Journal
IEEE TRANSACTIONS ON SERVICES COMPUTING
Volume 15, Issue 3, Pages 1280-1294Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TSC.2020.2980258
Keywords
Internet of Things; Wireless communication; Wireless sensor networks; Quality of service; Crowdsourcing; Smart phones; Sensors; IoT services; crowdsourced energy services; spatio-temporal composition; multiple local knapsack optimization
Funding
- Qatar National Research Fund (Qatar Foundation) [NPRP9-224-1-049]
- Australian Research Council [DP160100149, LE180100158]
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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.
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.
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