Data Bridge – Components for Real-Time Data Remote Access
A system that enables remote complex system data access requires the ability to access diverse system data from a variety of platforms and deliver it to experts quickly and accurately. This system must sift through large and fast streams of binary data, access the most relevant data, and then be able to move the most important data reliably over limited shared networks. Finally, the system must provide this data in a meaningful way to the team of experts. The diagram below illustrates the required elements to bridge this complex system maintenance data from the system site to a central location.
Connectors provide several ways to access system data from heterogeneous source data. Curation selects the most important data from a large and fast stream of data. Compression further reduces this data. Transport provides the capability to store, prioritize and quickly and accurately forward data when the operational needs and bandwidth allows. Transport provides the intelligence to efficiently move data across multiple networks with varying reliability. At the central location, data is reassembled, reversing Transport, Compression and Curation. A final step makes the data available to a variety of data consumers using different tools, analyses, and computer platforms so that the data is understandable and useful.
Data Bridge Components for Real-Time Data Remote Access
Optimization of data compression, data transfer and data curation is best accomplished when such processing is dependent on the data itself. With access to metadata specific to each data stream, it is possible to manipulate the data to achieve such optimization. This can be applied to each of the components of the solution:
- Transport – Data transfer protocols and coding can be tailored based on the structure of the data and the reliability and retransmission requirements of each data set so that the data can arrive at its destination quickly and accurately. Prioritization and Bandwidth management can take advantage of data knowledge embedded in the metadata to best utilize available bandwidth.
- Compression – Compression algorithms can be selected that are optimal for a particular data set rather than attempting to use a single algorithm for all data.
- Curation – Curation can be performed on each data set in a manner that is tailored for the needs of that particular data type.
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Challanges of Remote System Test Maintenance and Sustainment
Effecient Data Capture and Movement
Data Bridge Architecture