VSTP: vessel spatio-temporal contact pattern detection based on MapReduce
Liu et al. EURASIP Journal on Wireless Communications and
Networking
VSTP: vessel spatio-temporal contact pattern detection based on MapReduce
Chao Liu 0
Zhongwei Sun 0
Jing Liu
Haiguang Huang
Zhongwen Guo
Yuan Feng
0 Equal contributors Department of Information Science and Engineering, Ocean University of China , Songling Road No. 238, Qingdao 266100 , China
Due to lack of the coverage of 3G/4G network, satellite communication which costs excessively is the main approach used in ocean to provide network service. Ocean mobile delay tolerant network (OMDTN) can provide low-cost data transmission service in the network by utilizing the contact chances of moving vessels. Spatio-temporal contact pattern is one of the key metrics to improve the efficiency of the routing algorithm in OMDTN. Some researches have been carried out on human handheld device and vehicular ad hoc networks (VANETs). However, the vessel's trajectory data is distributed and stored disorderly, which makes traditional contact pattern detection algorithm cannot be directly applied. In this paper, we design a parallel algorithm named VSTP based on MapReduce to detect spatio-temporal contact pattern from trajectories of over 2000 vessels. Studying the vessels' trajectories and the contact records, we observe that the vessels' contact pattern including inter-contact time distribution and contact times distribution is in sharp contrast to the study on human handheld device and VANETs. Our results can provide the guidelines for the design of data routing protocols on OMDTN and give a new solution to overcome the difficulty of ocean network coverage.
Contact pattern; Empirical data analysis; Delay tolerant network; MapReduce; Sensor network
1 Introduction
Ocean network communication is one of the most
important research topics in the field of ocean information
technology in the future. It plays an important role in vessel
communication, ocean observation and military security.
Currently, the main communication means of ocean
vessels include HF and VHF radio communication [
1–3
],
onboard laser communication [
4
], cellular mobile
network [
5
], and maritime satellite communication [
6
]. HF
and VHF radio communication are vulnerable to
atmospheric interference, thus having blind coverage areas and
poor confidentiality. Its communication requires a
predetermined frequency which makes it impossible to provide
network service in large-scale ocean area. At present, it
is only suitable for the internal communication among
fleet of vessels and the directional communication to the
seashore base station. Laser communication has many
advantages, such as high bandwidth and confidentiality,
but it is not suitable for providing general oceanic network
communication services due to the targeting problem.
Because of high cost of setting up the ocean base station,
the cellular network cannot provide the network
coverage for medium or long distance of sea area and frequent
network data transmission will lead to high
communication cost. Currently, maritime satellite communication is
a good way of ocean network communication. However,
the high price of terminals and communication expenses
prohibit it from large-scale application.
In short, existing ocean communication schemes are
restricted by the limitation of the communication mode
and high infrastructure deployment cost and
communication expenses; thus, they cannot provide low-cost
large-scale oceanic network services. Hence, ocean
network communication is a problem that should be solved
quickly. The ocean mobile delay tolerant network can
provide mutual communication opportunity through the
movement of the vessels in the network and provide
lowcost data transmission service in the whole network
without any infrastructure. In the process of data routing in the
mobile delay tolerant network, the optimal routing path
can be computed efficiently if the obtained information
base (such as the contact pattern, hot spots area among
nodes, and the movement pattern model) is very
comprehensive. Therefore, it is the key problem in the research
of ocean network communication to explore the rules of
vessel movement and contact pattern from the large-scale
moving trajectory data of vessels.
However, there are many unique characteristics of vessel
trajectory data. Firstly, the vessel moving trajectory data is
sparse. Due to the pressure of the base stations, capacity
constraints of satellite communication, equipment’s
stability and the vessel density in the sea and so on, under
normal circumstances, the timestamp interval of vessel
trajectory data is different and it is from 3 to 20 min in
general. This results in the characteristic of sparseness in
the vessel trajectory data. The missing data is short-time
missing data. In addition, because some fishermen lack
the safety operation awareness and do not open the VMS
(Vessel Monitoring System), there is long-term missing
data in part of the vessels’ trajectory.
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