Resource Allocation TRIZ Cases

A virtual computing environment management system analyzes current workload to forecast future demands and recommends architectural changes.

A data center administration server moves virtual machines to separate physical hosts using unique identifiers.

A programming interface abstracts memory with datablocks to schedule accelerator tasks via data flow graphs, reducing manual data movement complexity.

Extended IOMMU hardware merges address translation to reduce system memory consumption while maintaining secure VM isolation.

Management server calculates weighted resource utilization values via interference scores to resolve conflicting service level and performance goals.

A memory allocation method maps tasks to cores and calculates variable access counts to select optimal placement locations.

Execution orders allow data to be shared across kernels, reducing memory bandwidth consumption and computational overhead.

Automated resource selection and configuration reduce manual intervention while maintaining service levels through dynamic intent assurance.

Segmenting a directed graph into time-point snapshots reduces search time for cloud infrastructure configuration data.

Virtual server segmentation groups high-efficiency physical nodes to prioritize task assignment and reduce power consumption.

A computer system integrates parallel computing devices into a network topology using autonomous domain building modules for efficient resource management.

A batch scheduler generates and deploys virtual machines to compute nodes for task execution.

Least-recently-deallocated allocation schemes delay reuse to detect improper usage and enhance resource isolation.

A composite service device determines suitable further devices by evaluating their transactional properties to enable consistent task execution.

A component life cycle management system generates logical design elements to abstract physical components.

A proxy component forwards commands between drivers and executors to enable dynamic memory allocation.

A co-allocation mechanism reserves compute storage and network resources simultaneously using calculated parameters.

A spanning tree collective state machine coordinates message routing across compute nodes in high performance computing clusters.

A distributed resource model manages traits of resources in a computing system using a publish-subscribe mechanism.

Differential equation accelerators partition computational domains across systolic arrays to enable concurrent time-stepping, reducing simulation latency.

Measuring dynamic wave footprints enables real-time spawning adjustments that prevent serialization and improve resource utilization efficiency.

Application tenants allow users to self-register for services, reducing administrative overhead and unnecessary application exposure.

A dynamic allocation scheme adjusts queue counts per virtual function to match real-time demand.

A resource management platform tracks telemetry data to predict container usage patterns for efficient load balancing.

Monte Carlo simulation optimizes resource allocation across automation computing nodes, reducing timing analysis errors and scheduling defects.

A distributed computing system processes video advertisement data using cloud resources to analyze operational parameters and consumer segments.

Iterative binding of abstract patterns to target infrastructure catalogs automates deployment and reduces manual adaptation complexity.

A content abstraction layer enables remote data access from virtual machines without requiring a running desktop environment.

An adaptive throttling service manages concurrent rate limits using token buckets to control tenant access.

Homogeneous processing units rotate between master and slave roles to resolve contradictions between versatility and task execution efficiency.

Configures operational modes to activate or deactivate virtual machines within a single appliance template.

A parallel-processing computer system segments data packets into sub-pipelines executed by multiple processing elements to enhance throughput.

An online learning algorithm recommends tailored computing resource quotas for each service type on a platform.

Server detects geometric shapes in image units to generate indication information, reducing encoding complexity while maintaining transmission efficiency.

Zone controller allocates resources based on health data, avoiding centralized bottlenecks.

A discovery application parses unique resource identifiers to map computing resources to authentication systems.

A control node records device characteristics and usage patterns to determine service deployment configurations.

Dynamic threshold adjustment handles workload variations by preventing overload scenarios in multi-tier e-commerce systems.

A publish subscribe architecture manages computing resources through producer and consumer templates.

A de-duplication task tool consolidates duplicate configuration item representations into a single master representation.

A dynamic evaluation engine manages runtime functions and parameters to decouple application logic from evaluation logic.

A NUMA-aware packet handling system steers ingress traffic to local receive queues for direct memory access on the host node.

A resource policy mechanism monitors external user-defined function processes to manage system consumption dynamically.

A computer system determines parallel execution scenarios based on identified hardware exception sources and associated parallelization factors.

A priority-based scheduler adjusts bandwidth using throttle values to prevent high-priority traffic blocking.

A workload optimizer detects task attributes to configure hardware resources for execution.

A hybrid application design uses a local Device Feature Application Program Interface to enable external websites to access native device hardware features.

A seismic modeling system divides discretized models into subsets to optimize GPU memory usage.