A serverless cloud computing framework for real-time appliance-usage recommendation

dc.contributor.author	Dash, S.
dc.contributor.author	Sodhi, R.
dc.contributor.author	Sodhi, B.
dc.date.accessioned	2021-06-08T20:22:09Z
dc.date.available	2021-06-08T20:22:09Z
dc.date.issued	2021-06-09
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/1776
dc.description.abstract	Real-time appliance-usage recommendation (RTAUR) is an essential pre-requisite for various demand response (DR) programmes. This paper presents a simple yet effective integer programming (IP)-based model to solve the applianceusage scheduling problem in a dynamic pricing scenario. The proposed work further explores the viability of using a Serverless cloud-computing (SCC) framework for the actual implementation of RT-AUR algorithm. The efficacy of the overall proposal is demonstrated using a co-simulation architecture, combining a grid-simulation platform- MATLAB with a real-time cloudcomputing platform- Amazon Web Services (AWS). Various cosimulation results clearly reveal the effectiveness of the proposed SCC framework for RT-AUR.	en_US
dc.language.iso	en_US	en_US
dc.subject	Demand Response	en_US
dc.subject	Integer Programming	en_US
dc.subject	Serverless Cloud Computing	en_US
dc.subject	Appliance-Usage Recommendation	en_US
dc.subject	Amazon Web Services	en_US
dc.title	A serverless cloud computing framework for real-time appliance-usage recommendation	en_US
dc.type	Article	en_US