Efficient algorithms for the capacitated concentrator location problem
Computers and Operations Research
Minimum cost capacity installation for multicommodity network flows
Mathematical Programming: Series A and B - Special issue on computational integer programming
Appia: Automatic Storage Area Network Fabric Design
FAST '02 Proceedings of the Conference on File and Storage Technologies
On the Design Problem of Multitechnology Networks
INFORMS Journal on Computing
Single-source unsplittable flow
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Routing, Flow, and Capacity Design in Communication and Computer Networks
Routing, Flow, and Capacity Design in Communication and Computer Networks
Solving the hub location problem with modular link capacities
Computers and Operations Research - Articles presented at the conference on routing and location (CORAL)
Optimization of Teleprocessing Networks with Concentrators and Multiconnected Terminals
IEEE Transactions on Computers
Core-Edge design of storage area networks-A Single-edge formulation with problem-specific cuts
Computers and Operations Research
Designing data storage tier using Integer Programing
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Benchmarking and modeling disk-based storage tiers for practical storage design
ACM SIGMETRICS Performance Evaluation Review
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In this paper we address the problem of optimal network design for a storage area network. We consider the Core-Edge reference topology and present two formulations for the Core-Edge storage area network design problem. One formulation excludes explicit host/device connections to the edge (as is common in currently available heuristics), the other includes these connections to allow the modeling of multiple disjoint paths between hosts and devices. These formulations include generic component types to reduce the number of constraints and variables, with the properties of these components being determined as part of the solution process. The size of the formulation is further reduced by a preprocessing method that removes suboptimal switches and links from consideration. We test our formulations on a randomly generated set of problems, all of which are of a size consistent with those encountered in industry. We generate solutions using our two formulations for all test problems in good time. Finally we apply a relaxation of one of our formulations to re-configure the Cecil back-end network, which is currently used across the University of Auckland. We present two designs for the re-configured network to significantly increase reliability and scalability.