Bandwidth Optimization in Connection-Oriented Networks
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Solution Overview
Problem
Existing network systems face inefficiencies in resource utilization due to dynamic and unpredictable connection arrivals and releases, leading to stranded bandwidth and reduced capacity, which increases operational costs and can result in capacity collapse.
Innovation Solution
A bandwidth optimization method that monitors network states, predicts trends, and adjusts policies using analytics to identify inefficient connections and relocate them to more optimal paths, utilizing SDN control to manage Wave Division Multiplexing (WDM), Time Division Multiplexing (TDM), and packet components, and can add temporary resources to accommodate moves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If networks support dynamic connections with varied durations and bandwidth requirements, then service flexibility and adaptability are improved, but network resource utilization deteriorates due to stranded bandwidth from connection arrivals and releases
Solution Approach 1:
The patent implements dynamic connection reconfiguration that continuously monitors network state and automatically relocates connections between different paths, time slots, and wavelengths to optimize resource utilization. This dynamic adjustment allows the network to adapt to changing connection patterns while maintaining high resource efficiency, resolving the contradiction between service flexibility and resource utilization.
2Productivity
If conventional reconfiguration techniques are used, then some bandwidth optimization is achieved, but the network cannot handle rapidly evolving dynamic connections and scheduled connections efficiently
Solution Approach 1:
The patent applies preliminary action by pre-calculating and pre-positioning connections according to predicted future network states and scheduled connection patterns. The system uses historical data and analytics to forecast connection arrivals and proactively reconfigures the network before congestion occurs, enabling efficient handling of dynamic connections while maintaining bandwidth optimization.
Solution Approach 2:
The patent implements continuous feedback mechanisms that monitor network utilization, connection patterns, and resource usage in real-time. This feedback drives adaptive reconfiguration decisions, allowing the system to respond effectively to rapidly evolving dynamic connections while maintaining optimal bandwidth utilization through data-driven adjustments.
3Adaptability or versatility
If network capacity is increased to handle dynamic connection arrivals, then service capability is improved, but operational costs increase
Solution Approach 1:
The patent changes multiple network parameters simultaneously including spatial paths, temporal scheduling, and wavelength assignments to maximize the utilization of existing network capacity. By optimizing the combination of these parameters, the system can handle dynamic connections effectively without requiring proportional increases in physical network capacity, thereby avoiding increased operational costs.
4Productivity
If reconfiguration is performed frequently to optimize bandwidth, then resource utilization is improved, but network complexity and operational overhead increase
Solution Approach 1:
The patent applies partial action by selectively reconfiguring only those connections that will benefit from relocation, rather than performing comprehensive reconfiguration of all connections. The system identifies candidate connections based on current network state and prioritizes reconfiguration of connections that will yield the greatest resource utilization improvement, reducing operational complexity while maintaining high resource efficiency.
Data Source
AI summary
Systems and methods for bandwidth optimization in a network include monitoring a state of the network, wherein the network is a connection-oriented network; utilizing analytics based on the monitoring to predict trends, create triggers, and determine updates to policy associated with the network; and performing bandwidth optimization on one or more connections based on the trends, the triggers, and the policy, wherein each of the one or more connections has one or more of a Wave Division Multiplexing (WDM) component, a Time Division Multiplexing (TDM) component, and a packet component, and wherein the bandwidth optimization finds the one or more connections with inefficient resource usages and moves the one or more connections, in one or more of time and space, to more optimal paths.


