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Deployment Versus Data Retrieval Costs for Caches in the Plane

机译:平面中缓存的部署与数据检索成本

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We consider the problem of finding the Pareto front of the expected deployment cost of wireless caches in the plane and the expected retrieval cost of a client requesting data from the caches. The data is stored at the caches according to partitioning and coding strategies. We show that under coding, it is optimal to deploy many caches with low storage capacity. For partitioning, we derive a simple relation between the cost of the cache deployment and the cost of retrieving the data from the caches. We quantify the improvements offered by optimal coding in comparison to partitioning, i.e., we derive a relation for the difference in deployment cost required to achieve a given retrieval cost. Finally, we show that even non-optimal coding is better than partitioning in the sense that no coded deployment can be dominated by a partitioning strategy.
机译:我们考虑以下问题:找到平面中无线缓存的预期部署成本和客户端从缓存中请求数据的预期检索成本的Pareto前沿。数据根据分区和编码策略存储在高速缓存中。我们表明,在编码下,最佳的做法是部署许多存储容量低的缓存。对于分区,我们得出了缓存部署成本和从缓存中检索数据的成本之间的简单关系。我们量化了与分区相比最优编码所提供的改进,即我们得出了实现给定检索成本所需的部署成本差异的关系。最后,我们证明,即使没有优化的编码,也比分区更好,因为没有编码部署可以由分区策略主导。

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