Incentive-Based Selection and Composition of IoT Energy Services

Abusafia, Amani; Bouguettaya, Athman; Mistry, Sajib

doi:10.1109/scc49832.2020.00047

Cited by 20 publications

(25 citation statements)

References 22 publications

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“…We assume that the IoT coordinator provides incentives to encourage energy sharing in the form of credits. These would be used to receive more energy when the providers act as consumers in the future [29][1] [2]. The IoT coordinator is assumed to be deployed one hop away from the energy providers and consumers (e.g., router at the edge) to minimize the communication overhead and latency while advertising energy services and requests.…”

Section: Iot Coordinatormentioning

confidence: 99%

“…We create a crowdsourced IoT environment scenario close to reality. We mimic the energy sharing behavior of the crowd within microcells by utilizing a dataset published by IBM for a coffee shop chain with three branches in New York city 2 . The dataset consists of transaction records of customers purchases in each coffee shop for one month.…”

Section: Dataset and Experiments Environmentmentioning

confidence: 99%

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Fairness-aware Crowdsourcing of IoT Energy Services

Lakhdari¹,

Bouguettaya²

2021

Preprint

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We propose a Novel Fairness-Aware framework for Crowdsourcing Energy Services (FACES) to efficiently provision crowdsourced IoT energy services. Typically, efficient resource provisioning might incur an unfair resource sharing for some requests. FACES, however, maximizes the utilization of the available energy services by maximizing fairness across all requests. We conduct a set of preliminary experiments to assess the effectiveness of the proposed framework against traditional fairness-aware resource allocation algorithms. Results demonstrate that the IoT energy utilization of FACES is better than FCFS and similar to Max-min fair scheduling. Experiments also show that better fairness is achieved among the provisioned requests using FACES compared to FCFS and Max-min fair scheduling.

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Section: Iot Coordinatormentioning

confidence: 99%

Section: Dataset and Experiments Environmentmentioning

confidence: 99%

Fairness-aware Crowdsourcing of IoT Energy Services

Lakhdari¹,

Bouguettaya²

2021

Preprint

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“…We describe a scenario at the university campus where students move across, gather, and practice various activities in different confined places (i.e., microcells), e.g., library, study spaces, food court. We assume that students are incentivized to recycle the spare energy of their IoT devices by sharing it with nearby devices [15]. Energy providers advertise their energy services in different microcells within the smart campus according to their spatio-temporal preferences and their energy usage behavior.…”

Section: Motivating Scenariomentioning

confidence: 99%

Proactive Composition of Mobile IoT Energy Services

Lakhdari¹,

Bouguettaya²

2021

Preprint

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We propose a novel proactive composition framework of wireless energy services in a crowdsourced IoT environment. We define a new model for energy services and requests that includes providers' and consumers' mobility patterns and energy usage behavior. The proposed composition approach leverages the mobility and energy usage behavior to generate energy services and requests proactively. Preliminary experimental results demonstrate the effectiveness of generating proactive energy requests and composing proactive services.

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“…The harvested spare energy can be shared with nearby IoT devices as services (hence the name energy-as-a-service). Energy services may be achieved with the emergence of new technologies known as "Over-the-Air wireless charging" [9]. For example, Energous developed a technology to enable wireless charging up to a distance of 4.5 meters 2 .…”

Section: Introductionmentioning

confidence: 99%

Wireless IoT Energy Sharing Platform

Yao¹,

Abusafia²,

Lakhdari³

et al. 2022

Preprint

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Wireless energy sharing is a novel convenient alternative to charge IoT devices. In this demo paper, we present a peer-to-peer wireless energy sharing platform. The platform enables users to exchange energy wirelessly with nearby IoT devices. The energy sharing platform allows IoT users to send and receive energy wirelessly. The platform consists of (i) a mobile application that monitors and synchronizes the energy transfer among two IoT devices and (ii) and a backend to register energy providers and consumers and store their energy transfer transactions. The developed framework allows the collection of a real wireless energy sharing dataset. A set of preliminary experiments has been conducted on the collected dataset to analyze and demonstrate the behavior of the current wireless energy sharing technology.

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Incentive-Based Selection and Composition of IoT Energy Services

Cited by 20 publications

References 22 publications

Fairness-aware Crowdsourcing of IoT Energy Services

Fairness-aware Crowdsourcing of IoT Energy Services

Proactive Composition of Mobile IoT Energy Services

Wireless IoT Energy Sharing Platform

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