English
资源说明：For the perpetual wireless sensor network (WSN),
energy harvesting (EH) technology is emerging as a promising
solution. However, the randomness and the instability of the
harvested energy may lead to the occurrence of the temporal
death, which is harmful to the functions of the WSN, and has
negative impact on the quality of service of the network. With
temporal death being taken into account, this paper proposes a
novel and overall framework, namely, a multi-layer Markov fluid
queue (MLMFQ) model, for modeling and analyzing the data
transmission nature of the EH devices (EHDs). We formulate the
model of the whole system in terms of MLMFQ, and obtain the
stead-state probabilities of the EHD. We study the issue of how
to maximize the steady-state average reward rate of the reported
data packets. We then propose an optimization model, in which
one can maximize the overall steady-state average reward rate
with relation to transmission policy under the specific constraints.
On this basis, we are able to propose an algorithm for calculating
the optimal transmission policy of the EHD with temporal death.
We validate our results using a numerical example and report
some interesting findings from our numerical studies.
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