Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

IoTSim-Osmosis: A framework for modeling and simulating IoT applications over an edge-cloud continuum

Alwasel, Khaled, Jha, Devki Nandan, Habeeb, Fawzy, Demirbaga, Umit, Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646, Baker, Thar, Dustdar, Scharam, Villari, Massimo, James, Philip, Solaiman, Ellis and Ranjan, Rajiv 2021. IoTSim-Osmosis: A framework for modeling and simulating IoT applications over an edge-cloud continuum. Journal of Systems Architecture 116 , 101956. 10.1016/j.sysarc.2020.101956

[thumbnail of IoTSim_Osmosis.pdf]
Preview
PDF - Accepted Post-Print Version
Download (780kB) | Preview

Abstract

The osmotic computing paradigm sets out the principles and algorithms for simplifying the deployment of Internet of Things (IoT) applications in integrated edge-cloud environments. Various existing simulation frameworks can be used to support integration of cloud and edge computing environments. However, none of these can directly support an osmotic computing environment due to the complexity of IoT applications and heterogeneity of integrated edge-cloud environments. Osmotic computing suggests the migration of workload to/from a cloud data center to edge devices, based on performance and security trigger events. We propose ‘IoTSim-Osmosis– a simulation framework to support the testing and validation of osmotic computing applications. In particular, our detailed related work analysis demonstrates that IoTSim-Osmosis is the first simulation framework to enable unified modeling and simulation of complex IoT applications over heterogeneous edge-cloud environments. IoTSim-Osmosis is demonstrated using an electricity management and billing application case study, for benchmarking various run-time QoS parameters, such as IoT battery use, execution time, network transmission time and consumed energy.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Elsevier
ISSN: 1383-7621
Date of First Compliant Deposit: 1 December 2020
Date of Acceptance: 23 November 2020
Last Modified: 07 Nov 2023 04:20
URI: https://orca.cardiff.ac.uk/id/eprint/136718

Citation Data

Cited 16 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics