Optimizing Data Center Traffic Management with Proactive Planning

In this article, we’ll dive into the world of data center interconnects and explore how to optimally place Laser Power Systems (LPS) to meet demand. Think of a data center like a big city with lots of buildings (nodes) connected by roads (optical fibers). Each building has its own unique set of traffic demands, which is like the number of people living in each building and their daily commute patterns.
To start, we need to sort the traffic demands in order of shortest distance between nodes. This is like organizing a busy airport by the shortest flight paths. Once we have the sorted list, we consider each demand’s required data rate, which is like the number of passengers on each flight.
For each demand, we examine the shortest paths and place an LPS on each path that meets the data rate requirement. This is like building a network of roads connecting the buildings in the city. We repeat this process until all demands are met or there are no more available paths to add an LPS.
There are two main placement strategies: Just Enough and Highest. With Just Enough, we choose the configuration that provides the highest data rate while meeting the demand. This is like prioritizing the most important flights during peak travel times. Highest selects the highest data rate configuration possible, even if it doesn’t meet the demand exactly. It’s like booking a flight with extra legroom, even if it means paying a bit more.
If multiple LPS are required to fulfill a demand, we assign them to different paths in a first-fit manner, like boarding passengers on a plane based on their seat preference. If no free slots are found, the placement process continues on the next shortest path. It’s like trying to book a flight with available seats during a busy travel period.
Finally, if at least three LPS are needed for a demand, we consider using a 4-line fixed free spectral range (FSR) technology, which is like having four planes fly in formation to reduce fuel consumption. This comes at the expense of a slight decrease in data rate performance compared to single-wavelength transponders.
In summary, optimally placing LPS for data center interconnects involves sorting traffic demands by shortest distance, examining each demand’s required data rate, and assigning LPS to paths based on first-fit assignment or fixed spectral range technology. By following these steps, we can ensure that data centers have enough bandwidth to meet their traffic demands while minimizing the number of LPS needed, resulting in cost savings and improved performance.