Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
New sampling-based summary statistics for improving approximate query answers
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
New directions in traffic measurement and accounting
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Maintaining stream statistics over sliding windows: (extended abstract)
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Gigascope: high performance network monitoring with an SQL interface
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Computing Iceberg Queries Efficiently
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Finding Frequent Items in Data Streams
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Frequency Estimation of Internet Packet Streams with Limited Space
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
What's hot and what's not: tracking most frequent items dynamically
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Issues in data stream management
ACM SIGMOD Record
Supporting sliding window queries for continuous data streams
SSDBM '03 Proceedings of the 15th International Conference on Scientific and Statistical Database Management
Tribeca: a system for managing large databases of network traffic
ATEC '98 Proceedings of the annual conference on USENIX Annual Technical Conference
Approximate frequency counts over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
StatStream: statistical monitoring of thousands of data streams in real time
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Identifying elephant flows through periodically sampled packets
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Duplicate detection in click streams
WWW '05 Proceedings of the 14th international conference on World Wide Web
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
An integrated efficient solution for computing frequent and top-k elements in data streams
ACM Transactions on Database Systems (TODS)
Data streams: algorithms and applications
Foundations and Trends® in Theoretical Computer Science
Variance estimation over sliding windows
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Progressive ranking of range aggregates
Data & Knowledge Engineering
Short communication: TOPSIS: Finding Top-K significant N-itemsets in sliding windows adaptively
Knowledge-Based Systems
Mining frequent items in a stream using flexible windows
Intelligent Data Analysis - Knowledge Discovery from Data Streams
FIDS: Monitoring Frequent Items over Distributed Data Streams
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Adaptive shared-state sampling
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Frequent items in streaming data: An experimental evaluation of the state-of-the-art
Data & Knowledge Engineering
Data Mining and Knowledge Discovery
Optimal sampling from sliding windows
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Counting Flows over Sliding Windows in High Speed Networks
NETWORKING '09 Proceedings of the 8th International IFIP-TC 6 Networking Conference
Competitive Analysis of Aggregate Max in Windowed Streaming
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Approximate Frequent Itemset Discovery from Data Stream
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
An execution environment for C-SPARQL queries
Proceedings of the 13th International Conference on Extending Database Technology
Sampling-based stream mining for network risk management
JSAI'06 Proceedings of the 20th annual conference on New frontiers in artificial intelligence
Aggregate computation over data streams
APWeb'08 Proceedings of the 10th Asia-Pacific web conference on Progress in WWW research and development
Supporting top-k aggregate queries over unequal synopsis on internet traffic streams
APWeb'08 Proceedings of the 10th Asia-Pacific web conference on Progress in WWW research and development
A new algorithm for mining global frequent itemsets in a stream
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
The frequent items problem, under polynomial decay, in the streaming model
Theoretical Computer Science
Querying RDF streams with C-SPARQL
ACM SIGMOD Record
TOPSIL-Miner: an efficient algorithm for mining top-K significant itemsets over data streams
Knowledge and Information Systems
DevoFlow: scaling flow management for high-performance networks
Proceedings of the ACM SIGCOMM 2011 conference
Optimal sampling from sliding windows
Journal of Computer and System Sciences
Progressive ranking of range aggregates
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Querying sliding windows over online data streams
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Net-cohort: detecting and managing VM ensembles in virtualized data centers
Proceedings of the 9th international conference on Autonomic computing
International Journal of Data Mining and Bioinformatics
Size matters: finding the most informative set of window lengths
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
Scalable identification and measurement of heavy-hitters
Computer Communications
Using a real-time top-k algorithm to mine the most frequent items over multiple streams
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories
Stream mining on univariate uncertain data
Applied Intelligence
Mining frequent itemsets in a stream
Information Systems
Mining frequent items in data stream using time fading model
Information Sciences: an International Journal
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Internet traffic patterns are believed to obey the power law, implying that most of the bandwidth is consumed by a small set of heavy users. Hence, queries that return a list of frequently occurring items are important in the analysis of real-time Internet packet streams. While several results exist for computing frequent item queries using limited memory in the infinite stream model, in this paper we consider the limited-memory sliding window model. This model maintains the last $N$ items that have arrived at any given time and forbids the storage of the entire window in memory. We present a deterministic algorithm for identifying frequent items in sliding windows defined over real-time packet streams. The algorithm uses limited memory, requires constant processing time per packet (amortized), makes only one pass over the data, and is shown to work well when tested on TCP traffic logs.