In this paper, routing optimizations based on energy sources are proposed in dynamic GMPLS controlled optical networks. The influences of re-routing and load balancing factors on the algorithm are evaluated, with a focus on different re-routing thresholds. Results from dynamic network simulations show that re-routing strategies can lower CO 2 emissions compared to the basic energy source routing scheme, and a lower re-routing threshold achieves more savings. The increased blocking probability brought by using re-routing schemes can be compensated by applying load balancing criteria. A trade-off between blocking probability and obtained CO 2 savings is studied. Keywords: GMPLS, optical networks, energy-efficient, re-routing. With the rapid growth of the network bandwidth demand in the past years, concerns have arisen due to the accompanied growing energy consumption. The network components (routers, transponders, ROADMs, amplifiers, etc.) are becoming significant contributors to the greenhouse gas emissions. As an example, a 1 kW router powered by a coal power plant can contribute to 8.6 tons of CO 2 emissions per year [1] . Thus, if the network traffic can be monitored to go through green routes (routes which use green energy sources such as wind or solar), the CO 2 emissions can be greatly reduced. The recent development in Smart Grid technology has made it possible to select the type of energy sources (solar, wind, fuel, coal, etc.) used for network components, and some research has been done to employ green energy sources to reduce the network energy consumption, as in [2] [3] [4] . Ideas regarding re-routing strategies are also mentioned in [5] , where the author focuses on turning off links in the network. The results are given in a static environment. Similar work done in [6] also aims at turning off unused links. However, the majority of the work done in the optical networking field is for a static network environment, with time-consuming optimization methods, such as linear programming. In this paper, a pure energy source aware (ESA) routing algorithm (routing decision based on the path with most green energy sources) is implemented to solve such issues in Generalized Multi-protocol Label Switching (GMPLS) [7] controlled dynamic optical core networks. Open Shortest Path First -Traffic Engineering (OSPF-TE) [8] is used as routing protocol, and Resource Reservation Protocol -Traffic Engineering (RSVP-TE) [9] is used as signalling protocol. In the considered environment, it is difficult to use the traditional optimization methods for improving the sub-optimal results, due to the unpredictability of the traffic pattern, the dynamically changing energy sources and the need for a fast convergence routing protocol. In this paper, besides presenting the results of ESA routing algorithm, with randomly changing energy sources (green and dirty), several optimization criteria are exploited under different energy source changing intervals, such as applying re-routing policies when a energy source has changed during the connection duration and the employment of load balancing factors in helping with the connection blocking rate. To the authors' best knowledge, this paper is one of the first works addressing these issues in a dynamic environment with re-optimization and load-balancing criteria. The remainder of the paper is organized as follows. Section 2 presents the energy model used for estimating CO 2 emissions; implementation environment is described in Section 3; simulation results are illustrated in Section 4; and conclusions are given in Section 5.
The work in REF has introduced values for different types of energy sources to calculate the amount of consumed energy in terms of the amount of emission.
Energy-aware routing optimization in dynamic GMPLS controlled optical networks
2012 14th International Conference on Transparent Optical Networks (ICTON)
2012 14th International Conference on Transparent Optical Networks (ICTON)
Computer Science