Dynamic Event-Driven Simulation for Mobile Network Resource Control
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Solution Overview
Problem
Current mobile telephony systems, particularly third-generation networks like UMTS, face challenges in dynamic radio resource management and quality control due to varying data throughput and service types, with existing solutions being either inefficient or too resource-intensive for operational use.
Innovation Solution
A method and system for simulating and optimizing resource usage in mobile networks, utilizing statistical distribution maps and routing algorithms to dynamically manage resources and ensure quality of service across cells, allowing for efficient traffic control and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If statistical simulation methods (Monte Carlo) are used to predict network traffic, then resource management capability is provided, but temporal dynamics of communications are not captured and call admission control is not enabled
Solution Approach 1:
The patent transitions from static statistical simulation to dynamic event-driven simulation. The system models temporal dynamics by processing events in chronological order, updating network state after each event, and enabling call admission control decisions based on real-time resource availability. This dynamic approach captures the temporal evolution of communications while maintaining resource management capabilities.
2Reliability
If dynamic simulation of communications is implemented to capture temporal dynamics, then call admission control becomes possible, but computational resources required become enormous and the system becomes too complex for operational use
Solution Approach 1:
The patent segments the network simulation into discrete event types (call arrivals, call departures, handovers, etc.) that can be processed independently in chronological order. Each event triggers localized updates to network state and resource allocation, avoiding the need to simulate all communications simultaneously. This segmentation reduces computational complexity while preserving temporal dynamics.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing network topology, resource configurations, and service parameters before simulation begins. Event handlers are pre-programmed with specific actions to take when certain events occur, enabling efficient real-time processing without complex runtime calculations. This preliminary preparation significantly reduces computational resources required during operational simulation.
3Productivity
If existing simulation solutions are used, then some resource management functions are provided, but load control and data throughput control for individual users are not enabled
Solution Approach 1:
The patent implements a universal event-driven simulation framework that can handle multiple resource management functions simultaneously. The same simulation engine processes call admission control, load control, and data throughput control by responding to different event types and updating appropriate network parameters. This multi-functional approach enables comprehensive resource management including previously unavailable load control and per-user throughput control capabilities.
Data Source
AI summary
This present invention concerns a method and a system for simulating and optimising the use of resources available in a zone of coverage of a mobile telephone network (RT), characterized, firstly, in that it is implemented by processing resources (10) of at least one resource optimization system (1) and, secondly, in that it includes the following stages determination (50), by an event management module (EM) of the optimization system (1), of a variation, called a disruption, of at least one packet (P) transmission (T) required within the network (RT), from at least one statistical distribution map (CR) held in storage resources (11) of the optimization system (1), and that consists of data representing data packet (P) transmissions (T), selection (52) of a set of cells determining a simulated zone (ZS), by a resource operating-resources control module (CL), and then use of a routing algorithm in order to determine a routing path (CP) in the simulated zone (ZS) and to successively optimize the resources of the servers (ER) covering the successive cells of the routing path (CP)