Traffic in telecom networks is increasing rapidly, and it has been a challenging task to plan and upgrade network capacities for this increasing traffic, keeping the cost of resources within a targeted budget. Besides handling this drastic growth in traffic, future optical networks are also expected to be increasingly heterogeneous with respect to services supported and underlying technologies employed. To support this heterogeneous volume of traffic, mixed-line-rate (MLR) optical networks with line rates of 10, 40, and 100 Gbps have been shown to be effective. In the case of a greenfield network design, i.e., when planning capacities for a new network, MLR networks have been shown to be cost efficient as well as energy efficient in some recent studies. The concept of an MLR network is evolutionary, starting from a 10G single-line-rate network to a coexistence of multiple line rates in the same network as capacities on some links are periodically upgraded from 10G per wavelength to 40G and 100G per wavelength with traffic growth. Therefore, from a network-upgrade perspective, an important issue is to devise a cost-optimized migration strategy from 10G to 40G to 100G and beyond, given a traffic growth model. However, energy consumption in different elements in the network, especially in those elements whose energy consumption depends on the bandwidth of the traffic that they are handling, is also an important parameter to consider. Therefore, the ultimate question is: Can an MLR be a good candidate for energy-efficient and cost-efficient upgrade? In this study, we investigate the energy-efficient and cost-efficient MLR network-upgrade problem. In this context, we also study the effect of network connection disruption on energy-efficient and cost-efficient MLR network upgrade. In general, the service provider’s aim would be to have as few disruptions as possible during capacity upgrade, as disruptions may induce service degradation. Our results show that the amount of disruptions has a conflicting effect on energy-efficient and cost-efficient upgrade in MLR networks, and we develop an optimized upgrade strategy so that both cost and energy are kept within a certain limit.
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