5G Load Balancer Orchestration for Multi-Protocol Traffic
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Solution Overview
Problem
Conventional load balancing methods in mobile communication networks, particularly in telco cloud networks, fail to efficiently manage network resources due to insufficient support for multiple protocols, dynamic topology adjustments, and protocol-specific load balancing, leading to suboptimal performance and resource inefficiencies.
Innovation Solution
A load balancing method and apparatus that includes a load balancer with a controller, orchestrator, and engine group, capable of dynamically selecting and configuring load balancing instances based on service requests, supporting various protocols, and optimizing resource allocation through intelligent packet classification and hardware offloading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional load balancing methods are used in mobile communication networks, then basic load distribution is achieved, but resource efficiency deteriorates due to insufficient support for multiple protocols and dynamic topology adjustments
Solution Approach 1:
The patent implements a universal load balancer architecture that supports multiple protocols (HTTP, HTTPS, TCP, UDP, SCTP) through a unified control plane and multiple protocol-specific engines. The orchestrator dynamically selects and configures appropriate engines based on service request requirements, enabling a single load balancer to perform multiple protocol-specific load balancing functions simultaneously, thereby improving resource efficiency while maintaining high adaptability.
Solution Approach 2:
The patent introduces dynamic topology adjustment capabilities where the load balancer can automatically adapt to changing network conditions, service requirements, and traffic patterns. The orchestrator dynamically creates, modifies, or removes load balancing instances based on real-time network state, enabling the system to optimize resource allocation continuously and respond to dynamic topology changes without manual intervention.
2Productivity
If static load balancing configuration is used, then system complexity is reduced, but performance deteriorates due to inability to adapt to changing network conditions and request types
Solution Approach 1:
The patent implements self-service automation through the orchestrator that automatically monitors network conditions, analyzes service requests, and dynamically configures load balancing parameters without manual intervention. The system autonomously adjusts load balancing algorithms, selects appropriate engines, and optimizes resource allocation based on real-time metrics, thereby achieving high performance while keeping operational complexity low through automation.
Solution Approach 2:
The patent incorporates feedback mechanisms where the load balancer continuously monitors network performance metrics, traffic patterns, and service quality indicators. This feedback information is fed back to the orchestrator, which dynamically adjusts load balancing configurations and parameters to optimize performance, creating a closed-loop control system that adapts to changing conditions automatically.
3Productivity
If protocol-specific load balancing is implemented for each service, then service optimization is improved, but device complexity increases due to multiple separate load balancers
Solution Approach 1:
The patent merges multiple protocol-specific load balancing engines into a single unified load balancer architecture. The orchestrator intelligently selects and activates only the required protocol engines based on incoming service requests, combining the advantages of protocol-specific optimization with the resource efficiency of a consolidated system. This reduces the total number of load balancers needed while maintaining service-specific performance optimization.
Solution Approach 2:
The patent segments the load balancing functionality into independent, modular protocol engines (HTTP engine, HTTPS engine, TCP engine, UDP engine, SCTP engine) that can be selectively activated. Each engine is optimized for its specific protocol while being managed by a common orchestrator, allowing fine-grained control over resource allocation and enabling service optimization without requiring separate physical load balancers for each protocol.
Data Source
AI summary
A communication technique that integrates a 5th generation (5G) communication system for supporting a higher data rate after a 4th generation (4G) system with Internet of Things (IoT) technology, and a system thereof is provided. The disclosure can be applied to intelligent services (e.g., smart home, smart building, smart city, smart car or connected car, healthcare, digital education, retail business, security and safety related services, or the like) based on 5G communication technology and IoT-related technology. The disclosure discloses a dynamic and efficient load balancing method and apparatus.


