Battery-powered IoT devices face challenges like cost, maintenance, and environmental sustainability, prompting the emergence of batteryless energy-harvesting systems that harness ambient sources. However, their intermittent behavior can disrupt program execution and cause data loss, leading to unpredictable outcomes. Despite exhaustive studies employing conventional checkpoint methods and intricate programming paradigms to address these pitfalls, this paper proposes an innovative systematic methodology, namely DIAC. The DIAC synthesis procedure enhances the performance and efficiency of intermittent computing systems, with a focus on maximizing forward progress and minimizing the energy overhead imposed by distinct memory arrays for backup. Then, a finite-state machine is delineated, encapsulating the core operations of an IoT node, sense, compute, transmit, and sleep states. First, we validate the robustness and functionalities of a DIAC-based design in the presence of power disruptions. DIAC is then applied to a wide range of benchmarks, including ISCAS-89, MCNS, and ITC-99. The simulation results substantiate the power-delay-product (PDP) benefits. For example, results for complex MCNC benchmarks indicate a PDP improvement of 61%, 56%, and 38% on average compared to three alternative techniques, evaluated at 45 nm.

翻译：电池驱动的物联网设备面临着成本、维护和环境可持续性等挑战，这促使了利用环境能源的无电池能量采集系统的出现。然而，这类系统的间歇性行为可能中断程序执行并导致数据丢失，从而引发不可预测的结果。尽管已有大量研究采用传统的检查点方法和复杂的编程范式来应对这些问题，本文提出了一种创新的系统性方法，即DIAC。DIAC综合流程旨在提升间歇计算系统的性能与效率，重点关注最大化正向推进速度并最小化用于备份的独立存储阵列所带来的能耗开销。随后，本文描述了一个有限状态机，该状态机封装了物联网节点的核心运行状态，即感知、计算、传输和休眠。首先，我们验证了基于DIAC的设计在电源中断情况下的鲁棒性和功能性。然后，将DIAC应用于广泛的基准测试集，包括ISCAS-89、MCNS和ITC-99。仿真结果证实了其功耗-延迟积（PDP）优势。例如，在45纳米工艺下，针对复杂MCNC基准测试，与三种替代技术相比，DIAC平均实现了61%、56%和38%的PDP改进。