Central Payload Processor for B2B Transaction Ordering
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Solution Overview
Problem
Current solutions for B2B transactions face challenges in processing large business payloads while maintaining order, especially for small and medium enterprises without continuous Internet presence, as they require high processing capabilities and result in high bandwidth usage and potential bottlenecks.
Innovation Solution
A framework utilizing a central payload processor (CPP) that processes payloads en-route, allowing senders and receivers to dynamically or statically provide processing logic, leveraging cloud computing for scalability and geographical distribution of storage, and implementing map-reduce functionality to handle large payloads efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If large business payloads are processed directly between sender and receiver, then processing capability is improved, but bandwidth usage increases and bottlenecks occur
Solution Approach 1:
The patent introduces a Central Payload Processor (CPP) as an intermediary component between senders and receivers. The CPP receives payloads from senders, processes them using available executable logic, and delivers results to receivers. This intermediary architecture enables processing to occur centrally rather than requiring direct sender-receiver processing capabilities, thereby reducing the processing burden on individual endpoints and optimizing bandwidth utilization by avoiding redundant payload transmissions.
2Stability of the object's composition
If sender and receiver both have processing capabilities, then in-order processing is maintained, but device complexity increases
Solution Approach 1:
The CPP acts as a centralized intermediary that assumes the processing responsibility, eliminating the need for both sender and receiver to possess processing capabilities. The CPP maintains ordering by processing payloads sequentially according to their receipt order, using a payload registry to track and manage the sequence. This centralization simplifies the overall system architecture while preserving the in-order processing guarantee.
Solution Approach 2:
The system performs preliminary actions by pre-configuring executable logic bundles at the CPP that correspond to different payload types. When a payload arrives, the CPP checks its registry to determine if appropriate executable logic is already available, allowing immediate processing without requiring the receiver to have processing capabilities. This preliminary preparation of processing logic at the intermediary enables efficient in-order processing.
3Ease of operation
If receiver is offline during payload transmission, then availability is improved, but processing reliability deteriorates
Solution Approach 1:
The CPP performs preliminary processing of payloads before the receiver needs to access them. When a payload is received, the CPP immediately processes it using available executable logic from its registry, stores the results, and makes them available for later retrieval. This allows the receiver to be offline during transmission and processing without affecting reliability, as the results are already prepared and stored when the receiver comes online.
Solution Approach 2:
The CPP autonomously processes payloads and manages result delivery without requiring the receiver to be present or online. The system performs self-service by automatically checking the payload registry, executing appropriate logic, storing results, and making them available for retrieval. This autonomous operation ensures processing reliability even when receivers are offline, as the CPP independently completes all processing steps.
Data Source
AI summary
Certain example embodiments relate to a framework that helps address dynamic scalability and in-order processing of payloads, e.g., pertaining to B2B and/or other transactions. A receiver and/or sender is/are able to dynamically and/or statically provide an executable to an intermediary entity (e.g., a central payload processor or CPP) to process and/or otherwise transform payloads, en-route. This arrangement advantageously provides a very efficient way of delivering ordered content, especially when the content is extremely large. Cloud processing and/or storage facilities may be implemented in certain example instances, parallel sending and/or receiving may be provided, etc., in addressing issues relating to how to send large amounts of data over large distances to possibly multiple recipients.