Summary cache: a scalable wide-area web cache sharing protocol
IEEE/ACM Transactions on Networking (TON)
An analysis of Internet content delivery systems
ACM SIGOPS Operating Systems Review - OSDI '02: Proceedings of the 5th symposium on Operating systems design and implementation
The performance of difference coding for sets and relational tables
Journal of the ACM (JACM)
Time-Decaying Bloom Filters for Data Streams with Skewed Distributions
RIDE '05 Proceedings of the 15th International Workshop on Research Issues in Data Engineering: Stream Data Mining and Applications
Approximately detecting duplicates for streaming data using stable bloom filters
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Hint-based Routing in WSNs using Scope Decay Bloom Filters
IWNAS '06 Proceedings of the 2006 International Workshop on Networking, Architecture, and Storages
CoNEXT '06 Proceedings of the 2006 ACM CoNEXT conference
Detecting Click Fraud in Pay-Per-Click Streams of Online Advertising Networks
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
An Economic Model of Click Fraud in Publisher Networks
International Journal of Electronic Commerce
Improved approximate detection of duplicates for data streams over sliding windows
Journal of Computer Science and Technology
B-SUB: A Practical Bloom-Filter-Based Publish-Subscribe System for Human Networks
ICDCS '10 Proceedings of the 2010 IEEE 30th International Conference on Distributed Computing Systems
A new analysis of the false positive rate of a Bloom filter
Information Processing Letters
The deletable bloom filter: a new member of the bloom family
IEEE Communications Letters
Approximately Detecting Duplicates for Probabilistic Data Streams over Sliding Windows
PAAP '10 Proceedings of the 2010 3rd International Symposium on Parallel Architectures, Algorithms and Programming
A Generalized Bloom Filter to Secure Distributed Network Applications
Computer Networks: The International Journal of Computer and Telecommunications Networking
Detecting Duplicates over Sliding Windows with RAM-Efficient Detached Counting Bloom Filter Arrays
NAS '11 Proceedings of the 2011 IEEE Sixth International Conference on Networking, Architecture, and Storage
One is enough: distributed filtering for duplicate elimination
Proceedings of the 20th ACM international conference on Information and knowledge management
| Hi-index | 0.00 |
Time-Decaying Bloom Filters are efficient, probabilistic data structures used to answer queries on recently inserted items. As new items are inserted, memory of older items decays. Incorrect query responses incur penalties borne by the application using the filter. Most existing filters may only be tuned to static penalties, and they ignore Bayesian priors and information latent in the filter. We address these issues in an integrated way by converting existing filters into inferential filters. Inferential filters combine latent filter information with Bayesian priors to make query-specific optimal decisions. Our methods are applicable to any Bloom Filter, but we focus on developing inferential time-decaying filters, which support new query types and sliding window queries with varying error penalties. We develop the inferential version of the existing Timing Bloom Filter. Through experiments on real and synthetic datasets, we show that when penalties are query-specific and prior probabilities are known, the inferential Timing Bloom Filter reduces penalties for incorrect responses to sliding-window queries by up to 70%.