SIAM Journal on Applied Mathematics
IEEE Internet Computing
Can Heterogeneity Make Gnutella Scalable?
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
A simple algorithm for finding frequent elements in streams and bags
ACM Transactions on Database Systems (TODS)
Adaptive filters for continuous queries over distributed data streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Gossip-Based Computation of Aggregate Information
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Epidemic-Style Proactive Aggregation in Large Overlay Networks
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
Finding (Recently) Frequent Items in Distributed Data Streams
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Gossip-based aggregation in large dynamic networks
ACM Transactions on Computer Systems (TOCS)
Decentralized Schemes for Size Estimation in Large and Dynamic Groups
NCA '05 Proceedings of the Fourth IEEE International Symposium on Network Computing and Applications
Efficient gossip-based aggregate computation
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Communication-efficient distributed monitoring of thresholded counts
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Peer counting and sampling in overlay networks: random walk methods
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Transactions on Parallel and Distributed Systems
Approximate frequency counts over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Asynchronous distributed averaging on communication networks
IEEE/ACM Transactions on Networking (TON)
The promise, and limitations, of gossip protocols
ACM SIGOPS Operating Systems Review - Gossip-based computer networking
Modeling Heterogeneous User Churn and Local Resilience of Unstructured P2P Networks
ICNP '06 Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols
Aggregation methods for large-scale sensor networks
ACM Transactions on Sensor Networks (TOSN)
Computing Frequent Elements Using Gossip
SIROCCO '08 Proceedings of the 15th international colloquium on Structural Information and Communication Complexity
Identifying Frequent Items in P2P Systems
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
On unbiased sampling for unstructured peer-to-peer networks
IEEE/ACM Transactions on Networking (TON)
Finding the frequent items in streams of data
Communications of the ACM - A View of Parallel Computing
Grid broker selection strategies using aggregated resource information
Future Generation Computer Systems
An analytical framework for self-organizing peer-to-peer anti-entropy algorithms
Performance Evaluation
Handling dynamics in diffusive aggregation schemes: An evaporative approach
Future Generation Computer Systems
Computer Networks: The International Journal of Computer and Telecommunications Networking
Network sampling and classification: An investigation of network model representations
Decision Support Systems
Peer-to-peer based multimedia distribution service
IEEE Transactions on Multimedia
Scheduling efficiency of resource information aggregation in grid networks
Future Generation Computer Systems
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We address the problem of discovering frequent items in unstructured P2P networks which is relevant for several distributed services such as cache management, data replication, query refinement, topology optimization and security. This study makes the following contributions to the current state of the art. First, we propose and develop a fully distributed Protocol for Frequent Items Discovery (ProFID) where the result is produced at every peer. ProFID uses gossip-based (epidemic) communication, a novel pairwise averaging function and system size estimation together to discover frequent items in an unstructured P2P network. We also propose a practical rule for convergence of the algorithm. In contrast to the previous works, each peer gives a local decision for convergence based on the change of updated local state. We developed a model of ProFID in PeerSim and performed various experiments to compare and evaluate its efficiency, scalability, and applicability. The protocol's resilience under realistic churn models was studied. For evaluating the effect of network dynamics, we deployed our protocol on the Internet-scale real network PlanetLab. We also compared the accuracy and scalability of ProFID with the adaptive Push-Sum algorithm. Our results confirm the practical nature, ease of deployment and efficiency of our approach, and also show that it outperforms adaptive Push-Sum in terms of accuracy, convergence speed and message overhead.