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We study the optimal control of a class of resource
allocation problems characterized by energy-latency
trade-offs in Wireless Sensor Networks (WSN) using
the framework of Discrete Event Systems. Our work is
based on the observation that energy of wireless
nodes can be greatly saved by introducing some delay
of task completion time. Specifically, we consider a
family of problems motivated by WSN such as Dynamic
Transmission Control and Dynamic Voltage Scaling,
where the objective is to minimize energy
consumption while satisfying real-time operating
constraints. Using advanced techniques, such as
sample path analysis and Receding Horizon Control,
we address both off-line and on-line scenarios and
have found better and more efficient solutions than
the existing ones in the literature. Our results do
not rely on the exact form of the cost function and
can be readily applied to other settings as long as
the cost function satisfies certain conditions.
This work is beneficial to students, scholars, and
engineers who are interested in utilizing advanced
control and optimization techniques to solve
resource allocation problems in wireless networks.
allocation problems characterized by energy-latency
trade-offs in Wireless Sensor Networks (WSN) using
the framework of Discrete Event Systems. Our work is
based on the observation that energy of wireless
nodes can be greatly saved by introducing some delay
of task completion time. Specifically, we consider a
family of problems motivated by WSN such as Dynamic
Transmission Control and Dynamic Voltage Scaling,
where the objective is to minimize energy
consumption while satisfying real-time operating
constraints. Using advanced techniques, such as
sample path analysis and Receding Horizon Control,
we address both off-line and on-line scenarios and
have found better and more efficient solutions than
the existing ones in the literature. Our results do
not rely on the exact form of the cost function and
can be readily applied to other settings as long as
the cost function satisfies certain conditions.
This work is beneficial to students, scholars, and
engineers who are interested in utilizing advanced
control and optimization techniques to solve
resource allocation problems in wireless networks.