Carbon offsetting through computer network redesign

Sustaining green communications in digital data transmission is gaining prime importance, as the 24/7 access networks contribute large electrical power consumption. Presently, the increased number of digital transactions in most of the enterprise network (EN) tremendously increases the volume of data transmitted through out the EN at all the time that would increase the electrical power consumption. We have proposed few operations to redesign the clusters of an enterprise network and we have modeled the cluster redesign problem as an optimization problem and utilized Simulated Annealing (SA) to search for the best re-clustering to reduce traffic at the backbone. The two redesign operations move node and swap nodes as the neighborhood functions in Simulated Annealing are utilized to reduce the traffic at the backbone of the enterprise network and we have extended our algorithm to prove that the decrease in volume of traffic at the backbone decreases the power consumption. We have selected Manchester coding to encode the generated and transmitted data, and it is our basic model to estimate the utilized power. Our simulation results demonstrate that an overall reduction in the backbone traffic after the redesign operations decreases the power consumption by 13% and 3.7% in move node and swap nodes operation, thus offsetting the carbon emissions per year by 45% and 13% respectively.