Distributed State Machine Services for Dynamic Shipment Rule Processing
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Solution Overview
Problem
Conventional state machines lack efficiency in handling complex processes like shipment customs processing and finance in distributed computing environments, requiring improved systems for automated deployment and processing of cargo data.
Innovation Solution
A system and method for programming a finite state machine (FSM) that includes rule-based and state-based application programs for automatic deployment in a distributed computing environment, utilizing electronic computer processors to collect, aggregate, and dynamically assign programmable rules for cargo shipment data from various sources, deploying FSMs with dynamically loadable rules, and integrating with container orchestration platforms for seamless operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional state machines are used for processing cargo shipment data, then the system structure is simple, but the processing efficiency and computational power are insufficient for complex distributed computing environments
Solution Approach 1:
The patent segments the state machine into multiple distributed app node services, where each node handles specific states or rules. This allows parallel processing of cargo shipment data across multiple nodes, significantly improving processing efficiency while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The patent transitions from a single-state machine architecture to a multi-dimensional distributed system architecture. By adding the dimension of spatial distribution across multiple nodes and introducing dynamic rule loading capabilities, the system achieves higher computational power and processing efficiency for complex customs and finance processes.
2Adaptability or versatility
If dynamically loadable programmable rules are integrated into distributed app node services, then the system adaptability and computational power are enhanced, but the device complexity increases
Solution Approach 1:
The patent implements dynamic rule loading mechanisms in distributed app node services, allowing rules to be loaded, unloaded, and modified at runtime without restarting services. This enhances system adaptability for handling varying customs and finance requirements while managing complexity through on-demand loading strategies.
Solution Approach 2:
The distributed app node services are designed with universal architectures that can handle multiple states and rules through a common framework. Each node service can dynamically load different rule sets to handle various cargo types, customs procedures, and finance processes, achieving multi-functionality without proportionally increasing complexity.
3Extent of automation
If FSM is deployed in distributed computing environment with container orchestration, then automated deployment and management are achieved, but the implementation complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where distributed app node services automatically register themselves with the container orchestration system, report their status, and manage their own rule sets. This automation reduces manual intervention requirements while the standardized interfaces keep implementation complexity manageable.
Solution Approach 2:
The system incorporates feedback mechanisms where app node services continuously report their operational status, rule loading states, and performance metrics to the orchestration system. This enables automated monitoring, health checks, and dynamic resource allocation, achieving high automation levels with manageable complexity through information feedback loops.
Data Source
AI summary
A method codifies data, programs, rule-based, state-based application software for automatic deployment, in distributed computing environment, including programming/assignment Production Rules as code for processing data/events for cargo port shipments, through Customs and Finance Processing referred to as supply chain financing; programming and deploying FiniteStateMachine (FSM) implementing state-based application components; deployment is collection of distributed software AppNodeServices (ANS) that collectively comprise an FSM. Each AppNode is at least a single state of FSM. AppNode contains programmable Rules loadable dynamically through the processes. Shipment data is received and collected from one or more data sources including Electronic Data Interchange (EDI), other Enterprise Resource Planning (ERP) messaging, web service Application Programming Interface (API) calls, Internet Of Things (IoT) messaging, remote file copies, and tracking sensors. SmartPass is aggregation of shipment data combined with rule processing, FSM, and associated processing actions, and is used to dynamically assign rules on individual shipment and pre-determined needs basis.