Placement algorithms for hierarchical cooperative caching
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
IEEE/ACM Transactions on Networking (TON)
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Replication Algorithms in a Remote Caching Architecture
IEEE Transactions on Parallel and Distributed Systems
Joint object placement and node dimensioning for internet content distribution
Information Processing Letters
Selfish caching in distributed systems: a game-theoretic analysis
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Static and adaptive distributed data replication using genetic algorithms
Journal of Parallel and Distributed Computing
On the optimization of storage capacity allocation for content distribution
Computer Networks: The International Journal of Computer and Telecommunications Networking
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
A survey of autonomic communications
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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A commonly employed abstraction for studying the object placement problem for the purpose of Internet content distribution is that of a distributed replication group. In this work the initial model of distributed replication group of Leff, Wolf, and Yu (IEEE TPDS '93) is extended to the case that individual nodes act selfishly, i.e., cater to the optimization of their individual local utilities. Our main contribution is the derivation of equilibrium object placement strategies that: (a) can guarantee improved local utilities for all nodes concurrently as compared to the corresponding local utilities under greedy local object placement; (b) do not suffer from potential mistreatment problems, inherent to centralized strategies that aim at optimizing the social utility; (c) do not require the existence of complete information at all nodes. We develop a baseline computationally efficient algorithm for obtaining the aforementioned equilibrium strategies and then extend it to improve its performance with respect to fairness. Both algorithms are realizable in practice through a distributed protocol that requires only limited exchange of information.