In optical WDM networks, an assignment of transceivers to channels implies an allocation of the bandwidth to the various network nodes. Intuition suggests, and our recent study has confirmed, that if the traffic load is not well balanced across the available channels, the result is poor network performance. Hence, the time-varying conditions expected in this type of environment call for mechanisms that periodically adjust the bandwidth allocation to ensure that each channel carries an almost equal share of the corresponding offered load. In this paper we study the problem of dynamic load balancing in broadcast WDM networks by retuning a subset of transceivers in response to changes in the overall traffic pattern. Assuming an existing wavelength assignment and some information regarding the new traffic demands, we present two approaches to obtaining a new wavelength assignment such that (a) the new traffic load is balanced across the channels, and (b) the number of transceivers that need to be retuned is minimized. The latter objective is motivated by the fact that tunable transceivers take a non-negligible amount of time to switch between wavelengths during which parts of the network are unavailable for normal operation. Furthermore, this variation in traffic is expected to take place over larger time scales (i.e., retuning will be a relatively infrequent event), making slowly tunable devices a cost effective solution. Our main contribution is a new approximation algorithm for the load balancing problem that provides for tradeoff selection, using a single parameter, between two conflicting goals, namely, the degree of load balancing and the number of transceivers that need to be retuned. This algorithm leads to a scalable approach to reconfiguring the network since, in addition to providing guarantees in terms of load balancing, the expected number of retunings scales with the number of channels, not the number of nodes in the network.
Photonic Network Communications – Springer Journals
Published: Oct 19, 2004
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
All the latest content is available, no embargo periods.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud