Verifying Outsourced Computation in an Edge Computing Marketplace

TL;DR

This paper introduces a lightweight, efficient scheme for verifying the integrity of outsourced computations in edge computing marketplaces, ensuring trustworthiness without significant performance overhead.

Contribution

It presents a novel verification scheme that is resistant to dishonest participants and compatible with real-time neural network tasks in edge environments.

Findings

Less than 1ms computational overhead on devices

Negligible network bandwidth overhead (up to 84 bytes/frame)

Resists a wide range of protocol violations

Abstract

An edge computing marketplace could enable IoT devices (Outsourcers) to outsource computation to any participating node (Contractors) in their proximity. In return, these nodes receive a reward for providing computation resources. In this work, we propose a scheme that verifies the integrity of arbitrary deterministic functions and is resistant to both dishonest Outsourcers and Contractors who try to maximize their expected payoff. We tested our verification scheme with state-of-the-art pre-trained Convolutional Neural Network models designed for object detection. On all devices, our verification scheme causes less than 1ms computational overhead and a negligible network bandwidth overhead of at most 84 bytes per frame. Our implementation can also perform our verification scheme's tasks parallel to the object detection to eliminate any latency overhead. Compared to other proposed verification schemes, our scheme resists a comprehensive set of protocol violations without sacrificing performance.