  Composed of spatially distributed sensors and actuators that communicate
through wireless networks, networked control systems are emerging as a
fundamental infrastructure technology in 5G and IoT technologies, including
diverse applications, such as autonomous vehicles, UAVs, and various sensing
devices. In order to increase flexibility and reduce deployment and maintenance
costs, many such applications consider battery-powered or energy-harvesting
networks, which bring additional limitations on the energy consumption of the
wireless network. Specifically, the operation of battery-powered or
energy-harvesting wireless communication networks needs to guarantee (i)
efficient communication between nodes and (ii) preservation of available
energy. Motivated by these novel requirements, in this paper, we present and
analyze a novel distributed average consensus algorithm, which (i) operates
exclusively on quantized values (in order to guarantee efficient communication
and data storage), and (ii) relies on event-driven updates (in order to reduce
energy consumption, communication bandwidth, network congestion, and/or
processor usage). We characterize the properties of the proposed algorithm and
show that its execution, on any time-invariant and strongly connected digraph,
will allow all nodes to reach, in finite time, a common consensus value that is
equal to the exact average (represented as the ratio of two quantized values).
Furthermore, we show that our algorithm allows each node to cease transmissions
once the exact average of the initial quantized values has been reached (in
order to preserve its battery energy). Then, we present upper bounds on (i) the
number of transmissions and computations each node has to perform during the
execution of the algorithm, and (ii) the memory and energy requirements of each
node in order for the algorithm to be executed.
