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

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.