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This paper proposes content-based wake-up control for top-k query in wireless sensor networks, where the sink attempts to collect information on top-k nodes or top-k values from sensor nodes employing wake-up receivers. The wakeup procedure is designed with a goal of waking up only the subset of nodes which have the relevant data observations to construct the desired top-k set. This prevents the sensors with less relevant data from waking up and wasting energy. Assuming p-persistent carrier sense multiple access (CSMA) as the medium access protocol, the proposed scheme is analyzed theoretically in terms of data collection delay and total energy consumption. The performance of the proposed wake-up control is examined over a wide variety of parameters with practical considerations and compared to the conventional identity (ID)-based wakeup (IDWu) such as unicast wake-up (UCWu) and broadcast wake-up (BCWu). The obtained numerical results show that the proposed CDCoWu outperforms IDWu in terms of data collection delay and energy consumption for the maximum ratio of topdata to number of sensor nodes ranging from 0.1 to 0.5 when the number of sensor nodes is equal to or more than 20.

Information freshness and high energy-efficiency are key requirements for sensor nodes serving Industrial Internet of Things (IIoT) applications, where a sink node must collect informative data before a deadline to control an external element. Pull-based communication is an interesting approach for optimizing information freshness and saving wasteful energy. To this end, we apply Content-based Wake-up (CoWu), in which the sink can activate a subset of nodes observing informative data at the time that wake-up signal is received. In this case, the timing of the wake-up signal plays an important role: early transmission leads to high reliability in data collection, but the received data may become obsolete by the deadline, while later transmission ensures a higher timeliness of the sensed data, but some nodes might not manage to communicate their data before the deadline. This letter investigates the timing for data collection using CoWu and characterizes the gain of CoWu. The obtained numerical results show that CoWu improves accuracy, while reducing energy consumption by about 75% with respect to round-robin scheduling.

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