Optimal Control Based on Scheduling for Comfortable Smart Home Environment

Sehrish Malik,Dohyeun Kim,Kyutae Lee

doi:10.1109/access.2020.3042534

Sehrish Malik, Dohyeun Kim + Show 1 more

Open Access

https://doi.org/10.1109/access.2020.3042534

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 35	License type: CC BY 4.0

Affiliation: Kongju National University, Jeju National University

Abstract

Smart home environments account to a major portion of the total energy consumption in today’s world. The residents of smart home environments wish to find solutions that reduce the energy costs along with providing an optimal indoor environment for the residents. Another significant aspect in smart home systems is efficiency of tasks management and control commands’ execution for smart home actuators. In this paper, we propose an optimal control solution for smart home environment based on smart home energy optimization and control tasks’ load dispatching and scheduling. Optimal control is achieved by first defining an objective function for minimizing energy cost which is implemented using VB-PSO (velocity boost particle swarm optimization) algorithm. Next, the control tasks are generated using rule set implemented in fuzzy logic; defined based on optimal values achieved from VB-PSO. A Markov model based mechanism dispatches control tasks at scheduler, for efficient scheduling and optimal control. The results show that the proposed optimization scheme saves up to 29.73% energy costs on average, in comparison to baseline scheme. The proposed tasks’ load dispatching scheme of admission control, makes the job of load balancing among the processors efficient while giving priority to the urgent tasks. The results for scheduler evidently show the low dropping probabilities for urgent tasks along with showing 34.9% reduction in tasks’ starvation rate and 36.82% reduction in average tasks’ instances missing rates.

Highlights

An average household consumes 90 million BTUs of energy yearly and a major chunk of this energy is wasted based on survey conducted by U.S department of energy [1]
A fuzzy logic-based solution is implemented for optimal control decision making and generation of control tasks while a load dispatching algorithm using Markov model is presented for load balancing, load prioritizing and distributed load scheduling
As the load of normal tasks is varying and the scheduler’s tasks dispatching unit has set a threshold to spare enough slots for urgent tasks to be processed for admission control, the dropping rate of urgent tasks is very low for admission control scheme in comparison to the no admission control

Summary

INTRODUCTION

S. Malik et al.: Optimal Control Based on Scheduling for Comfortable Smart Home Environment. Consumption, reducing energy costs, continuous energy consumption monitoring, maintaining user comfort index, environmental conditions based rule design, smart control of home appliances, and efficient scheduling [3], [4]. Based on the recent survey results, some of the major limitations in the existing solutions are consideration of efficient load scheduling algorithms with load balancing and admission control measures, and optimal decision making in order to prioritize existing appliances load. We propose a scheduling mechanism based optimal control solution for smart homes. A fuzzy logic-based solution is implemented for optimal control decision making and generation of control tasks while a load dispatching algorithm using Markov model is presented for load balancing, load prioritizing and distributed load scheduling.

RELATED WORKS

INPUT TASK MODELING

PERFORMANCE ANALYSIS

IMPLEMENTATION ENVIRONMENT

Findings

CONCLUSION