I have a problem that I'm sure that one of the classic algorithms can be solved but I can not understand it I am back and map it back. It may be a little late to explain the problem.
So I have some work machines that have certain procedures going on. Each process has some weight. It may be that a worker has to make offline referrals only for some time of the day to indicate this point and to deliver optimum distribution.
I will explain it clearly with the following example:
There are two workers: w1 and w2
worker w1 Load data every month, it is collected every 20 minutes. Now since I have to analyze the data over time, I have four large data I break into the dark window - morning, day, eve, night Now every worker loads the mile of each process in the window every time. Total resources of I W1 are 10 units and w2 has 15 .
Now with this data, I can say That some DB process takes you to W1 at night because we feel free at night at the Y1. Similarly other recommendations.
If I can deliver an optimal distribution, I can always compare and generate recommendations. How do I move forward? I saw many load balancing problems but they are real-time server request handling problems and job shop problems as a parameter during job completion.
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