Communication-efficient distributed monitoring of thresholded counts
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Streaming in a connected world: querying and tracking distributed data streams
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Continuously maintaining order statistics over data streams: extended abstract
ADC '07 Proceedings of the eighteenth conference on Australasian database - Volume 63
Randomized algorithms for data reconciliation in wide area aggregate query processing
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Algorithms for distributed functional monitoring
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Shape sensitive geometric monitoring
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficiently Monitoring Nearest Neighbors to a Moving Object
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Making filters smart in distributed data stream environments
Information Sciences: an International Journal
Optimal tracking of distributed heavy hitters and quantiles
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Functional Monitoring without Monotonicity
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Distributed stream join query processing with semijoins
Distributed and Parallel Databases
Aggregate computation over data streams
APWeb'08 Proceedings of the 10th Asia-Pacific web conference on Progress in WWW research and development
Optimal sampling from distributed streams
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Fully decentralized computation of aggregates over data streams
Proceedings of the First International Workshop on Novel Data Stream Pattern Mining Techniques
Counting distinct objects over sliding windows
ADC '10 Proceedings of the Twenty-First Australasian Conference on Database Technologies - Volume 104
Algorithms for distributed functional monitoring
ACM Transactions on Algorithms (TALG)
Fully decentralized computation of aggregates over data streams
ACM SIGKDD Explorations Newsletter
Mining frequent itemsets over distributed data streams by continuously maintaining a global synopsis
Data Mining and Knowledge Discovery
Continuous distributed monitoring: a short survey
Proceedings of the First International Workshop on Algorithms and Models for Distributed Event Processing
Privacy-preserving environment monitoring in networks of mobile devices
NETWORKING'11 Proceedings of the IFIP TC 6th international conference on Networking
Lower bounds for number-in-hand multiparty communication complexity, made easy
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Continuous sampling from distributed streams
Journal of the ACM (JACM)
Continuous distributed counting for non-monotonic streams
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
Survey: Streaming techniques and data aggregation in networks of tiny artefacts
Computer Science Review
Distributed Adaptive Windowed Stream Join Processing
International Journal of Distributed Systems and Technologies
The continuous distributed monitoring model
ACM SIGMOD Record
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Emerging applications in sensor systems and network-wide IP traffic analysis present many technical challenges. They need distributed monitoring and continuous tracking of events. They have severe resource constraints not only at each site in terms of per-update processing time and archival space for highspeed streams of observations, but also crucially, communication constraints for collaborating on the monitoring task. These elements have been addressed in a series of recent works. A fundamental issue that arises is that one cannot make the "uniqueness" assumption on observed events which is present in previous works, since widescale monitoring invariably encounters the same events at different points. For example, within the network of an Internet Service Provider packets of the same flow will be observed in different routers; similarly, the same individual will be observed by multiple mobile sensors in monitoring wild animals. Aggregates of interest on such distributed environments must be resilient to duplicate observations. We study such duplicate-resilient aggregates that measure the extent of the duplication―how many unique observations are there, how many observations are unique―as well as standard holistic aggregates such as quantiles and heavy hitters over the unique items. We present accuracy guaranteed, highly communication-efficient algorithms for these aggregates that work within the time and space constraints of high speed streams. We also present results of a detailed experimental study on both real-life and synthetic data.