Paper Info
Title
Link quality evaluation of a wireless sensor network in metal marine environments
Abstract
Wireless sensor networks (WSN) are finding increasing use in all-metal marine environments such as ships, oil and gas rigs, freight container terminals, and marine energy platforms. However, wireless propagation in an all-metal environment with ducting and sealed doors between compartments is difficult to model, and the operating machinery further complicates wireless network planning. This makes it necessary to characterize the performance of the physical wireless links in the actual operating environments. However, little has been reported in the literature on methodologies for measuring the full range of physical link quality indicators. In this paper, we present a methodology for doing this that we have verified by the deployment of a 2.4 GHz network of 18 nodes in three different all-metal scenarios: a cluster of freight containers, a full-sized shore-based working ship’s engine room training facility, and an operational ship’s engine room. The output variables included the key link quality indicators of packet delivery ratio (PDR), RSSI, and LQI for every possible link, as well as the performance of every node. We believe that this is the first time that this full range of physical link quality indicators has been measured in this type of application environment. We found that in all three scenarios the network performed with over 90% PDR average. However, as the scenarios become more complex, the communications become more unpredictable, yielding a wider transition zone, indicating that although a WSN could operate in these scenarios under different conditions, a pre-deployment practical study is essential for each new scenario.
Year
DOI
Venue
2019
10.1007/s11276-018-1726-z
Wireless Networks
Keywords
Field
DocType
Wireless sensor networks, Link quality, Marine metal environments
Wireless network,Software deployment,Wireless,Computer science,Network packet,Computer network,Marine energy,Engine room,Wireless sensor network,Doors
Journal
Volume
Issue
ISSN
25
3
1572-8196
Citations 
PageRank 
References 
0
0.34
18
Authors
2
Name
Order
Citations
PageRank
David Rojas1121.95
John Barrett201.69