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 a 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 15.97% less EDP than the baseline configuration and 21.99% less EDP than the existing work under unstable power. This work supports intermittent computing and works efficiently during frequent power failures.

翻译：针对太空、深井等特殊环境中电池使用带来的成本与污染问题，无电池技术应运而生。基于非易失性存储（NVM）的处理器被探索用于在电源故障时保存系统状态。此类设备具有小容量SRAM与大容量非易失性存储器。为实现系统能效优化，需高效利用SRAM，因此必须选择应用程序的特定模块并映射至SRAM或FRAM。本文提出一种基于整数线性规划（ILP）的内存映射技术，专用于间歇供电物联网设备。该技术提供最优映射方案，可降低系统的能量延迟积（EDP）。我们使用TI MSP430FR6989与MSP430F5529开发板进行验证：在稳定供电条件下，该配置较基准方案降低38.10%的EDP，较现有方案降低9.30%的EDP；在不稳定供电条件下，较基准方案降低15.97%的EDP，较现有方案降低21.99%的EDP。本工作支持间歇性计算，可在频繁电源故障场景中高效运行。