Battery-less technology evolved to replace battery usage in space, deep mines, and other environments to reduce cost and pollution. Non-volatile memory (NVM) based processors were explored for saving the system state during a power failure. Such devices have a small SRAM and large non-volatile memory. To make the system energy efficient, we need to use SRAM efficiently. So we must select some portions of the application and map them to either SRAM or FRAM. This paper proposes an ILP-based memory mapping technique for intermittently powered IoT devices. Our proposed technique gives an optimal mapping choice that reduces the system’s Energy-Delay Product (EDP). We validated our system using TI-based MSP430FR6989 and MSP430F5529 development boards. Our proposed memory configuration consumes 38.10% less EDP than the baseline configuration and 9.30% less EDP than the existing work under stable power. Our proposed configuration achieves 20.15% less EDP than the baseline configuration and 26.87% less EDP than the existing work under unstable power. This work supports intermittent computing and works efficiently during frequent power failures.

无电池技术的发展取代了太空、深矿井和其他环境中的电池使用，以降低成本和污染。人们探索了基于非易失性存储器（NVM）的处理器来在电源故障期间保存系统状态。此类设备具有小型 SRAM 和大型非易失性存储器。为了使系统节能，我们需要有效地使用SRAM。因此，我们必须选择应用程序的某些部分并将它们映射到 SRAM 或 FRAM。本文提出了一种用于间歇供电物联网设备的基于 ILP 的内存映射技术。我们提出的技术提供了一个最佳的映射选择，可以减少系统的能量延迟积（EDP）。我们使用基于 TI 的 MSP430FR6989 和 MSP430F5529 开发板验证了我们的系统。我们建议的内存配置比基准配置消耗的 EDP 减少 38.10%，比稳定功率下现有工作的 EDP 减少 9.30%。我们提出的配置比基准配置减少了 20.15% 的 EDP，比不稳定功率下的现有工作减少了 26.87% 的 EDP。这项工作支持间歇性计算，并在频繁断电时高效工作。