The SEQUOIA 2000 storage benchmark
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
The Management of Probabilistic Data
IEEE Transactions on Knowledge and Data Engineering
XMach-1: A Benchmark for XML Data Management
Datenbanksysteme in Büro, Technik und Wissenschaft (BTW), 9. GI-Fachtagung,
GADT: A Probability Space ADT for Representing and Querying the Physical World
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
MauveDB: supporting model-based user views in database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
The CQL continuous query language: semantic foundations and query execution
The VLDB Journal — The International Journal on Very Large Data Bases
ULDBs: databases with uncertainty and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Fuzzy Databases: Modeling, Design, and Implementation
Fuzzy Databases: Modeling, Design, and Implementation
XMark: a benchmark for XML data management
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Linear road: a stream data management benchmark
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
An adaptive RFID middleware for supporting metaphysical data independence
The VLDB Journal — The International Journal on Very Large Data Bases
Orion 2.0: native support for uncertain data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Cascadia: A System for Specifying, Detecting, and Managing RFID Events
Proceedings of the 6th international conference on Mobile systems, applications, and services
Managing Probabilistic Data with MystiQ: The Can-Do, the Could-Do, and the Can't-Do
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
Database Support for Probabilistic Attributes and Tuples
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Online Filtering, Smoothing and Probabilistic Modeling of Streaming data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
MayBMS: a probabilistic database management system
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Approximate initialization of camera sensor networks
EWSN'07 Proceedings of the 4th European conference on Wireless sensor networks
PODS: a new model and processing algorithms for uncertain data streams
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
AINTEC'06 Proceedings of the Second Asian international conference on Technologies for Advanced Heterogeneous Networks
Xtream: a system for continuous querying over uncertain data streams
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
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Inherent imprecision of data streams in many applications leads to need for real-time uncertainty management. The new emerging Probabilistic Data Stream Management Systems (PDSMSs) are being developed to handle uncertainties of data streams in real-time. Many approaches have been proposed so far but there is no way to compare them regarding precision and efficiency. This problem motivated us to design an evaluation framework to compare performance and accuracy of PDSMSs with each other and also with probabilistic databases. In this paper, after a brief introduction to PDSMSs, we describe requirements and challenges for designing a PDSMS benchmark. Then, we present different parts of our framework including probabilistic data stream generator, queries, and result evaluator. Furthermore, we focus on implementation aspects and use our framework to evaluate effects of floating precision in our PDSMS prototype.