Dynamic Client Rejection for Multi-Server Load Balancing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Multi-client/multi-server systems face challenges in balancing communication load and maintaining efficient client-server connections, particularly in renewable energy installations where environmental factors and unpredictable device positioning can lead to communication overload and disconnections.
Innovation Solution
A method is introduced that calculates a figure of merit for rejection to dynamically manage client-server connections by identifying clients with lower connection quality and probabilistically rejecting them to rebalance the network, using factors such as server load, signal strength, and buffer memory, allowing clients to reconnect to more suitable servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If clients are connected to servers in a multi-client/multi-server system, then the system can handle more data traffic and provide better service coverage, but the communication load on servers increases and may lead to overload
Solution Approach 1:
The patent implements dynamic client rejection mechanisms where servers can probabilistically reject clients based on current load conditions. The rejection probability is adjusted dynamically according to server utilization, allowing the system to adapt to changing traffic patterns and prevent overload while maintaining high client acceptance under normal conditions
Solution Approach 2:
The system changes the parameter of connection acceptance by introducing a rejection probability parameter that varies with server load. This allows the server to transition between accepting all clients, rejecting some clients probabilistically, or rejecting specific clients based on multiple factors including load, signal quality, and connection history
2Productivity
If the system accepts all client connection requests, then client service coverage is maximized, but communication bandwidth is consumed and load balancing deteriorates
Solution Approach 1:
The patent applies partial action by rejecting only a portion of client connection requests based on calculated rejection probabilities. Instead of accepting or rejecting all clients uniformly, the system selectively applies rejection to those with lower priority or poorer connection quality, maintaining overall service coverage while reducing unnecessary bandwidth consumption
Solution Approach 2:
The system uses feedback from server load monitoring and connection quality measurements to adjust rejection decisions. Servers continuously monitor their own utilization and the quality of incoming connections, using this feedback to dynamically adjust which clients to reject, thereby optimizing bandwidth usage while maintaining service coverage
3Reliability
If clients are rejected based on connection quality metrics, then load balancing improves, but system complexity increases due to multiple calculation factors
Solution Approach 1:
The patent manages complexity by defining a structured set of parameters for rejection calculation including signal quality metrics, server load indicators, and connection history. These parameters are combined using weighted formulas that can be configured independently, allowing the system to adjust complexity by adding or removing parameters without redesigning the entire rejection mechanism
4Reliability
If the rejection probability is high for overloaded servers, then load balancing improves, but client service availability decreases
Solution Approach 1:
The system dynamically adjusts rejection probability based on real-time server load conditions. When servers are overloaded, rejection probability increases to redistribute clients; when load decreases, rejection probability decreases to improve service availability. This dynamic adjustment ensures load balancing is achieved only when necessary, maintaining high availability during normal operation
Data Source
AI summary
The method comprises the following steps: connecting each client (5) to a respective one of said servers (3) and establishing a data communication between each client (5) and the respective server (3), thus forming a multi-client/multi-server network; 5 calculating a figure of merit for rejection (FoMR) for at least one client (5) con-nected to at least one of said servers (3), each figure of merit for rejection (FoMR) determining a probability of rejection of the relevant client (5) by the server (3); rejecting at least one client (5), which is connected to a server (3), and placing 10 said client in a non-connected condition; wherein the client to be rejected is selected on the basis of the figure of merit for rejection (FoMR); connecting the rejected client (5) to a server (3) again.