Flow-Based Energy Services Composition

We propose a novel spatio-temporal service composition framework for crowdsourcing
multiple
IoT energy services to cater to
multiple
energy requests. We define a new energy service model to leverage the
wearable-based
energy and wireless power transfer technologies. We reformulate the problem of spatio-temporal service composition to provision multiple energy requests as
a matching problem
. We leverage the
fragmented
nature of energy to offer
partial
services to maximize the utilization of energy services. We propose
EnergyFlowComp
, a modified Maximum Flow matching algorithm that efficiently provisions IoT energy services to accommodate multiple energy requests. Moreover, we propose
PartialFlowComp
, an extension of the
EnergyFlowComp
approach that considers the
partial-temporal

overlap
between services and requests in provisioning. We conduct an extensive set of experiments to assess the effectiveness and efficiency of the proposed framework.