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The Internet of things (IoT) comprises of wireless sensors and actuatorsconnected via access points to the Internet. Often, the sensing devices areremotely deployed with limited battery power and are equipped with energyharvesting equipment. These devices transmit real-time data to the base station(BS), which is used in applications such as anomaly detection. Under sufficientpower availability, wireless transmissions from sensors can be scheduled atregular time intervals to maintain real-time data acquisition. However, oncethe battery is significantly depleted, the devices enter into power saving modeand need to be more selective in transmitting information to the BS.Transmitting a particular piece of sensed data consumes power while discardingit may result in loss of utility at the BS. The goal is to design an optimaldynamic policy which enables the device to decide whether to transmit or todiscard a piece of sensing data particularly under the power saving mode. Thiswill enable the sensor to prolong its operation while causing minimum loss ofutility to the application. We develop an analytical framework to capture theutility of the IoT sensor transmissions and leverage dynamic programming basedapproach to derive an optimal real-time transmission policy that is based onthe statistics of information arrival, the likelihood of harvested energy, anddesigned lifetime of the sensors. Numerical results show that if the statisticsof future data valuation are accurately predicted, there is a significantincrease in utility obtained at the BS as well as the battery lifetime.

Real-Time Transmission Mechanism Design for Wireless IoT Sensors with Energy Harvesting under Power Saving Mode