Content Asset Task Bidding for Balanced Resource Assignment
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Solution Overview
Problem
Task assignment in managing content asset resources is inefficient due to a lack of knowledge about the current workload of resources, leading to tasks being assigned to overloaded processors or packagers when others are available.
Innovation Solution
A computing device, acting as a task resource manager, requests bids from resources based on their capabilities and availability, selects a resource with the winning bid, and transmits the task for completion, allowing for dynamic resource management and autonomous network balancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a tasker assigns tasks to resources without knowing their current workload, then task assignment is simple and fast, but resource utilization becomes inefficient and tasks may be assigned to overloaded processors
Solution Approach 1:
The patent implements a feedback mechanism where resources broadcast their current workload status and capabilities to the network. The tasker receives this feedback information and uses it to make informed task assignment decisions, thereby improving resource utilization efficiency without requiring complex centralized tracking of each resource's state.
Solution Approach 2:
Resources autonomously broadcast their own workload status and capabilities without requiring the tasker to actively query or track them. This self-service approach allows the tasker to receive up-to-date information passively, simplifying the task assignment system while improving resource utilization efficiency.
2Productivity
If a centralized system tracks all resource workloads to optimize task assignment, then resource utilization improves, but system complexity and overhead increase
Solution Approach 1:
Instead of the tasker actively tracking and querying resource workloads (centralized monitoring approach), the patent inverts the approach by having resources autonomously broadcast their status to the network. The tasker passively receives this information, thereby achieving efficient task assignment without the complexity of a centralized tracking system.
Solution Approach 2:
Resources perform self-service by autonomously broadcasting their workload status and capabilities. This eliminates the need for the tasker to implement complex tracking mechanisms, reducing system overhead while maintaining efficient task assignment through available information.
3Reliability
If tasks are assigned without considering resource capabilities and availability, then assignment speed is high, but task completion reliability decreases
Solution Approach 1:
Resources preemptively broadcast their capabilities and availability status before tasks are assigned. This preliminary action ensures that the tasker has all necessary information about resource suitability already available in the network, enabling fast and reliable task assignment decisions without requiring additional verification steps.
Solution Approach 2:
The system uses feedback from resource broadcasts about their capabilities and availability to make informed task assignment decisions. This feedback mechanism ensures tasks are assigned to suitable resources, improving completion reliability while maintaining assignment speed through passive information reception.
Data Source
AI summary
Provided are methods and systems whereby a request for a task relating to a content asset can be received. Information related to the task can be transmitted. A plurality of bids can be received in response to the transmitted information. Each bid can originate from a corresponding device such as a video packager. Each bid can represent a network related cost associated with the corresponding video packager accepting the task. A winning bid can be determined from the plurality of bids.