Decentralized Load-Aware Server Cluster Balancing
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Solution Overview
Problem
Current content delivery systems face challenges in efficiently distributing traffic across a cluster of servers, leading to inconsistent load balancing and potential server overload, which can result in decreased performance and user experience.
Innovation Solution
A load-aware load-balancing cluster system is implemented, where each server in the cluster decides whether to handle incoming traffic and can hand off connections to other servers based on load categorization and resource availability, using a hash function for initial connection mapping and a partition function for request handling, with a heartbeat mechanism for monitoring and maintaining cluster state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a central load balancer is used to distribute traffic, then load balancing control is centralized and simple to implement, but system complexity increases and single point of failure risk increases
Solution Approach 1:
The patent extracts the load balancing function from a central controller and distributes it to individual servers. Each server independently determines whether to handle incoming traffic by evaluating its own load state and the load states of other servers, eliminating the need for a central load balancer and reducing system complexity.
Solution Approach 2:
Each server in the cluster performs self-evaluation of its load state and actively participates in load balancing decisions. Servers monitor their own processing status and communicate with peers to collectively determine traffic distribution, enabling autonomous load balancing without external control.
2Ease of manufacture
If traffic is distributed without load awareness, then implementation is simple, but server overload occurs and performance decreases
Solution Approach 1:
The patent implements a feedback mechanism where servers continuously monitor their own load states and communicate this information to other servers in the cluster. This feedback loop enables servers to adjust traffic handling decisions based on real-time load conditions, preventing server overload while maintaining simple implementation.
Solution Approach 2:
The load balancing approach is dynamic rather than static. Servers can change their load handling capacity over time based on actual processing status, and the system adapts traffic distribution in real-time. This dynamic adjustment prevents server overload without requiring complex predetermined load distribution rules.
3Measurement precision
If servers continuously monitor load states, then load balancing accuracy improves, but processing time increases
Solution Approach 1:
The patent applies partial monitoring by having servers track only the most critical load metrics necessary for making load balancing decisions, rather than continuously monitoring all possible system parameters. This partial action approach maintains sufficient load state accuracy while minimizing processing time overhead.
Data Source
AI summary
A load-aware load-balancing cluster includes a switch having a plurality of ports; and a plurality of servers connected to at least some of the plurality of ports of the switch. Each server is addressable by the same virtual Internet Protocol (VIP) address. Each server in the cluster has a mechanism constructed and adapted to respond to determine the particular server's own measured load; convert the particular server's own measured load to a corresponding own particular load category of a plurality of load categories; provide the particular server's own particular load category to other servers of the plurality of servers; obtain load category information from other servers of the plurality of servers; and maintain, as an indication of server load of each of the plurality of servers, the particular server's own particular load category and the load category information from the other servers.