Distributed Load Management for Network Devices
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Solution Overview
Problem
The increasing demand for mobile data is straining network devices, leading to overloading and service disruptions, which existing infrastructure and offloading methods fail to efficiently address, resulting in high costs and customer dissatisfaction.
Innovation Solution
A distributed dynamic load management system that allows network devices to share real-time load information and reconfigure themselves by routing data traffic from overloaded devices to underutilized ones, using inter-device communication channels to prevent overloading and facilitate seamless offloading without service disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing infrastructure and offloading methods are used to handle increasing mobile data demand, then network coverage is maintained, but network devices become overloaded and service disruptions occur
Solution Approach 1:
The patent implements dynamic load management where network devices continuously monitor their own load conditions and autonomously make decisions about offloading mobile stations. This dynamic adaptation allows the network to respond to changing traffic conditions in real-time, preventing overload while maintaining service continuity without requiring centralized control
Solution Approach 2:
Each network device independently monitors its own load status and autonomously determines when and where to offload traffic. This self-service capability eliminates the need for centralized control units, reduces complexity, and enables rapid local responses to overload conditions, thereby maintaining service reliability while handling increased data traffic
2Productivity
If more network devices are deployed to handle increased data traffic, then data delivery capacity improves, but infrastructure costs increase
Solution Approach 1:
The patent merges the capabilities of multiple network devices into a cooperative system where devices share load information and coordinate offloading decisions. This allows existing infrastructure to be utilized more efficiently, achieving increased data delivery capacity without proportional increases in infrastructure investment by combining the resources of existing devices
3Ease of operation
If centralized control units are implemented to manage load distribution, then load balancing improves, but system complexity increases
Solution Approach 1:
The patent eliminates centralized control units by enabling each network device to independently monitor its own load status and autonomously make offloading decisions. This distributed self-service approach simplifies the overall system architecture while maintaining effective load distribution, as each device acts as its own controller based on real-time conditions
4Reliability
If manual interventions are used to address network overload, then service disruptions can be prevented, but operational efficiency decreases
Solution Approach 1:
The patent implements automatic dynamic load management where network devices continuously monitor their load conditions and autonomously execute offloading decisions without manual intervention. This automated dynamic response prevents service disruptions while maintaining high operational efficiency, as the system adapts in real-time without human involvement
Data Source
AI summary
This disclosure relates to a system and method for dynamically managing load on network devices in a distributed manner. As the proliferation of data rich content and increasingly more capable mobile devices has continued, the amount of data communicated over mobile operator's networks has exponentially increased. Upgrading the existing network to accommodate increased data traffic is neither desirable nor practical. One way to accommodate increased data traffic is by utilizing network resources more efficiently. This disclosure provides systems and methods for efficiently utilizing network resources by dynamically configuring the network in a distributed manner based on real-time load information.