17886860. Scalable and Cost-Efficient Information Retrieval Architecture for Massive Datasets simplified abstract (GOOGLE LLC)
Scalable and Cost-Efficient Information Retrieval Architecture for Massive Datasets
Organization Name
Inventor(s)
David Simcha of Jersey City NJ (US)
Alexander-Teodor Voicu of Zurich (CH)
Felix Chern of New York NY (US)
Philip Wenjie Sun of New York NY (US)
Hanna Maria Pasula of Zurich (CH)
Martin Ulrich Seiler of Mutschellan (CH)
Scalable and Cost-Efficient Information Retrieval Architecture for Massive Datasets - A simplified explanation of the abstract
This abstract first appeared for US patent application 17886860 titled 'Scalable and Cost-Efficient Information Retrieval Architecture for Massive Datasets
Simplified Explanation
The patent application describes a scalable and cost-efficient storage architecture for large-scale datasets, such as Internet-scale datasets with billions of data elements. The architecture includes a bifurcated storage system with two sets of storage media, each storing a data index with different latency levels.
- The storage architecture is designed for large-scale datasets with very large numbers of data elements.
- The architecture includes two sets of storage media, each storing a data index.
- The first set of storage media has lower latency than the second set.
- The bifurcated storage system allows for efficient storage and retrieval of data elements.
Potential Applications
- Big data storage and retrieval systems
- Cloud storage solutions
- Internet of Things (IoT) data management
Problems Solved
- Efficient storage and retrieval of large-scale datasets
- Cost-effective storage solutions for Internet-scale datasets
- Scalability for handling billions of data elements
Benefits
- Lower latency for accessing data elements
- Cost-efficient storage architecture
- Scalability for handling large-scale datasets
Original Abstract Submitted
Provided is a scalable and cost-efficient storage architecture for large-scale datasets, such as Internet-scale datasets that include very large numbers (e.g., billions) of data elements. More particularly, provided is a bifurcated storage architecture that includes a first data index stored by a first set of storage media and a second data index stored by a second set of storage media, where the first set of storage media has a lower latency than the second set of storage media.
