A survey of adaptive sorting algorithms
ACM Computing Surveys (CSUR)
On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Computer networks: a systems approach
Computer networks: a systems approach
Packet reordering is not pathological network behavior
IEEE/ACM Transactions on Networking (TON)
Deriving traffic demands for operational IP networks: methodology and experience
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
On the nonstationarity of Internet traffic
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
SNMP,SNMPV2,Snmpv3,and RMON 1 and 2
SNMP,SNMPV2,Snmpv3,and RMON 1 and 2
Self-Similar Network Traffic and Performance Evaluation
Self-Similar Network Traffic and Performance Evaluation
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
On the autocorrelation structure of TCP traffic
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Advances in modeling and engineering of Longe-Range dependent traffic
On the autocorrelation structure of TCP traffic
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Advances in modeling and engineering of Longe-Range dependent traffic
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
New directions in traffic measurement and accounting: Focusing on the elephants, ignoring the mice
ACM Transactions on Computer Systems (TOCS)
Gigascope: a stream database for network applications
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
On TCP and self-similar traffic
Performance Evaluation - Long range dependence and heavy tail distributions
A multifractal wavelet model with application to network traffic
IEEE Transactions on Information Theory
Counting preimages of TCP reordering patterns
Discrete Applied Mathematics
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We propose a new methodology, Restored, for model-based storage and regeneration of TCP traces. Restored provides significant data compression by exploiting semantics of TCP. Experiments show that Restored can achieve over 10,000-fold compression ratios for some really large input connections, while still being able to recover several structural and QoS measures.