The Promise and Challenges of Computation Deduplication and Reuse at the Network Edge

TL;DR

This paper discusses the potential and challenges of implementing computation deduplication and reuse at the network edge to improve efficiency and scalability in edge computing environments.

Contribution

It introduces a multi-layer architecture for computation deduplication at the network edge and explores open challenges and future research directions.

Findings

Deduplication can significantly reduce task completion times.

Edge computing environments face unique technical challenges for deduplication.

A multi-layer architecture enables effective computation reuse at the network edge.

Abstract

In edge computing deployments, where devices may be in close proximity to each other, these devices may offload similar computational tasks (i.e., tasks with similar input data for the same edge computing service or for services of the same nature). This results in the execution of duplicate (redundant) computation, which may become a pressing issue for future edge computing environments, since such deployments are envisioned to consist of small-scale data-centers at the edge. To tackle this issue, in this paper, we highlight the importance of paradigms for the deduplication and reuse of computation at the network edge. Such paradigms have the potential to significantly reduce the completion times for offloaded tasks, accommodating more users, devices, and tasks with the same volume of deployed edge computing resources, however, they come with their own technical challenges. Finally, we present a multi-layer architecture to enable computation deduplication and reuse at the network edge and discuss open challenges and future research directions.