Composing Energy Services in a Crowdsourced IoT Environment

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.

Automated summary

We propose a novel framework for composing crowdsourced wireless energy services in a crowdsourced IoT environment to meet users' energy requirements. We design a new energy service model and propose a composability model that considers the spatio-temporal aspects and usage patterns of IoT devices. We develop a multiple local knapsack-based approach to select an optimal set of energy services and propose a heuristic-based composition approach. Experimental results demonstrate the effectiveness and efficiency of the proposed approach.