Web Services for Asynchronous, Distributed Optimization Using Conservative Signal Processing
Year: 2015
Type: preprint
Abstract: This paper presents a systematic approach for implementing a class of nonlinear signal processing systems as a distributed web service, which in turn is used to solve optimization problems in a distributed, asynchronous fashion. As opposed to requiring a specialized server, the presented approach requires only the use of a commodity database back-end as a central resource, as might typically be used to serve data for websites having large numbers of concurrent users. In this sense the presented approach leverages not only the scalability and robustness of various database systems in sharing variables asynchronously between workers, but also critically it leverages the tools of signal processing in determining how the optimization algorithm might be organized and distributed among various heterogeneous workers. A publicly-accessible implementation is also presented, utilizing Firebase as a back-end server, and illustrating the use of the presented approach in solving various optimization problems commonly arising in the context of signal processing.
Source: arXiv (Cornell University)
Authors: Lahlou, Tarek A., Baran, Thomas A.
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2294857236