ADNA Workflow Repair for Scalable Decentralized 5G Execution
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Solution Overview
Problem
Existing 5G networks face challenges in managing decentralized workflows with unknown numbers of sub-processes and tasks, leading to inefficiencies and increased power consumption due to request-response transactions.
Innovation Solution
Implementing a dynamically scalable ADNA Manager with decentralized atomic decision making, using ADNA task blocks that execute workflow rules without a fixed orchestration, and incorporating exception handling to remediate unsatisfied input parameters, thereby reducing transactions and enhancing system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If decentralized atomic decision making with ADNA task blocks is implemented, then system scalability is improved, but system complexity increases
Solution Approach 1:
The system segments workflow management into atomic deterministic next action (ADNA) task blocks, where each block represents an independent, self-contained unit of work with a single entry point and a single exit point. This segmentation allows the system to scale by adding individual task blocks without increasing overall system complexity, as each block operates autonomously according to predefined rules.
Solution Approach 2:
The ADNA Manager dynamically scales the system by adding or removing task blocks based on runtime requirements. The pool of ADNA task blocks can be dynamically adjusted without requiring fixed orchestration, allowing the system to adapt its complexity level to match actual operational needs while maintaining scalability.
2Reliability
If exception handling is implemented to remediate unsatisfied input parameters, then reliability is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary validation of input parameters against qualification rules before executing task blocks. Exception ADNA task blocks are pre-configured to handle specific failure modes, remediating unsatisfied input parameters before they can cause system failures. This preliminary action improves reliability by preventing errors rather than reacting to them.
Solution Approach 2:
Exception handling is implemented as a self-service mechanism where the ADNA Manager automatically detects qualification rule violations and invokes appropriate exception task blocks without external intervention. The system self-corrects by remediating unsatisfied input parameters through predefined exception handling logic, improving reliability without requiring complex external error management systems.
3Loss of energy
If request-response transactions are eliminated, then power consumption is reduced, but loss of information may increase
Solution Approach 1:
The system replaces the mechanical request-response transaction model with a rule-based execution model. ADNA task blocks execute based on predefined workflow rules and qualification rules rather than through iterative request-response cycles. This substitution eliminates the need for continuous communication transactions, significantly reducing power consumption while maintaining complete workflow state information through deterministic rule execution.
Solution Approach 2:
The system uses breadcrumb information as a copy of workflow state that is stored and retrieved as needed. Instead of maintaining continuous request-response transactions to track state, the system creates copies of relevant state information (breadcrumbs) that can be independently accessed and verified, preventing information loss while eliminating the need for ongoing transactional communication.
Data Source
AI summary
Systems and methods for providing a dynamically scalable ADNA Manager with decentralized atomic decision making are described. The decentralized atomic decision making may be performed using atomic deterministic next action (ADNA) task blocks that execute one or more workflow rules and then invoke one or more ADNAs within a pool of ADNAs. The system includes a processor that is configured to detect that an exception ADNA has been invoked more than a threshold number of times, repair a first ADNA, add a new ADNA to the pool of ADNAs, add a new workflow rule that acquires an updated input parameter to the one or more workflow rules for the repaired first ADNA based on a number of exception ADNAs invoked by the repaired first ADNA, and invoke the new ADNA using the repaired first ADNA.