Performance Improvements in Cooperative Downloading: Encoding and Strategies for Heterogeneous Vehicular Networks

Niebisch M, Pfaller D, German R, Djanatliev A (2022)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2022

Pages Range: 1-9

Event location: Edmonton CA

DOI: 10.1109/LCN53696.2022.9843364

Abstract

With the vast increase in software and digital services in the vehicular domain, communication networks play an increasingly important role. While some applications rely on fast data transfers, other tasks can be offloaded and delayed. For those, cooperative downloading schemes have been proposed, which utilize opportunistic communication, heterogeneous networks, and extended deadlines in a best effort approach. The efficiency of such communication depends on the chosen protocol and strategies, which impact the performance. We, therefore, introduce a novel hybrid encoding scheme for the encoding of relevant data. Additionally, we study the impact of reacting to data requests and initial distribution of data. We introduce a protocol logic for cooperative downloading and evaluate the overall downloading efficiency in simulation. A comparison between strategies reveals improvements of up to 31.8% in downloading progress and a time reduction averaging 46.4% for the best set of parameters, while also reducing the channel load significantly.

Authors with CRIS profile

Michael Niebisch Computer Science 7 (Computer Networks and Communication Systems) Reinhard German Computer Science 7 (Computer Networks and Communication Systems) Anatoli Djanatliev Computer Science 7 (Computer Networks and Communication Systems)

Related research project(s)

Heterogeneous vehicle networks for data transmission in the field April 1, 2020 - Sept. 30, 2023

Involved external institutions

Audi AG DE Germany (DE)

How to cite

APA:

Niebisch, M., Pfaller, D., German, R., & Djanatliev, A. (2022). Performance Improvements in Cooperative Downloading: Encoding and Strategies for Heterogeneous Vehicular Networks. In Proceedings of the IEEE 47th Conference on Local Computer Networks (LCN) (pp. 1-9). Edmonton, CA.

MLA:

Niebisch, Michael, et al. "Performance Improvements in Cooperative Downloading: Encoding and Strategies for Heterogeneous Vehicular Networks." Proceedings of the IEEE 47th Conference on Local Computer Networks (LCN), Edmonton 2022. 1-9.

BibTeX: Download