Balanced Pair Resource Consumption Tracking
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Solution Overview
Problem
Resource management systems face inefficiencies in tracking and analyzing time-bounded resource consumption, particularly in scenarios like Software Defined Networking, where the addition of time dimension makes it computationally expensive and unscaleable to determine booked consumption, impacting performance and scalability.
Innovation Solution
A method is implemented in a time-bounded resource management system where each resource consumption event is stored as a balanced pair of entries in a database, with a start time and positive consumption amount, and an end time with a negative consumption amount of the same magnitude, allowing for efficient querying and computation of instantaneous or peak resource utilization using Structured Query Language (SQL) functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional resource tracking methods are used to analyze every booking to determine consumption at any given time, then measurement precision is maintained, but computational complexity and processing time increase linearly with the number of bookings
Solution Approach 1:
The patent applies preliminary action by pre-processing resource consumption events into a balanced pair format (positive entry at start time, negative entry at end time) and storing them in chronological order. This preprocessing enables instantaneous query resolution through simple summation of events up to the query time, eliminating the need for complex analysis of every booking during query execution.
Solution Approach 2:
The patent transforms the representation of resource consumption by changing the parameter structure from traditional booking records to balanced pairs with explicit start/end times and signed consumption amounts. This parameter transformation allows the system to compute consumption at any time point through a simple cumulative sum operation, reducing computational complexity from linear analysis to constant-time aggregation.
2Measurement precision
If all bookings in the system are analyzed to determine resource consumption, then complete accuracy is achieved, but system scalability is compromised due to the large order book size
Solution Approach 1:
The patent extracts only the necessary information for consumption calculation by representing each resource consumption event as a balanced pair of entries (start event with positive consumption, end event with negative consumption). This extraction reduces the data structure to essential elements, enabling efficient querying without analyzing the complete booking history, thus improving scalability while maintaining accuracy.
Solution Approach 2:
By pre-structuring all resource events in a balanced pair format with chronological ordering before queries are executed, the system enables scalable operation. The preliminary organization allows any consumption query to be resolved by summing events up to the query time point, independent of the total number of bookings in the system, thereby achieving both accuracy and scalability.
3Measurement precision
If complex analysis of every booking is performed to determine resource consumption, then measurement accuracy is maintained, but device complexity increases
Solution Approach 1:
The patent changes the parameter representation of resource events to a balanced pair structure with signed consumption amounts and explicit time boundaries. This parameter transformation simplifies the measurement process from complex booking analysis to a straightforward cumulative sum operation, maintaining measurement accuracy while dramatically reducing processing complexity.
Solution Approach 2:
The system performs preliminary organization of all resource events into balanced pairs with chronological ordering. This upfront preparation enables subsequent consumption queries to be executed with minimal complexity through simple aggregation, eliminating the need for complex analysis logic during query processing while preserving measurement accuracy.
Data Source
AI summary
A method implemented in a time-bounded resource management system for managing a resource is described. The time-bounded resource management system includes a processor communicatively coupled to a database. The method includes storing each resource consumption event of the resource as a balanced pair of entries in the database, wherein the balanced pair of entries comprise 1) a first entry comprising a start time for the resource consumption event and a positive resource consumption amount and 2) a second entry comprising an end time for the resource consumption event and a negative resource consumption amount with the same magnitude as the positive resource consumption amount; receiving a query related to the resource; performing computations on entries in the database related to the query; and providing a result based on the computations as a response to the query.