Workload Allocation Planning Tool for Service Classes

The patent segments consumer demands into different classes of service (COS) based on priority levels. High-priority demands are allocated guaranteed capacity while low-priority demands share remaining capacity probabilistically. This segmentation allows the system to satisfy critical QoS requirements for essential services while efficiently utilizing resources for less critical services, resolving the contradiction between QoS satisfaction and resource utilization efficiency.

The patent changes the allocation parameter from binary (all or nothing) to probabilistic based on consumer priority levels. By introducing probability parameters that vary with service class, the system can optimize the balance between guaranteeing QoS for high-priority services and maximizing overall resource utilization efficiency through statistical multiplexing of lower-priority services.

The patent simplifies the allocation system by segmenting consumers into discrete priority classes rather than handling continuous priority levels. This segmentation reduces the complexity of managing individual consumer requirements while still providing guaranteed access where needed, as the system only needs to track aggregate statistics for each class rather than individual consumer states.

The patent implements self-service through statistical multiplexing where lower-priority consumers automatically share remaining capacity based on historical demand patterns and probability parameters. This eliminates the need for complex centralized scheduling algorithms to manage every possible allocation scenario, as the system uses pre-computed statistical models to handle capacity sharing automatically.

The patent segments the resource allocation problem into two independent parts: guaranteed capacity allocation for high-priority services and probabilistic capacity allocation for low-priority services. This segmentation allows the system to optimize cost-effectiveness by fully utilizing statistical multiplexing for low-priority services while maintaining QoS for high-priority services, as the two segments can be optimized independently without compromising either objective.

The patent introduces probability parameters that change with service class to model the trade-off between cost-effectiveness and QoS. By using these parameters to calculate optimal allocation breakpoints, the system can determine the precise threshold where guaranteed access transitions to probabilistic access, maximizing cost-effectiveness while ensuring QoS for critical services remain satisfied.