FUNCTION COMPUTING IN VERTICALLY PARTITIONED DISTRIBUTED DATABASES
Kaustubh Shinde · OhioLink ETD Center (Ohio Library and Information Network) · 2006
Advances in database and storage technology and need to manage constant flow of information have necessitated use of databases for every organization.These databases are independently owned and operated by respective organizations and privacy of data prevents complete data sharing between entities.Combined data from multiple sources potentially can contribute to mutually beneficial computations.This thesis perceives independent databases as single logical database partitioned and distributed over a number of locations and aims to compute complex mathematical functions over vertically distributed databases while preserving privacy of data.A Global function to be computed over single logical database, as we perceive it, is broken into a set of Local functions that operate on individual data sites.We developed an iterative algorithm and it's variation that performs global computation using summaries of local computations.The working of the algorithms was shown through software simulations and effectiveness of the suggested approach was demonstrated.