Computing-aided update for information freshness in the internet of things

Age of information (AoI), a notion that measures the information freshness, is an important performance metric for real-time applications in Internet of Things (IoT). With the surge of computing resources at the IoT devices, it is possible to preprocess the information packets that contain the status update before sending them to the destination so as to lighten the transmission burden. However, the additional time and energy expenditure induced by computing also make the optimal updating a non-trivial problem. In this paper, we consider a real-time IoT monitoring system, where the computing-aided IoT device is capable of preprocessing the status update. A joint preprocessing and transmission policy is devised to minimize the average AoI at the destination and the energy consumption at the IoT device. Due to the difference in the processing rate and the transmission rate and the difference in the idle duration and the active duration, this problem is formulated as an average cost semi-Markov decision process (SMDP) and then transformed into a discrete-time Markov decision process (MDP). We show that the optimal policy is of threshold type with respect to the AoI. Equipped with this, a low-complexity relative policy iteration algorithm is proposed to obtain the optimal policy of the SMDP. Finally, simulation results demonstrate the optimal policy structure in different cases and show that the proposed policy outperforms two baseline policies.