With the advancement of video sensors in the Internet of Things, Internet of
Video Things (IoVT) systems, capable of delivering abundant and diverse
information, have been increasingly deployed for various applications. However,
the extensive transmission of video data in IoVT poses challenges in terms of
delay and power consumption. Intelligent reconfigurable surface (IRS), as an
emerging technology, can enhance communication quality and consequently improve
system performance by reconfiguring wireless propagation environments. Inspired
by this, we propose a multi-IRS aided IoVT system that leverages IRS to enhance
communication quality, thereby reducing power consumption while satisfying
delay requirements. To fully leverage the benefits of IRS, we jointly optimize
power control for IoVT devices and passive beamforming for IRS to minimize
long-term total power consumption under delay constraints. To solve this
problem, we first utilize Lyapunov optimization to decouple the long-term
optimization problem into each time slot. Subsequently, an alternating
optimization algorithm employing optimal solution-seeking and fractional
programming is proposed to effectively solve the optimization problems at each
time slot. Simulation results demonstrate that the proposed algorithm
significantly outperforms benchmark algorithms in terms of long-term total
power consumption. Moreover, a trade-off between the number of IRS elements and
system performance is also proved