Scheduling Server Dynamic Load Balancing for CDNs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In Content Delivery Networks (CDNs), existing load balancing methods fail to fully utilize resources and ensure timely service delivery when some Content Delivery Function (CDF) entities are operational but with reduced processing capability, leading to potential service failures and resource wastage.
Innovation Solution
A method and system that select content delivery devices based on service processing information, such as the number or percentage of successfully and unsuccessfully processed services, to determine abnormal devices and adjust delivery proportions, ensuring that service requests are routed to devices with higher processing capabilities, thereby improving successful service delivery and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If service requests are delivered according to load balancing principle to multiple CDF entities, then resource utilization is improved, but service timeliness deteriorates when some CDF entities have reduced processing capability
Solution Approach 1:
The patent implements dynamic delivery proportion adjustment based on real-time service processing information. The scheduling server continuously monitors the performance of each CDF entity and dynamically adjusts the delivery proportion for each entity, transitioning from static load balancing to dynamic adaptive routing. This allows the system to respond to changing conditions and allocate traffic optimally based on current capabilities.
Solution Approach 2:
The patent establishes a feedback mechanism where the scheduling server receives service processing information from CDF entities and uses this feedback to adjust delivery proportions. The system collects data on successfully processed services, unsuccessfully processed services, and other performance metrics, then uses this feedback to optimize future routing decisions, creating a closed-loop control system.
2Quantity of substance
If service requests are delivered to CDF entities with reduced processing capability according to load balancing, then resource utilization is improved, but service success rate deteriorates
Solution Approach 1:
The system dynamically adjusts delivery proportions based on real-time service processing information, allowing CDF entities with reduced capability to handle only appropriate portions of traffic. The scheduling server continuously adapts the routing strategy to match current system conditions, optimizing both resource utilization and service success rate simultaneously.
Solution Approach 2:
The patent changes the delivery proportion parameter for each CDF entity based on their service processing performance. By adjusting this key parameter dynamically, the system optimizes the distribution of service requests to match the actual capabilities of each entity, thereby improving overall service success rate while maintaining resource utilization.
3Device complexity
If service requests are delivered according to load balancing without considering actual processing capability, then system simplicity is maintained, but service timeliness and success rate deteriorate
Solution Approach 1:
The CDF entities autonomously provide service processing information to the scheduling server, and the scheduling server automatically adjusts delivery proportions based on this information. The system performs self-optimization without requiring manual intervention, maintaining operational simplicity while improving service timeliness through automated adaptive routing.
Solution Approach 2:
The patent implements a feedback-based automatic adjustment mechanism that maintains system simplicity while improving performance. The scheduling server automatically receives performance data, processes it, and adjusts delivery proportions without human intervention, balancing complexity and effectiveness.
4Quantity of substance
If CDF entities with reduced processing capability continue to receive service requests according to load balancing, then resource utilization appears improved, but actual service delivery effectiveness deteriorates
Solution Approach 1:
The system dynamically adjusts delivery proportions to match the actual processing capability of each CDF entity. By continuously monitoring service processing information and adapting traffic distribution in real-time, the system ensures that resource utilization translates into actual service delivery effectiveness, preventing the mismatch between theoretical and actual productivity.
Solution Approach 2:
The patent changes the delivery proportion parameter based on service processing performance metrics. This parameter adjustment ensures that CDF entities with reduced capability receive appropriate traffic levels, optimizing the relationship between resource utilization and actual service delivery effectiveness.
Data Source
Figure 1~2
Figure 3~4
Figure 5~6
AI summary
The present invention discloses a method, a system, and a scheduling server for content delivery, and pertains to the field of multimedia technologies. he method includes: receiving a service request for accessing content; selecting, according to service processing information of each device storing the content, one device to respond to the service request, where the service processing information includes at least one of the number of services successfully processed, a percentage of services successfully processed, the number of services unsuccessfully processed, and a percentage of services unsuccessfully processed; and base upon the selection, sending the received service request to the selected device. The system includes: a scheduling server and a content delivery device. By delivering the service request according to the number of services successfully processed, or a percentage of services successfully processed, or the number of services unsuccessfully processed, or a percentage of services unsuccessfully processed of the devices, the present invention may not only improve the percentage of services successfully processed, but also prevent waste of resources and reduce unnecessary service loss, therefore serving users better.