Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
PREFER: a system for the efficient execution of multi-parametric ranked queries
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Relational data sharing in peer-based data management systems
ACM SIGMOD Record
Optimizing Top-k Selection Queries over Multimedia Repositories
IEEE Transactions on Knowledge and Data Engineering
Efficient top-K query calculation in distributed networks
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Progressive Distributed Top-k Retrieval in Peer-to-Peer Networks
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
KLEE: a framework for distributed top-k query algorithms
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Reducing network traffic in unstructured P2P systems using Top-k queries
Distributed and Parallel Databases
Efficient top-k processing in large-scaled distributed environments
Data & Knowledge Engineering
Summary management in P2P systems
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
On efficient top-k query processing in highly distributed environments
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Best-Effort Top-k Query Processing Under Budgetary Constraints
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Top-k generation of integrated schemas based on directed and weighted correspondences
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
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Top-k query processing in P2P systems has focused on efficiently computing the top-k results while reducing network traffic and query response time. However, in overloaded P2P systems (with very high query loads), some peers may take a long time to answer, thus making the user wait a long time to obtain the final top-k result. In this paper, we address this problem, which we reformulate as early top-k query processing in P2P systems. First, to complement response time, we introduce two new metrics, stabilization time and cumulative quality gap, with which we formally define the problem. Then, we propose an efficient algorithm that dynamically adapts to query loads of peers in order to return to the user top-k results as soon as possible, without waiting for the final result. We validated our solution through simulations over a real dataset. The results show that our algorithm significantly outperforms baseline algorithms by returning high quality top-k results to users in much better times.