Self-Organizing Linear Network for Parallel Management
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Solution Overview
Problem
Existing network management systems face challenges in efficiently managing large-scale networks due to high latency, resource-intensive operations, and the inability to perform real-time management, leading to inaccurate and untimely information collection and reporting.
Innovation Solution
A network management system where nodes self-organize into a linearly ordered sequence, allowing queries to be injected and propagated in parallel along local segments, enabling each node to respond and aggregate management information, which is then reported to a server in real time, reducing resource demands and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional network management systems collect information from all devices, then comprehensive network status information is obtained, but the time required for collection increases significantly and real-time management becomes infeasible
Solution Approach 1:
The network is divided into linearly ordered local segments with first machines and second machines. Queries are segmented and injected at first machines, then propagated through local segments in parallel, allowing comprehensive information collection without centralized sequential processing delays
Solution Approach 2:
Machines self-organize into linearly ordered sequences and prepare query propagation paths in advance. When a query is injected, the pre-established segment structure enables immediate parallel propagation through all local segments, eliminating the need for dynamic routing decisions during query execution
2Ease of operation
If network management operations are performed on large-scale networks, then complete network control is achieved, but resource consumption and computation requirements become prohibitively high
Solution Approach 1:
Management operations are segmented into local segment-level queries that propagate in parallel. This distributes computation across the network rather than concentrating it at a central server, reducing overall resource consumption while maintaining complete network control
Solution Approach 2:
Each machine in the local segment autonomously responds to queries and contributes its own local information to the payload. This self-service approach eliminates the need for a resource-intensive central server to collect and process all information, allowing large-scale networks to be managed with minimal external resources
3Measurement precision
If information is collected sequentially from network devices, then accurate status data is obtained, but the collection process takes too long and data becomes obsolete
Solution Approach 1:
The linearly ordered segment structure is pre-established through self-organization, enabling queries to propagate immediately through all segments in parallel upon injection. This preliminary structuring transforms sequential information collection into parallel processing, maintaining data accuracy while dramatically improving collection speed
Solution Approach 2:
The system transitions from sequential single-threaded information collection to parallel multi-threaded propagation through the linearly ordered segments. This dimensional change from one-dimensional sequential processing to multi-dimensional parallel processing enables simultaneous data gathering from multiple devices, improving both speed and accuracy
Data Source
AI summary
A non-static collection of machines self-organizes into a linear communication orbit. A server has sent a data unit to a subset of machines in the linear communication orbit. A first machine receives a plurality of shards of the data unit from an upstream neighbor of the first machine in the linear communication orbit and sends the plurality of shards of the data unit to a downstream neighbor of the first machine in the linear communication orbit. The first machine selects and maintains a subset of the plurality of shards of the data unit in a local cache of the first machine according to a data caching method. The first machine selects the subset of the plurality of shards it maintains independently of whether the subset of the plurality of shards are maintained locally by the upstream neighbor and the downstream neighbor of the first machine in the linear communication orbit.