Coded Computation for Internet of Things

The Internet of Things (IoT) is emerging as a new Internet paradigm connecting an exponentially increasing number of smart IoT devices and sensors. IoT applications include smart cities, transportation systems, mobile healthcare and smart grid, to name a few. Unlocking the full power of IoT requires analyzing and processing this data through computationally intensive algorithms at unprecedented high rates, with stringent reliability, security and latency constraints. In many scenarios, these algorithms cannot be run locally on the computationally-limited IoT-devices and are rather outsourced to the cloud. This leaves the IoT network, and the applications it is supporting, at the complete mercy of an adversary, or a natural disaster that can jeopardize the IoT, or completely disconnect it from its “brain” (the cloud), with potentially catastrophic consequences.

As a solution to mitigate the computational bottleneck in IoT, we focus on the scenario that IoT-devices help each other in their computations in a distributed fashion, with possible help from the cloud, if available. Our approach is based on the new theory of coded computations, which studies the design of erasure and error-correcting codes to improve the performance of distributed algorithms through “smart” data redundancy. We have developed distributed, adaptive, and secure coded computation algorithms for IoT devices and deployed these algorithms on real IoT devices to demonstrate the efficiency of the approach. This work has been supported by Army Research Lab (ARL) #W911NF-1820181 and #W911NF-1710032, National Science Foundation (NSF) #CNS-1801708, Army Research Office (ARO) #W911NF1810211 grants.