Execution Space Resource Allocation Overhead Reduction
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Solution Overview
Problem
In multi-task information processing systems, the overhead associated with additional resource allocation to processes increases significantly as the number of processes executed in the system grows, due to communication overhead and processing queue delays.
Innovation Solution
The method involves requesting additional resource allocation within an execution space, determining approval based on defined resource allocation limitations, and allocating resources efficiently by retaining surplus resources within the execution space to minimize external communication and queue delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the OS coordinates and re-allocates CPU time for each process requesting additional resources, then resource allocation flexibility is improved, but communication overhead and processing queue delays increase significantly
Solution Approach 1:
The patent segments the information processing system into multiple execution spaces, each independently managing its own processes and resources. This segmentation allows resource allocation decisions to be made locally within each execution space rather than requiring centralized OS coordination, thereby reducing communication overhead and processing queue delays while maintaining resource allocation flexibility.
Solution Approach 2:
The execution space acts as an intermediary layer between processes and the OS. Each execution space independently manages resource allocation for its contained processes, serving as a mediator that eliminates the need for direct communication between processes and the OS for resource requests, thus reducing overhead.
2Productivity
If the OS manages resource allocation for all processes, then system-wide resource distribution is improved, but device complexity and management overhead increase
Solution Approach 1:
The system is divided into multiple execution spaces that independently manage their own processes and resources. This segmentation distributes the management complexity across multiple independent units rather than concentrating it all in the OS, reducing overall system complexity while maintaining efficient resource distribution.
Solution Approach 2:
Each execution space autonomously manages its own resource allocation without requiring OS intervention. This self-service approach allows execution spaces to efficiently distribute resources among their processes while reducing the management burden on the OS.
3Adaptability or versatility
If more processes are executed in parallel, then system functionality is improved, but communication overhead and processing queue delays increase
Solution Approach 1:
Processes are grouped into execution spaces that independently manage their own resource allocation. This segmentation reduces the need for cross-process communication with the OS, thereby reducing communication overhead and processing queue delays even as the total number of processes increases.
Data Source
AI summary
A certain process included in a first execution space requests a local resource manager to allocate a resource. The local resource manager obtains the authentication ID of the process issuing the request and determines whether or not the resource can be allocated. If the resource can be allocated and the resource previously secured in the execution space can suffice the request, the local resource manager allocates the resource to the process. If the resource is insufficient, the local resource manager requests a global resource manager to allocate the resource. The global resource manager obtains the authentication ID of the first execution space issuing the request and determines whether or not the resource can be allocated. If it is determined that the resource can be allocated, the resource is allocated to the first execution space.