Area efficient remote code execution platform with on-demand instruction manager for cloud-connected code executable IoT devices

An energy-area efficient cloud-connected software execution architecture in IoT sensor processor is proposed. A remotely installed sensor device such as an environmental activity monitor is commonly implemented using the conventional embedded processor only providing the fixed services, which includes statically compiled embedded software in on-chip flash memory. Instead of conventional on-chip flash memory for an instruction code area, we adopt an virtually mapped internal memory concept to realize cloud-connected software execution, in where the remote storage area via the IoT platform is indirectly mapped onto the physical address space of the instruction memory using a dynamic address translation technique. The proposed cloud-connected architecture of the system enables on-demand code execution for the instructions, which are fetched from the cloud-side remote storage area in the runtime, instead of using a directly-connected on-chip instruction bus. The proposed storage-less approach may be adopted to reduce the high access current and large chip area overhead by eliminating the on-chip code flash memory. To reduce the access current overhead in order to retrieve the requested instruction, a small-sized RAM scratch pad is adopted for retaining the hot-spot instruction code and early filled with pre-estimated instruction sector. The experimental results show that the proposed technique reduces the energy consumption and packet delay of an IoT device for executing the remote embedded software, as well as the reduced chip area by realizing a storage-less sensor architecture.