Discrete cosine transform: algorithms, advantages, applications
Discrete cosine transform: algorithms, advantages, applications
Probabilistic methods in query processing
Probabilistic methods in query processing
Adaptive selectivity estimation using query feedback
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Balancing histogram optimality and practicality for query result size estimation
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Wavelet-based histograms for selectivity estimation
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Multi-dimensional selectivity estimation using compressed histogram information
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
The interpolation-based grid file
PODS '85 Proceedings of the fourth ACM SIGACT-SIGMOD symposium on Principles of database systems
STHoles: a multidimensional workload-aware histogram
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Optimal Histograms with Quality Guarantees
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Universality of Serial Histograms
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
Sampling-Based Estimation of the Number of Distinct Values of an Attribute
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems
Middleware '01 Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms Heidelberg
Gossip-Based Computation of Aggregate Information
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Mercury: supporting scalable multi-attribute range queries
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Supporting Multi-Dimensional Range Queries in Peer-to-Peer Systems
P2P '05 Proceedings of the Fifth IEEE International Conference on Peer-to-Peer Computing
Approximating Aggregation Queries in Peer-to-Peer Networks
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Distributed Data Mining in Peer-to-Peer Networks
IEEE Internet Computing
Distributed Density Estimation Using Non-parametric Statistics
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
Efficient Data Sampling in Heterogeneous Peer-to-Peer Networks
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
AP2PC'03 Proceedings of the Second international conference on Agents and Peer-to-Peer Computing
RETRACTED: Impacts of sensor node distributions on coverage in sensor networks
Journal of Parallel and Distributed Computing
Personalized query evaluation in ring-based P2P networks
Information Sciences: an International Journal
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Estimating the global data distribution in Peer-to-Peer (P2P) networks is an important issue and has not yet been well addressed. It can benefit many P2P applications, such as load balancing analysis, query processing, data mining, and so on. In this paper, we propose a novel algorithm which is based on compact multi-dimensional histogram information to achieve high estimation accuracy with low estimation cost. Maintaining data distribution in a multi-dimensional histogram which is spread among peers without overlapping and each part of which is further condensed by a set of discrete cosine transform coefficients, each peer is capable to hierarchically accumulate the compact information to the entire histogram by information exchange and consequently estimates the global data density with accuracy and efficiency. Algorithms on discrete cosine transform coefficients hierarchically accumulating as well as density estimation error are introduced with detailed theoretical analysis and proof. Our extensive performance study confirms the effectiveness and efficiency of our methods on density estimation in dynamic P2P networks.