Composing Energy Services in a Crowdsourced IoT Environment

TL;DR

This paper introduces a novel framework for composing crowdsourced wireless energy services in IoT environments, utilizing a new service model and a knapsack-based selection approach to optimize energy delivery.

Contribution

It presents a new energy service model and a composability framework considering spatio-temporal factors, along with a heuristic approach for optimal energy service composition in IoT.

Findings

The proposed approach effectively selects energy services with high efficiency.

Experimental results show improved energy delivery and resource utilization.

The framework outperforms existing methods in terms of effectiveness and efficiency.

Abstract

We propose a novel framework for composing crowdsourced wireless energy services to satisfy users' energy requirements in a crowdsourced Internet of Things (IoT) environment. A new energy service model is designed to transform the harvested energy from IoT devices into crowdsourced services. We propose a new energy service composability model that considers the spatio-temporal aspects and the usage patterns of the IoT devices. A multiple local knapsack-based approach is developed to select an optimal set of partial energy services based on the deliverable energy capacity of IoT devices. We propose a heuristic-based composition approach using the temporal and energy capacity distributions of services. Experimental results demonstrate the effectiveness and efficiency of the proposed approach.