Cyber-physical systems often include sensor devices in their structure. These devices may require firmware updates once deployed and these updates must be energy efficient for battery powered, physically inaccessible sensors. The problem of energy saving reprogramming can be split to four tasks– making old and new firmware versions more similar, generating small delta files using differencing algorithms, propagating delta files and applying updates at the end devices. This paper describes existing approaches dealing with this problem, analyzes their power consumption and introduces new optimizations for differencing algorithms. A new approach is presented that requires no external flash memory, device reboot or complex update agent at the sensor device.

Low-power embedded devices are widely used in sensor networks, monitoring systems, and industrial applications. These devices typically rely on internal flash memory, where storage is constrained by bootloaders, communication stacks, and other software. Adding external memory increases cost and energy consumption, making efficient memory utilization essential. This article presents key design concepts for developing an efficient, lightweight, and reliable embedded filesystem. It introduces an improved version of the configurable flash filesystem (CFFS), designed to maximize memory utilization, minimize flash wear, and support portability across hardware platforms and operating systems. Reliability mechanisms integrated into CFFS are also discussed. We compare CFFS with widely used low-power embedded filesystems—LittleFS, SPIFFS, and FDS—highlighting its advantages in memory efficiency and reduced flash memory wear. Experimental results demonstrate that CFFS achieves up to 99% memory utilization while significantly reducing erase operations.

The embedded low-power devices are very important part of any smart system. With the large amounts of sensors and actuators used, it is a good practice to implement remote reprogramming capabilities into the firmwares of these devices. This paper presents a new configurable reprogramming methodology that can be applied to various platforms. It is built on the best reprogramming practices while giving developers more control over firmware outline, updated functions and modules. It also refers energy efficiency, as the data shared over the network and memory operations on the devices are minimal. The multiplatform capabilities make this scheme ideal for smart systems.