V. Pryyma, L. Bölöni, and D. Turgut. Active time scheduling for rechargeable sensor networks. Computer Networks (Elsevier), 54(4):631–640, March 2010.
Recent progress in energy harvesting technologies made it possible to build sensor networks with rechargeable nodes which target an indefinitely long operation. In these networks, the goal of energy management is to allocate the available energy such that the important performance metrics, such as the number of detected threats, are maximized. As the harvested energy is not sufficient for continuous operation, the scheduling of the active and inactive time is one of the main components of energy management. The active time scheduling protocols need to maintain the energy equilibrium of the nodes, while considering the uncertainties of the energy income, which is strongly influenced by the weather, and the energy expenditures, which are dependent on the behavior of the targets. In this paper, we describe and experimentally compare three active time scheduling protocols: (a) static active time, (b) dynamic active time based on multi-parameter heuristic and and (c) utility-based uniform sensing. We show that protocols which take into consideration the probabilistic models of the energy income and expenditure and can dynamically adapt to changes in the environment, can provide a significant performance advantage
@article{Pryyma-2010-ComNet,
author= "V. Pryyma and L. B{\"o}l{\"o}ni and D. Turgut",
title= "Active time scheduling for rechargeable sensor networks",
journal ="Computer Networks (Elsevier)",
year = "2010",
month = "March",
volume = "54",
number = "4",
pages = "631-640",
abstract = {
Recent progress in energy harvesting technologies made it possible
to build sensor networks with rechargeable nodes which target an
indefinitely long operation. In these networks, the goal of energy
management is to allocate the available energy such that the
important performance metrics, such as the number of detected
threats, are maximized. As the harvested energy is not sufficient
for continuous operation, the scheduling of the active and
inactive time is one of the main components of energy management.
The active time scheduling protocols need to maintain the energy
equilibrium of the nodes, while considering the uncertainties of
the energy income, which is strongly influenced by the weather,
and the energy expenditures, which are dependent on the behavior
of the targets. In this paper, we describe and experimentally
compare three active time scheduling protocols: (a) static active
time, (b) dynamic active time based on multi-parameter heuristic
and and (c) utility-based uniform sensing. We show that protocols
which take into consideration the probabilistic models of the
energy income and expenditure and can dynamically adapt to changes
in the environment, can provide a significant performance
advantage
},
}
Generated by bib2html.pl (written by Patrick Riley, Lotzi Boloni ) on Fri Jan 29, 2021 20:15:21