The multicast policy and its relationship to replicated data placement
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Optimal Placement of Replicas in Trees with Read, Write, and Storage Costs
IEEE Transactions on Parallel and Distributed Systems
Optimal Placement of Replicas in Data Grid Environments with Locality Assurance
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
Optimal replica placement in hierarchical Data Grids with locality assurance
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A QoS-Aware Heuristic Algorithm for Replica Placement
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QoS-aware, access-efficient, and storage-efficient replica placement in grid environments
The Journal of Supercomputing
Server placement in the presence of competition
GPC'07 Proceedings of the 2nd international conference on Advances in grid and pervasive computing
Optimizing server placement in distributed systems in the presence of competition
Journal of Parallel and Distributed Computing
QoS-aware replica placement for grid computing
Concurrency and Computation: Practice & Experience
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The architecture of overlay networks should support high-performance and high-scalability at low costs. This becomes more crucial when communication, storage costs as well as service latencies grow with the exploding amounts of data exchanged and with the size and span of the overlay network. For that end, multicast methodologies can be used to deliver content from regional servers to end users, as well as for the timely and economical synchronization of content among the distributed servers. Another important architectural problem is the efficient allocation of objects to servers to minimize storage, delivery and update costs. In this work, we suggest a multicast based architecture and address the optimal allocation and replication of dynamic objects that are both consumed and updated. Our model network includes consumers which are served using multicast or unicast transmissions and media sources (that may be also consumers) which update the objects using multicast communication. General costs are associated with distribution (download) and update traffic as well as the storage of objects in the servers. Optimal object allocation algorithms for tree networks are presented with complexities of O(N) and O(N2) in case of multicast and unicast distribution respectively. To our knowledge, the model of multicast distribution combined with multicast updates has not been analytically dealt before, despite its popularity in the industry.