Crowdsourcing Energy as a Service

Lakhdari, Abdallah; Bouguettaya, Athman; Neiat, Azadeh Ghari

doi:10.1007/978-3-030-03596-9_24

Cited by 30 publications

(64 citation statements)

References 10 publications

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“…IoT-based energy services are modelled using the spatio-temporal aspects of device owners [3]. We extend the existing energy service model [5] by considering the dynamic energy usage behavior of providers and consumers. We formally define the crowdsourced energy service model as follows.…”

Section: Crowdsourced Energy Service Modelmentioning

confidence: 99%

“…For example, a set of co-located smartphones may provide computing or storage for a nearby resourceconstrained smartwatch to render a map journey [4]. IoT devices can provide various types of crowdsourced services such as WiFi hotspots, wireless charging and environmental sensing [3], [5], [6]. This provides opportunities to build novel applications such as spatio-temporal targeted recommender systems [7] and shared IoT service markets [8].…”

Section: Introductionmentioning

confidence: 99%

“…The function of the wireless delivery of energy is represented formally along with its non-functional attributes (i.e., Quality of Service (QoS)). The service abstraction enables some key operations such as the discovery of available energy services, and the composition of energy services based on users' requirements [5].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the selected set of crowdsourced energy services will not fulfil the requirement of a consumer if these services are not composable according to: (i) their spatio-temporal features and (ii) preferences of the energy consumers. We propose a composition framework of energy services extending the energy service model proposed in [5]. The proposed framework considers all the aforementioned challenges except the volatile behavior of energy services due to the mobility of the crowd.…”

Section: Introductionmentioning

confidence: 99%

“…Crowdsourced energy services in confined areas crowdsourced energy services depends on defining the context (i.e., location and time of the day) in addition to the usage behavior of the IoT user[20]. We propose a composition framework of energy services extending the energy service model proposed in[5]. The proposed framework considers all the aforementioned challenges except the volatile behavior of energy services due to the mobility of the crowd.…”

mentioning

confidence: 99%

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Composing Energy Services in a Crowdsourced IoT Environment

Lakhdari

Bouguettaya

Mistry

et al. 2022

IEEE Trans. Serv. Comput.

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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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Section: Crowdsourced Energy Service Modelmentioning

confidence: 99%