Section: New Results
Specific studies: Distributed optimization in network management
Participant : Eric Fabre.
This work represents part of our activities within the research group “High Manageability,” supported by the common lab of Alcatel-Lucent Bell Labs (ALBLF) and INRIA. It concerns a key issue for the autonomic management of photonic networks, i.e. optically routed networks. The problem concerns the fine tuning of wavelength reamplification gains at the input of each fiber, in order to optimize the optical signal to noise ratio (OSNR) at egress of the connection. The tuning of these gains directly influences the reach of a connection, that is the distance over which the signal can be transported optically, without necessity of an electronic regeneration. This in turn has a direct financial impact since less equipment is needed.
The problem is made complex by several phenomena. First of all, the total amount of power allowed in a fiber is limited (or equivalently each optical cross-connect has a bounded power budget). This implies that each node must select which wavelengths will be reamplified, and by how much. Secondly, the per-wavelength amplification gains are themselves limited, so an important loss on some connection in a link may have to be compensated for by several consecutive reamplifications along this connection. These two phenomena, combined with other non-linear effects, make this optimal tuning of gains a huge and complex network-scale optimization problem under constraints. The objective function is of course to maximize the OSNR of all connections in the network, and at the same time equalize these OSNR, so that long-range connections have the same quality as short range ones. For the moment, all these gains are manually adjusted, one by one, which is extremely difficult and suboptimal.
We have designed and tested an iterative and distributed solution to solve this problem: Each optical cross-connect in the network tunes its own reamplification gains, based on information provided by its neighbors. No global topology information is necessary, and convergence is guaranteed. The algorithm is adaptive to network changes: it redistributes optimally the power left by closed connections, and symmetrically pumps power in the less important connections to feed a newly created one.
Two patents have been derived from this work, jointly registered by ALBLF and INRIA. This delayed the publication work, that will take place in 2009. A demo of the prototype solution was performed at the Alcatel-Lucent Innovation Days, June 2009.
