Data allocation in distributed database systems
ACM Transactions on Database Systems (TODS)
Algorithmic mechanism design (extended abstract)
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
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IEEE/ACM Transactions on Networking (TON)
Allocating Data and Operations to Nodes in Distributed Database Design
IEEE Transactions on Knowledge and Data Engineering
An Overview of Data Replication on the Internet
ISPAN '02 Proceedings of the 2002 International Symposium on Parallel Architectures, Algorithms and Networks
Static and adaptive distributed data replication using genetic algorithms
Journal of Parallel and Distributed Computing
IEEE Communications Magazine
Design and evaluation of data allocation algorithms for distributed multimedia database systems
IEEE Journal on Selected Areas in Communications
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
Comparison and analysis of ten static heuristics-based Internet data replication techniques
Journal of Parallel and Distributed Computing
Distributed and Parallel Databases
Mosaic-Net: a game theoretical method for selection and allocation of replicas in ad hoc networks
The Journal of Supercomputing
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This paper addresses the problem of fine-grained data replication in large distributed systems, such as the Internet, so as to minimize the user access delays. With fine-grained data replication, certain data objects, as opposed to a complete site, are duplicated at multiple servers. In this paper, we abstract the distributed system as an agent-based model wherein mobile agents on behalf of their nodes continuously compete for allocation and reallocation of data objects. However, since these agents do not have a global view of the system, the optimization process becomes highly local. This localization may encourage these selfish agents to alter the output of the resource allocation mechanism in their favor by misreporting critical data such as the objects' popularity. This paper proposes a game theoretical resource allocation mechanism involving selfish agents. The mechanism ensures that the agents do not misreport, always follow the rules, and that a global optima is achieved. The mechanism is extensively evaluated against some wellknown algorithms, such as: greedy, branch and bound, game theoretical auctions and genetic algorithms. The experimental results reveal that the mechanism provides excellent solution quality, while maintaining fast execution time.