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In the era of the Internet of Things (IoT), the interest and demand for embedded systems have been explosively increasing. In particular, vehicular sensor networks are one of the fields where IoT-oriented embedded devices (also known as IoT devices) are being actively used. These IoT devices are widely deployed in and out of the vehicle to check vehicle conditions, prevent accidents, and support autonomous driving, forming a vehicular sensor network. In particular, such sensor networks mainly consist of third-party devices that operate independently of the vehicle and run on their own batteries. After all, like all battery-powered embedded devices, the IoT devices for the vehicular sensor network also suffer from limited power sources, and thus research on how to design/operate them energy-efficiently is drawing attention from both academia and industry. This paper notes that the vehicular sensor network may be the best application for ultra-low power system on-chips (ULP SoCs). The ULP SoCs are mainly designed based on ultra-low voltage operating (ULV) circuits, and this paper aims to realize the energy-optimized driving of the network by applying state of the art (SoA) low-power techniques exploiting the unique characteristics of ULV circuits to the IoT devices in the vehicular sensor network. To this end, this paper proposes an optimal task assignment algorithm that can achieve the best energy-efficient drive of the target network by fully utilizing the SoA low power techniques for ULV circuits. Along with a detailed description of the proposed algorithm, this paper demonstrates the effectiveness of the proposed method by providing an in-depth evaluation process and experimental results for the proposed algorithm.

TEI-DTA: Optimizing a Vehicular Sensor Network Operating with Ultra-Low Power System-on-Chips