Research Article
M-ODD: A Standard Protocol for Reporting MANET Related Models, Simulations, and Findings
@INPROCEEDINGS{10.1007/978-3-030-98005-4_9, author={Izabela Savić and Marshall Asch and Keefer Rourke and Fatemeh Safari and Patrick Houlding and Jeremie Fraeys de Veubeke and Jason Ernst and Daniel Gillis}, title={M-ODD: A Standard Protocol for Reporting MANET Related Models, Simulations, and Findings}, proceedings={Ad Hoc Networks and Tools for IT. 13th EAI International Conference, ADHOCNETS 2021, Virtual Event, December 6--7, 2021, and 16th EAI International Conference, TRIDENTCOM 2021, Virtual Event, November 24, 2021, Proceedings}, proceedings_a={ADHOCNETS \& TRIDENTCOM}, year={2022}, month={3}, keywords={MANET Mobile ad hoc Ad hoc networks Standardization Simulation Scientific communication Documentation protocol}, doi={10.1007/978-3-030-98005-4_9} }- Izabela Savić
Marshall Asch
Keefer Rourke
Fatemeh Safari
Patrick Houlding
Jeremie Fraeys de Veubeke
Jason Ernst
Daniel Gillis
Year: 2022
M-ODD: A Standard Protocol for Reporting MANET Related Models, Simulations, and Findings
ADHOCNETS & TRIDENTCOM
Springer
DOI: 10.1007/978-3-030-98005-4_9
Abstract
There has been a steady increase in the number of research publications in the Mobile ad hoc Network (MANET) domain over the last two decades. However, several studies have indicated that the credibility of MANET simulation publications may be in question because numerous publications lack vital information (e.g., simulation tools, variables, parameters used) and statistical rigor. This has led to issues of repeatability and reproducibility of previous work and calls into question the validity of the simulation results which are difficult or impossible to verify. To address this, we propose a modified Overview, Design Concepts, and Details (ODD) protocol, based on the work of Grimm et al., as a standard documentation protocol for MANET simulation studies. The MANET ODD (M-ODD) protocol will promote credibility within the domain of study by increasing repeatability, reproducibility, and statistical rigor.
