Weight-Based Distribution for Consistent Hashing
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Solution Overview
Problem
Existing consistent hashing algorithms struggle to effectively manage load balancing across servers with varying capacities and resource utilization costs, particularly in scenarios with disproportionate loads and heterogeneous server capabilities.
Innovation Solution
The implementation of weight-based distribution mechanisms within consistent hashing algorithms, where servers are assigned weights based on their processing power or storage capacity, and replicas are generated accordingly to manage requests and distribute resources efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a consistent hashing algorithm is used to distribute traffic uniformly across servers, then load distribution is improved, but servers with heterogeneous capacities cannot be effectively managed
Solution Approach 1:
The patent applies local quality by assigning different weights to different servers based on their individual capacities. High-capacity servers receive higher weights and thus more traffic, while low-capacity servers receive lower weights and less traffic. This resolves the contradiction by making the load distribution adaptive to local server characteristics rather than applying a uniform distribution approach.
Solution Approach 2:
The patent changes the parameter of traffic distribution from uniform to weight-proportional. By introducing weight parameters that reflect server capacities, the system can dynamically adjust traffic allocation based on server capabilities, thereby achieving both improved load distribution and adaptability to heterogeneous server capacities.
2Device complexity
If servers with different capacities are assigned equal traffic distribution, then simplicity is maintained, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent introduces weight parameters to change the distribution mechanism from simple equal allocation to capacity-proportional allocation. This adds a parameter (weight) that reflects server capacity, enabling the system to achieve better resource utilization efficiency without significantly increasing complexity, as the weight-based approach builds upon the existing consistent hashing framework.
3Productivity
If weight-based replica generation is implemented, then disproportionate load management is improved, but algorithm complexity increases
Solution Approach 1:
The patent applies local quality by generating a different number of replicas for each server based on its weight. High-capacity servers generate more replicas and thus handle more traffic, while low-capacity servers generate fewer replicas. This resolves the contradiction by making the replica generation process adaptive to local server characteristics, improving load management while keeping the complexity increase manageable.
Data Source
AI summary
Systems and methods for weight-based distribution for consistent hashing algorithm are provided. A system can include one or more processors, coupled with memory. The one or more processors can maintain a table of a count of replicas of each of a plurality of services that is generated based on a weight of each of the plurality of services. The one or more processors can receive, from a client device remote from the one or more processors, a request. The one or more processors can select, from the table based on the request, a service of the plurality of services. The one or more processors can route the request to the selected service of the plurality of services.