Dynamic Load Balancing in Communication Networks
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Solution Overview
Problem
Current wireless communication networks face challenges in dynamically balancing load across network elements, particularly in mobility management entities (MMEs), leading to potential overload and service disruptions.
Innovation Solution
Implementing a gateway that monitors real-time load conditions on MMEs, determines a load capacity value based on processing unit usage, memory usage, and active sessions, and communicates this value to eNodeBs and other network elements to dynamically adjust and distribute load across the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static load balancing methods are used in MMEs, then network configuration is simple, but network elements cannot adapt to dynamic load conditions leading to overload and service disruptions
Solution Approach 1:
The patent implements dynamic load balancing by continuously monitoring load conditions on MMEs and adjusting the selection of target MMEs based on real-time capacity values. The system transitions from static configuration to dynamic adaptation where the load capacity values are updated periodically based on actual load measurements, allowing the network to respond to changing conditions without manual reconfiguration.
Solution Approach 2:
The system employs feedback mechanisms where load capacity values are monitored, measured, and used to influence subsequent routing decisions. The MME capacity information is fed back to source MMEs and eNodeBs, enabling them to make informed decisions about session establishment and handover based on current network conditions, creating a closed-loop control system.
2Productivity
If real-time load monitoring is implemented across all network elements, then load distribution is optimized, but information exchange overhead and processing requirements increase
Solution Approach 1:
The patent utilizes existing universal messaging interfaces and protocols (such as S10 interface and S1 interface) to carry load capacity information. The same message structures used for standard MME communication are leveraged to transport capacity data, avoiding the need for dedicated communication channels or specialized message formats, thus minimizing additional information overhead.
Solution Approach 2:
The system changes the parameter being monitored from detailed individual session information to aggregated load capacity values. By summarizing load conditions into capacity metrics (such as number of active sessions, processing capacity), the system reduces the volume of information that needs to be exchanged while still enabling effective load balancing decisions.
3Speed
If load capacity values are updated frequently, then network elements can respond to load changes quickly, but processing overhead and energy consumption increase
Solution Approach 1:
The system implements periodic updates of load capacity values at predetermined intervals rather than continuous real-time updates. This periodic action allows the network to respond to load changes at regular intervals, balancing the need for timely information with the cost of frequent processing and communication.
Solution Approach 2:
The system updates load capacity information selectively rather than continuously for all network elements. Updates are performed based on predetermined criteria such as threshold crossings or specific triggering events, performing partial updates only when necessary rather than exhaustive continuous updates, thereby reducing processing energy consumption.
Data Source
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AI summary
Methods and systems for providing a dynamic and real time load factor that can be shared with other network elements is disclosed. The load factor can be used in determining the relative load among a set of network elements and in distributing new sessions requests as well as existing session on the set of network elements. The load factor can also be used for determining to which network element a user equipment is handed off. The dynamic load factor can also be shared amongst network elements to determine how the load is balanced among the network elements, such as a mobility management entity (MME).