Distributed Storage Using Similarity-Aware-Partitioning

Web Published:
1/13/2014
Description:

Distributed Storage Using Similarly-Aware-Partitioning

Princeton Docket # 14-2948

 

Data volumes are increasing at an unprecedented rate due to the advent of large social networks, on-demand cloud-based video services, and file sharing applications. To store and access data efficiently, there has been an increased demand for distributed data stores. These storage services face an ever-increasing demand on their systems and must satisfy two important concerns: they should be space-efficient to manage the high volumes of data, and they should be access-efficient in terms of minimizing network accesses to read or write to these files

 

Researchers in the Department of Electrical Engineering at Princeton University have developed a distributed storage tool in Java based on Similarity-Aware-Partitioning (SAP) algorithms. This algorithmic technique is used to present solutions that are both space-efficient and access-efficient. This technique has considerable utility in terms of the cost of disk/memory required for storage while ensuring that customer deadlines are met due to the low access costs. Further, this novel technique presents fundamental insights in how to exploit similarity among data. This technology can be used in other areas that deal with data, such as data processing, analytics, and data communication. In addition, distributed storage systems form the backbone of many web-based services. This novel distributed storage tool based on the new algorithms can be used to perform deduplication in such storage systems.

 

Applications:   

·         Data Processing

 

·         Analytics

 

·         Data Communication

 

      ·       Deduplication in Storage Systems

 

Advantages:

·         Space-Efficient

 

·         Access-Efficient

 

·         Low Access Costs

 

·         Exploits similarity among data

 

Faculty Inventor

 

Mung Chiang is the Arthur LeGrand Doty Professor of Electrical Engineering at Princeton University. His research on networking received the Alan T. Waterman Award (2013) and the IEEE Kiyo Tomiyasu Award (2012).  A Technology Review TR35 Award recipient (2007) and founder of the Princeton EDGE Lab, his technologies have resulted in several industry adoptions and startup companies in communication networks, mobile content, and education technologies. As an educator, he received the Terman Award (2013) from ASEE, started the “3 Nights and Done” learning platform, and his Massive-Open-Online-Course reached 100,000 students in 2012-2013. The corresponding textbook, “Networked Life: 20 Questions and Answers,” received the PROSE Award in Engineering and Technology (2012) from AAP. He chairs Princeton University’s Committee on Classroom Design, the founding steering committee of IEEE Transactions on Network Science and Engineering, and co-chaired the U.S. NITRD Workshop on Complex Engineered Networks.

 

Intellectual Property Status

Patent protection is pending.

Princeton is seeking to identify appropriate partners for further development and commercialization of this technology.

 

Contact

Michael Tyerech
Princeton University Office of Technology Licensing • (609) 258-6762• tyerech@princeton.edu

Laurie Bagley
Princeton University Office of Technology Licensing • (609) 258-5579•
lbagley@princeton.edu

 

 

 

Patent Information:
Category(s):
Computers and Software
For Information, Contact:
Michael Tyerech
former Princeton Sr. Licensing Associate
Princeton University
mtyerech@rd.us.loreal.com
Inventors:
Bharath Balasubramanian
Tia Lan
Mung Chiang
Keywords:
computers/software
Opto-Electronics/ELE ENG