Below are some ideas from me. People are encouraged to better it, provide alternative ways/solutions, and give their inputs based on the material provided below -
We are using a Windows (OS) based laptop having VMware installed on it. We need to develop a Grid, out of lets say, three virtual computers created by VMware (on this laptop). The control of the grid is on one of the virtual system/computer and rest two are accessed by this main system through a GUI, for additional computing needs.
The three virtual systems are networked using IP addresses, all of which are of a different class. E.g., Class A, for the first system, Class B, for the second system and Class C, for the third system.
Additionally, Machine Learning has to be implemented (using - "Artificial Neural Networks, Genetic Algorithms and Fuzzy Logic") on this Grid, to - "Predict the Time and Resources Consumed by Applications running on these three virtual systems."
Modern machine learning techniques able to handle large number of attributes should be used, taking into account application and system specific attributes (e.g., CPU micro architecture, size and speed of memory and storage, input data characteristics and input parameters). Also, state the most suitable machine learning technique(s) for predicting spatio temporal utilization of resources by applications and system.
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