Reliability Model for Incentive-Driven IoT Energy Services

TL;DR

This paper introduces a reliability model for IoT energy services that leverages consumer behavior and incentives to enhance participation and optimize energy request scheduling.

Contribution

It presents a novel reliability model based on user history and incentives, along with adaptive scheduling methods to improve IoT energy sharing efficiency.

Findings

Proposed reliability model increases provider incentives.

Adaptive scheduling improves energy request reliability.

Experimental results confirm approach efficiency.

Abstract

We propose a novel reliability model for composing energy service requests. The proposed model is based on consumers' behavior and history of energy requests. The reliability model ensures the maximum incentives to providers. Incentives are used as a green solution to increase IoT users' participation in a crowdsourced energy sharing environment. Additionally, adaptive and priority scheduling compositions are proposed to compose the most reliable energy requests while maximizing providers' incentives. A set of experiments is conducted to evaluate the proposed approaches. Experimental results prove the efficiency of the proposed approaches.