying aggregation over a network
Journal of Computer and System Sciences
Bottom-k sketches: better and more efficient estimation of aggregates
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Summarizing data using bottom-k sketches
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Tighter estimation using bottom k sketches
Proceedings of the VLDB Endowment
Leveraging discarded samples for tighter estimation of multiple-set aggregates
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Maintaining time-decaying stream aggregates
Journal of Algorithms
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The neighborhood variance problem is as follows. Given a (directed or undirected) graph with values associated with each node, compute a data structure that for any given node v and r ≥ 0, would quickly produce an estimate of the variance of all values of nodes that lie within distance r from v. The problem can be generalized to other moment functions and to arbitrary distance-dependent decay.These problems are motivated by applications where the relevance of a measurement observed (or data present) at a certain location decreases with its distance, and thus the aggregate value varies by location. The centralized version of the problem is motivated by applications to query processing on graphical databases. The distributed version of the problem falls in a model we recently introduced for spatially decaying aggregation and is motivated by sensor or p2p networks.We present novel algorithms for the centralized and distributed versions of the problem. Our algorithms are nearly optimal, the centralized version requires Õ(m) time and the distributed version requires polylogarithmic communication per node or edge (depending on assumptions).