English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Motivated by the massive deployment of power-hungry data centers for serviceprovisioning, we examine the problem of routing in optical networks with theaim of minimizing traffic-driven power consumption. To tackle this issue,routing must take into account energy efficiency as well as capacityconsiderations; moreover, in rapidly-varying network environments, this must beaccomplished in a real-time, distributed manner that remains robust in thepresence of random disturbances and noise. In view of this, we derive a pricingscheme whose Nash equilibria coincide with the network's socially optimumstates, and we propose a distributed learning method based on the Boltzmanndistribution of statistical mechanics. Using tools from stochastic calculus, weshow that the resulting Boltzmann routing scheme exhibits remarkableconvergence properties under uncertainty: specifically, the long-term averageof the network's power consumption converges within $\varepsilon$ of itsminimum value in time which is at most $\tilde O(1/\varepsilon^2)$,irrespective of the fluctuations' magnitude; additionally, if the networkadmits a strict, non-mixing optimum state, the algorithm converges to it -again, no matter the noise level. Our analysis is supplemented by extensivenumerical simulations which show that Boltzmann routing can lead to asignificant decrease in power consumption over basic, shortest-path routingschemes in realistic network conditions.

Boltzmann meets Nash: Energy-efficient routing in optical networks under uncertainty