Server Load Balancing by Service Probability
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Solution Overview
Problem
Current load balancing methods in call centers, which route calls based on estimated waiting time, do not necessarily maximize the number of customers served within a contracted time period, as they focus on reducing average waiting time rather than optimizing call servicing within the contracted timeframe.
Innovation Solution
The method routes work (calls) to servers based on the relative probability of servicing the work within a target service time interval, selecting the server with the highest probability or sufficient opportunities to complete the task on time, thereby efficiently allocating workload without complex absolute probability calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If calls are routed based on estimated waiting time to reduce average waiting time, then the average waiting time is reduced, but the number of customers serviced within the contracted time period is not maximized
Solution Approach 1:
The patent changes the routing parameter from estimated waiting time to probability of servicing within target time. By calculating and using the probability parameter instead of the waiting time parameter, the system optimizes for the number of customers serviced within contracted time while maintaining computational efficiency through relative probability comparisons rather than absolute probability calculations.
2Measurement precision
If absolute probability calculations are performed to determine server selection, then the accuracy of probability-based routing is improved, but the computational overhead increases
Solution Approach 1:
The patent applies partial action by using relative probability comparisons instead of complete absolute probability calculations. The system only needs to determine which server has the highest relative probability, not compute the actual absolute probability values, thereby reducing computational overhead while maintaining sufficient accuracy for effective server selection.
Data Source
AI summary
The present invention is directed to balancing resource loads. In particular, the present invention is directed to assigning work to service locations having the greatest probability of servicing the work within a target time. Because an average wait time is not necessarily equal to a probability of servicing work within a target time, the present invention is useful in meeting service target goals. Because the present invention operates by comparing the probability of a defined set of service locations to one another, absolute probabilities need not be calculated. Instead, relative probabilities may be used in assigning work.