Dfinder—An efficient differencing algorithm for incremental programming of constrained IoT devices

Abstract

Internet of Things (IoT) proliferation has been remarkably, interconnecting a vast number of devices for the support of complex data-driven applications in a variety of domains. The ability to remotely update these devices is of paramount importance, as it allows the integration of additional functionality into their firmware, the resolution of code errors, the fixing of security vulnerabilities, or even their complete re-purpose, without physically accessing them. Such Over-the-Air Programming (OTAP) solutions require the reduction of the required transmitted data during a network update, in order to minimise devices’ energy consumption due to the communication overhead.In this paper, we present the design and evaluation of Dfinder, a differencing algorithm that operates at byte-level and is able to generate small patches based on delta encoding that makes feasible the transition from a current firmware version to a new one. The algorithm runs in O(nlogn) time and O(n) space complexity, utilising enhanced suffix arrays and state-of-the-art construction techniques that enable the efficient detection of common segments between two firmware versions. Additionally, we propose an extension of the algorithm, which halves the storage requirements at the IoT device side (compared to other state-of-the-art approaches), so that devices with limited storage can also be efficiently re-programmed over-the-air. Moreover, we evaluate its performance, comparing it with other differencing algorithms, and by integrating it in a complete IoT OTAP system.