Term Project Green Routing

Introduction:
Traditional routing protocols and techniques are often used in today's networks, and their basics were generally established before the millennium. In recent years, the network area has not experienced the same level of fast transformation as other IT industries. With the development of the digital world and the introduction of new industries and technologies like 5G and cloud computing, the volume of data transferred through networks today is massive and will continue to expand in the future. Modern networks must not only deal with an unprecedented amount of data transmissions, but many new requirements have emerged in order to meet client demands. In our time with climate change a new requirement on the energy efficiency of routing was developed.

Problem:
Ecological aspects are becoming increasingly important in our world. The latest estimates for the ICT sector indicate emissions of around 1.4Gt of CO[sub]2[/sub] per year. Internet backbone networks are responsible for six percent of this ecological footprint. The growing bandwidth creates new opportunities to consider other metrics and aspects in addition to the traditional ones which mostly only tend to use more and more bandwidths. A new possibility of this is to measure the energy consumption of ASR 9000 routers and to draw conclusions for the definition of the path.
This thesis is to look for a solution to implement a green routing approach, where in a network the most ecological paths are to be computed. The solution should be able to compute paths efficiently underlying a defined green index based on sensor data from routers. The calculated paths should be meaningful on the basis of power consumptions on a specified time range to prevent possible route flapping.

Result:
Through the thesis a first approach to the definition of the green index could be defined by setting paths with the cumulative least electricity consumption over the whole route from the source to the destination router. The overlying calculation of the best paths based on the green index could be implemented by a Green SR-App software in form of a REST-API. This backend API, which is written in modern GoLang, can synchronize all network data via the Jalapeno API Gateway, process it, store it optimally in the sense of statistical purposes and then calculate the best path over a predefined period of sensor data based on Dijkstra's algorithm. The software is designed to be very performant despite very large networks of up to 1000 routers with many times more links in between. High Quality, mature scalability and a proven architecture through a Domain Driven Design have been deliberately written, because this thesis is only the beginning of larger extensions.