Efficient remote software execution architecture based on dynamic address translation for internet-of-things software execution platform

In this paper, an efficient remote code execution technique is proposed to implement a storage-less sensor in the internet-of-Things (IoT) paradigm. A statically installed sensor such as an environmental activity monitor includes statically compiled embedded software and only offers its pre-defined functionality. To realize a flexible code update mechanism and to optimize the use of an IoT device in terms of utilizing its various functions, we adopt the concept of remote on-demand code execution (ROCE) to implement a storage-less sensor. Instead of using conventional on-chip flash memory for an instruction code, an instruction memory is used wherein the remote storage area based on the IoT platform is virtually mapped onto the address space of the instruction memory using a dynamic address translation technique. A pervasive Internet-connected sensor enables on-demand code execution from the cloud-side remote storage resource, without the need for a direct instruction bus. The proposed storage-less approach using the remote resource as a virtual code space may be adopted to reduce the high access current and chip area overhead of an 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. 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 realizing a storage-less sensor architecture.