Discrete Event Simulation Data Generation via SQL Fixpoint
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Solution Overview
Problem
Discrete event simulation systems face challenges in handling concurrent operations and processing both past and pending events due to the limitations of SQL queries, which are set-wise and insensitive to history, making it difficult to serialize and process entire chronological sequences of events efficiently.
Innovation Solution
The use of a fixpoint mechanism in a database management system to recursively evaluate SQL queries, combined with pipelined query processing and user-defined functions, allows for the serialization of primary and pending events by processing each event and its preceding events up to the current time, enabling efficient generation of discrete event simulation data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If hand-coded programming languages (e.g., C) are used for discrete event simulation, then the system can handle complex simulation logic, but the computational cost becomes expensive for larger simulations
Solution Approach 1:
The patent replaces traditional hand-coded programming languages (C) with SQL query language to implement discrete event simulation. This substitution leverages the set-wise processing capabilities and optimized query evaluation mechanisms of database systems, achieving both computational efficiency and ease of implementation while maintaining the ability to handle complex simulation logic through SQL's expressive power
2Productivity
If SQL queries are used for discrete event simulation, then the implementation becomes simpler and more efficient, but the system struggles to handle concurrent operations and process chronological sequences of events
Solution Approach 1:
The patent applies preliminary action by pre-ordering events chronologically using SQL's ORDER BY clause before processing. This ensures that when SQL queries evaluate events in set-wise operations, they maintain the correct chronological sequence required for discrete event simulation, resolving the conflict between SQL's set-wise processing and event sequence requirements
Solution Approach 2:
The patent introduces an intermediary mechanism (fixpoint iteration with ordered event processing) that mediates between SQL's set-wise query evaluation and the sequential nature of discrete event simulation. This intermediary layer ensures that pending events are properly serialized and processed in chronological order while leveraging SQL's computational efficiency
3Adaptability or versatility
If set-wise SQL operations are used, then data manipulation becomes more powerful, but it becomes difficult to serialize and process events in chronological order
Solution Approach 1:
The patent applies preliminary action by pre-ordering events chronologically using SQL's ORDER BY clause before processing. This ensures that when SQL queries evaluate events in set-wise operations, they maintain the correct chronological sequence required for discrete event simulation, resolving the conflict between SQL's set-wise processing and event sequence requirements
Data Source
AI summary
A method of generating discrete event simulation data using a query is provided herein. The method includes retrieving a trajectory specifying a service access event for a customer accessing a service in a simulation. The method also includes processing, in a relational database query, one or more pending events corresponding to one or more customers accessing the service before the customer. Additionally, the method includes processing, in the relational database query, the service access event. Processing the service access event occurs after processing the one or more pending events. The method also includes providing a result for the relational database query. The result comprises the trajectory, and the one or more trajectories.