# Improving In-Network Computing in IoT Through Degeneracy

## TL;DR

This paper introduces a new approach to in-network computing in IoT by leveraging degeneracy, which involves multiple network options to optimize performance metrics like delay and energy consumption.

## Contribution

It proposes a novel degeneracy concept for INC, along with an efficient algorithm to identify multiple functional alternatives, enhancing computation success rates.

## Key findings

- Significant improvement in successful computation rate
- Ability to meet delay and energy constraints
- Effective exploitation of network degeneracy

## Abstract

We present a novel way of considering in-network computing (INC), using ideas from statistical physics. We define degeneracy for INC as the multiplicity of possible options available within the network to perform the same function with a given macroscopic property (e.g. delay). We present an efficient algorithm to determine all these alternatives. Our results show that by exploiting the set of possible degenerate alternatives, we can significantly improve the successful computation rate of a symmetric function, while still being able to satisfy requirements such as delay or energy consumption.