Distributed Storage Peer Group Task Assignment
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Solution Overview
Problem
Distributed data storage systems face performance bottlenecks due to centralized processing and transmission inefficiencies, particularly in high-volume conditions, leading to degraded system performance and increased latency and error rates.
Innovation Solution
A performance module identifies or predicts bottlenecks and assigns tasks to peer groups of data storage devices, designating master and slave devices to execute tasks without involving the network controller, thereby redistributing workload and maintaining consistent performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If centralized processing through network controller is used, then system coordination and control are simplified, but performance bottlenecks and latency increase under high-volume conditions
Solution Approach 1:
The patent segments the centralized processing function into distributed processing units across multiple data storage devices. Each device is assigned specific tasks by the performance module, dividing the overall processing workload from a single network controller across multiple devices, thereby reducing the bottleneck effect while maintaining coordinated control.
Solution Approach 2:
The patent transitions from a single-dimension centralized processing model to a multi-dimensional distributed processing architecture. By introducing spatial distribution across multiple devices and hierarchical task assignment (performance module → peer groups → individual devices), the system adds dimensional complexity to processing pathways, enabling parallel execution and reducing latency.
2Reliability
If network controller handles all task coordination, then centralized control is maintained, but workload on network controller increases causing bottlenecks
Solution Approach 1:
The patent extracts specific processing tasks from the network controller and assigns them to peer groups of data storage devices. The performance module identifies suitable tasks and reallocates them to downstream devices, effectively removing the bottleneck workload from the network controller while maintaining overall system coordination.
Solution Approach 2:
The patent enables data storage devices to perform processing tasks independently through self-service mechanisms. Once tasks are assigned by the performance module, peer groups execute them autonomously without requiring continuous network controller intervention, reducing the controller's workload while maintaining control consistency through initial task assignment and monitoring.
3Productivity
If tasks are distributed to peer groups, then network controller workload is reduced, but system complexity increases
Solution Approach 1:
The patent implements a universal performance module that can identify, evaluate, and assign multiple types of tasks to appropriate peer groups. This multi-functional component handles diverse processing requirements through a unified task assignment framework, managing distribution complexity while enabling flexible task allocation across different device configurations.
Solution Approach 2:
The patent incorporates feedback mechanisms where the performance module monitors task execution results and system performance metrics. This feedback loop enables dynamic adjustment of task assignments, optimization of peer group configurations, and identification of new bottlenecks, managing distribution complexity through continuous learning and adaptation.
Data Source
AI summary
A data storage system employing distributed memories can have at least one host connected to a plurality of data storage devices via a network controller. One or more performance bottlenecks through the network controller may be identified with a performance module. A peer group consisting of at least two of the plurality of data storage devices is created with the performance module in response to the identified performance bottleneck so that a task can be assigned by the performance module to the peer group. The task may be chosen to mitigate the performance bottleneck by avoiding involvement of the network controller in the task.