XOR Star and XOR Chain Load Balancing in Distributed Storage
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Solution Overview
Problem
Current geographically distributed data storage systems face challenges in balancing storage loads efficiently, particularly in large-scale setups, as external load balancers can affect write performance and require complex coordination, and existing data protection methods often result in capacity overhead.
Innovation Solution
Implementing a mechanism that combines XOR Star and XOR Chain techniques for internal load balancing, allowing zones to switch between default and rebalancing modes independently, without the need for external load balancers, and providing native disaster recovery support by using geographically distributed replication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If an external load balancer is used to balance data storage between zones, then load balancing is achieved, but write performance is degraded due to traffic redirection
Solution Approach 1:
The patent extracts the load balancing function from external load balancers and implements it natively within the distributed storage system itself. Each storage node independently determines its load status and participates in load balancing operations, eliminating the need for external traffic redirection and avoiding write performance degradation.
Solution Approach 2:
The system implements self-service load balancing where storage nodes autonomously monitor their own load conditions, identify imbalances, and execute rebalancing operations without external coordination. The system self-regulates data distribution across zones based on real-time load conditions, improving write performance while maintaining load balance.
2Adaptability or versatility
If external load balancers are used for load balancing, then data distribution is optimized, but system complexity increases due to coordination requirements
Solution Approach 1:
The patent segments the load balancing function into independent operations at each storage node. Instead of a centralized coordination model, each node independently determines load conditions, identifies rebalancing opportunities, and executes local data migration decisions, significantly reducing system coordination complexity.
Solution Approach 2:
The system implements local quality by allowing each storage node to independently assess its own load conditions and make localized rebalancing decisions. This distributed decision-making approach eliminates the need for complex global coordination while achieving effective data distribution optimization.
3Reliability
If traditional data protection replication is used, then data safety is ensured, but capacity overhead increases
Solution Approach 1:
The patent merges data protection replication with load balancing operations. The same data migration mechanisms used for load balancing also serve replication purposes, allowing the system to achieve both data safety and load optimization without additional capacity overhead. XOR-based parity data is used to provide protection while minimizing storage requirements.
Solution Approach 2:
The system changes the parameter of data protection from traditional full replication to XOR-based parity protection, which reduces capacity overhead while maintaining data reliability. This parameter change allows the system to provide robust data protection with minimal additional storage requirements.
Data Source
AI summary
The disclosure relates to data protection management for geographically distributed storage systems. Specifically, the present disclosure provides a mechanism for load balancing by combining the techniques of XOR Star and XOR Chain to control the protection of data internally. The load balancing is done by each zone without the need for an external load balancer. In addition, the load balancing mechanism provides the ability for native (e.g. without additional configuration) support of disaster recovery.