Online Qualification submission for Google Hash Code 2017.
Team members: Marcel Eschmann, Cedric Seger and Simone Stefani
Hub: Royal Institute of Technology (KTH) - Stockholm
Have you ever wondered what happens behind the scenes when you watch a YouTube video? As more and more people watch online videos (and as the size of these videos increases), it is critical that video-serving infrastructure is optimized to handle requests reliably and quickly. This typically involves putting in place cache servers, which store copies of popular videos. When a user request for a particular video arrives, it can be handled by a cache server close to the user, rather than by a remote data center thousands of kilometers away. But how should you decide which videos to put in which cache servers?
Given a description of cache servers, network endpoints and videos, along with predicted requests for individual videos, decide which videos to put in which cache server in order to minimize the average waiting time for all requests.
Input Data Set: "Me at the zoo"
