Evaluation of Connectivity Gaps Impact on TCP Transmissions in Maritime Communications

Michał Hoeft; Józef Woźniak

doi:10.1007/978-3-319-59767-6_8

Evaluation of Connectivity Gaps Impact on TCP Transmissions in Maritime Communications

Abstract

Many organizations and research working groups, including among others IEEE, ITU, ETSI and IMO are currently working towards improvements in communication of different types of vehicles (cars, trains, planes and vessels) and upgrading utilities and services offered to their crews and passengers travelling all over the world. The paper deals with selected aspects of the TCP protocol connectivity in maritime wireless networks. The authors show results of measurements performed in a real-world maritime environment consisting of on- and off-shore devices and transmission systems, partly located on vessels. Based on the collected measurements, the authors provide statistical analysis, including connectivity periods and connectivity gaps observed as a result of vessels motions. The obtained statistical results were used, in turn, in a simulation test-bed to verify efficiency of TCP connections, assuming the use of Reno algorithm, together with F-RTO enhancement (Forward RTO-Recovery), Cubic algorithm, and further adjustments proposed by the authors. The results show significant increase of the average throughput (up to 3 times) and decrease of the average download time (up to 53%), as compared to the pure Reno TCP solution. The proposed modifications seem to be especially important and attractive for highly unreliable wireless links - expected to be very common in a maritime environment.

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Category:: Conference activity
Type:: materiały konferencyjne indeksowane w Web of Science
Title of issue:: 24th International Conference on Computer Networks (CN) strony 91 - 105
Language:: English
Publication year:: 2017
Bibliographic description:: Hoeft M., Woźniak J..: Evaluation of Connectivity Gaps Impact on TCP Transmissions in Maritime Communications, W: 24th International Conference on Computer Networks (CN), 2017, ,.
DOI:: Digital Object Identifier (open in new tab) 10.1007/978-3-319-59767-6_8
Verified by:: Gdańsk University of Technology