Distributed Data Tract Management for Datacenter Bandwidth Optimization
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Solution Overview
Problem
Large-scale datacenters face inefficiencies due to bandwidth bottlenecks, storage device failures, and inefficient data retrieval and recovery processes, particularly in the Map-Reduce model, where network congestion and redundant data copying lead to performance issues.
Innovation Solution
A system comprising multiple servers, a client, and a metadata server that distributes data tracts across servers using a locator table, enabling simultaneous read/write operations and efficient recovery by identifying and replicating data across multiple servers, thereby optimizing bandwidth utilization and reducing recovery time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored contiguously on a single storage device, then data retrieval is simple, but the full bandwidth of only one storage device is consumed while other devices sit idle
Solution Approach 1:
The patent divides data into multiple tracts and distributes them across multiple storage devices. When retrieving data, the system can access multiple storage devices simultaneously, thereby utilizing their collective bandwidth rather than being limited to a single device. This segmentation resolves the contradiction by maintaining simple retrieval operations while dramatically improving bandwidth utilization.
Solution Approach 2:
The patent combines multiple storage devices into a unified storage system where data tracts are distributed across them. The system merges the bandwidth capabilities of multiple devices to handle data retrieval operations in parallel, thus improving overall productivity while maximizing bandwidth utilization across the storage infrastructure.
2Reliability
If redundant copies of data are stored on separate devices, then data loss risk is minimized, but recovery time increases due to limited bandwidth for copying
Solution Approach 1:
The patent segments data into multiple tracts and distributes them across multiple storage devices, creating redundant copies of different tracts on different devices. When failure occurs, the system can retrieve data from multiple sources simultaneously, dramatically reducing recovery time while maintaining data reliability through distributed redundancy.
Solution Approach 2:
The system performs preliminary distribution of data tracts across multiple storage devices before any failure occurs. This preliminary action ensures that redundant copies are already in place and accessible, eliminating the need for time-consuming copying operations during recovery and thus reducing loss of time while maintaining reliability.
3Loss of information
If the entire storage device is scanned to identify files and locations, then complete information is obtained, but the process is slow and inefficient
Solution Approach 1:
The patent divides the storage device into multiple segments or zones, each with its own metadata information stored in memory. Instead of scanning the entire storage device, the system only needs to query the relevant memory tables for the specific zone containing the desired data, dramatically reducing scanning time while ensuring complete information is obtained about file locations.
4Device complexity
If the table is stored at a different location than the data being read/written, then data and metadata are separated, but the component must move across the storage device to update the table
Solution Approach 1:
The patent divides the storage device into multiple zones, with each zone having its metadata table stored in the memory of the same zone. This segmentation allows the read/write component to access both data and its corresponding metadata without moving across the storage device, improving speed while maintaining organized separation of data and metadata through zone-based structure.
Data Source
AI summary
A system including a plurality of servers, a client, and a metadata server is described herein. The servers each store tracts of data, a plurality of the tracts comprising a byte sequence and being distributed among the plurality of servers. To locate the tracts, the metadata server generates a table that is used by the client to identify servers associated with the tracts, enabling the client to provide requests to the servers. The metadata server also enables recovery in the event of a server failure. Further, the servers construct tables of tract identifiers and locations to use in responding to the client requests.