Fast, efficient equipment placement heuristics for broadband switched or Internet router networks

Fast, efficient equipment placement heuristics for broadband switched or Internet router networks

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Article ID: iaor20002651
Country: United States
Volume: 6
Issue: 1
Start Page Number: 39
End Page Number: 64
Publication Date: Jan 2000
Journal: Journal of Heuristics
Authors:
Keywords: heuristics, communications
Abstract:

Planning and designing the next generation of IP router or switched broadband networks seems a daunting challenge considering the many complex, interacting factors affecting the performance and cost of such networks. Generally, this complexity implies that it may not even be clear what constitutes a ‘good’ network design for a particular specification. Different network owners or operators may view the same solution differently, depending on their unique needs and perspectives. Nevertheless, we have observed a core common issue arising in the early stages of network design efforts involving leading-edge broadband switched technologies such as ATM, Frame Relay, and SMDS; or even Internet IP router networks. This core issue can be stated as follows: Given a set of service demands for the various network nodes, where should switching or routing equipment be placed to minimize the Installed First Cost of the network? Note that the specified service demands are usually projections for a future scenario and generally entail significant uncertainty. Despite this uncertainty, we have found that network owners and operators generally feel it is worthwhile to obtain high-level advice on equipment placement with a goal of minimizing Installed First Cost. This paper reports on a heuristic approach we have implemented for this problem that has evolved out of real network design projects. A tool with both a Solution Engine and an intuitive Graphical User Interface has been developed. The approach is highly efficient, for example, the tool can often handle LATA-sized networks in seconds or less on a workstation processor. By using only nodal demands rather than the more complex point-to-point demands usually required in tools of this sort, we have created an approach that is not only highly efficient, but is also a better match to real design projects in which demand data are generally scant and highly uncertain.

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