Abstract: A method can include training a machine learning algorithm to determine a duration of a new work order, based on (a) historical input data for the machine learning algorithm and (b) historical output data for the machine learning algorithm. The method can also include determining one or more work orders for a service provider comprising: determining, by the machine learning algorithm, as trained, one or more durations of the one or more work orders; and determining an optimized service route for the one or more work orders. The method can further include updating a work schedule for the service provider based on the optimized service route. Other embodiments are also provided.

Abstract: A method of balancing computer resources on a network of computers is provided employing a two-tier network architecture of at least one High Level Collector as a scheduler/load balancing server, and a plurality Low level Collectors which gather task data and execute instructions. Tasks are assigned priority and weight scores and sorted prior to assignment to Low Level Collectors. Also provided is a computer readable medium including instructions, wherein execution of the instructions by at least one computing device balances computer resources on a network of computers.

Abstract: A method of balancing computer resources on a network of computers is provided employing a two-tier network architecture of at least one High Level Collector as a scheduler/load balancing server, and a plurality Low level Collectors which gather task data and execute instructions. Tasks are assigned priority and weight scores and sorted prior to assignment to Low Level Collectors. Also provided is a computer readable medium including instructions, wherein execution of the instructions by at least one computing device balances computer resources on a network of computers.