Making the Most of Sporadic Feedback: Low-Complexity Application-Layer Coding for Data Recovery in the Internet of Things

TL;DR

This paper introduces low-complexity application-layer coding schemes for IoT data recovery that leverage sporadic feedback, combining retransmissions and erasure correction to improve efficiency and resilience in delay-sensitive uplink communications.

Contribution

It presents a reduced-complexity enhancement to windowed coding, a new feedback structure for better data recovery, and a relay-based forwarding scheme for increased resilience.

Findings

Reduced coding complexity with optimal degree computation in O(1)

Improved data recovery performance over existing schemes

Enhanced resilience through relay overhearing and forwarding

Abstract

We propose application-layer coding schemes to recover lost data in delay-sensitive uplink (sensor-to-gateway) communications in the Internet of Things. Built on an approach that combines retransmissions and forward erasure correction, the proposed schemes' salient features include low computational complexity and the ability to exploit sporadic receiver feedback for efficient data recovery. Reduced complexity is achieved by keeping the number of coded transmissions as low as possible and by devising a mechanism to compute the optimal degree of a coded packet in O(1). Our major contributions are: (a) An enhancement to an existing scheme called windowed coding, whose complexity is greatly reduced and data recovery performance is improved by our proposed approach. (b) A technique that combines elements of windowed coding with a new feedback structure to further reduce the coding complexity and improve data recovery. (c) A coded forwarding scheme in which a relay node provides further resilience against packet loss by overhearing source-to-destination communications and making forwarding decisions based on overheard information.