# Improving In-Network Computing in IoT Through Degeneracy

@article{Dzaferagic2021ImprovingIC, title={Improving In-Network Computing in IoT Through Degeneracy}, author={Merim Dzaferagic and Neal McBride and Ryan Thomas and Irene Macaluso and Nicola Marchetti}, journal={IEEE Systems Journal}, year={2021}, volume={15}, pages={238-244} }

We present a novel way of considering in-network computing (INC), using ideas from statistical mechanics. We model the execution of a distributed computation with graphs called functional topologies, which allows us to provide a formal definition for degeneracy and redundancy in the context of INC. Degeneracy for INC is defined as the structural multiplicity of possible options available within the network to perform the same function with a given macroscopic property (e.g., delay). Two…

## 3 Citations

### Deploying Hierarchical Mesh Networks for Supporting Distributed Computing in Industrial Internet of Things

- Computer ScienceIEEE Systems Journal
- 2022

An in-network-computation-oriented node placement (INP) algorithm that decomposes the whole problem into several delay constrained relay node placement problems, and solves them sequentially, and proves that the INP algorithm ensures explicit time complexity and approximation ratio.

### Complex Systems: A Communication Networks Perspective Towards 6G

- Computer ScienceIEEE Access
- 2020

This work attempts to review basic models of complex networks from a communication networks perspective, focusing on their structural and evolutionary properties, and aims to reveal the models, that may apply when modeling the 5G and 6G mobile communication networks.

### Framework for the Identification of Rare Events via Machine Learning and IoT Networks

- Computer Science2019 16th International Symposium on Wireless Communication Systems (ISWCS)
- 2019

An industrial cyber-physical system (CPS) based on the Internet of Things (IoT) that is designed to detect rare events based on machine learning and an introduction to the solution to be developed by the FIREMAN consortium.

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