Optimal allocation of electronic content

60Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

Abstract

The delivery of large files to single users, such as application programs for some versions of the envisioned network computer, or movies, is expected by many to be one of the main requirements of communication networks. This requires expensive high bandwidth capacity as well as fast and high storage servers. This motivates multimedia providers to optimize the delivery distances, as well as the electronic content allocation. A hierarchical architecture for providing the multimedia content was introduced by Nussbaumer, Patel, Schaffa, and Sternbenz (INFOCOM 94). They also introduced the trade-off between bandwidth and storage requirements for the placement of the content servers on the hierarchy tree. They found the best level of the hierarchy for the server location to minimize the total of the costs of communication and storage. Their algorithm is centralized. We solve the more general case where servers can be located at different levels of the hierarchy. Our algorithm is distributed, and each node requires a limited memory capacity and computational power. Results for related approaches to caching design are of higher complexity. Results for related classic Operations Research problems are for centralized algorithms, mostly linear programming, that are not easy to convert into distributed algorithms. Instead, we observe that the use of dynamic programming is more natural for distributed implementations. For the specific problem at hand, we also managed to find a natural function (a generalization of the problem) that simplifies the combination operation used in dynamic programming. We also show how to map such contemporary problems to the area of classical plant location problems in Operations Research.

Cite

CITATION STYLE

APA

Cidon, I., Kutten, S., & Soffer, R. (2001). Optimal allocation of electronic content. In Proceedings - IEEE INFOCOM (Vol. 3, pp. 1773–1780). https://doi.org/10.1109/infcom.2001.916675

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free