Research Article
DCAR: DTN Congestion Avoidance Routing Algorithm Based on
Tokens in an Urban Environment
Hezhe Wang, Hongwu Lv, Huiqiang Wang, and Guangsheng Feng
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
Correspondence should be addressed to Hongwu Lv; lvhongwu@hrbeu.edu.cn
Received 15 November 2016; Revised 10 April 2017; Accepted 20 April 2017; Published 30 May 2017
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ademic Editor: Jaime Lloret
Copyright © Hezhe Wang et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
When a delay/disruption tolerant network (DTN) is applied in an urban scenario, the network is mainly composed of mobile devices
carried by pedestrians, cars, and other vehicles, and the node’s movement trajectory is closely related to its social relationships and
regular life; thus, most existing DTN routing algorithms cannot show ecient network performance in urban scenarios. In this
paper, we propose a routing algorithm, called DCRA, which divides the urban map into grids; xed sink stations are established
in specic grids such that the communication range of each xed sink station can cover a specic number of grids; these grids
are dened as a cluster and allocated a number of tokens in each cluster; the tokens in the cluster are controlled by the xed sink
station. A node will transmit messages to a relay node that has a larger remaining buer size and encounters xed sink stations or
the destination node more frequently aer it obtains a message transmit token. Simulation experiments are carried out to verify
the performance of the DCAR under an urban scenario, and results show that the DCAR algorithm is superior to existing routing
algorithms in terms of delivery ratio, average delay, and network overhead.
1. Introduction
e concept of DTN [] originated in the interplanetary
networkandreferstothesourcenodeandthedestination
node is not necessary to maintain a complete communication
link, according to the node’s mobility to achieve a commu-
nication opportunity to complete the message transmission.
As the research continues, DTN has played a crucial role in
diverse application elds []; the main application includes
the following: wildlife tracking network [], vehicle network
[], marine sensor network [], and urban environment
network [].
DTN is characterized as highly partitioned, sparsely
connected, and intermittently connected ad hoc networks [].
In these challenging scenarios, end-to-end communication
paths between node pairs are rarely available; thus, the
process of a node transmitting a message must experience a
higher delay []. In order to overcome these network charac-
teristics, DTN adopts the method of “store-carry-forward” to
transmit messages []. at is to say, messages are temporarily
stored and carried by a node until an appropriate relay
node arises []. For this reason, the movement trajectory of
nodes is one of the crucial factors that aects the message
delivery ratio, delay, and network overhead in the process of
transmitting of messages.
However, with the continuous development of low-cost
mobile devices, mobile devices in people’s lives have been
widely used, which has resulted in many urban applications
of DTN []. However, existing routing algorithms such as
epidemic routing [], prophet routing [], and spray and
wait routing [] can show ecient network performance
in some specic scenarios. But they are not suitable for
deployment in urban scenarios. Because the streets and
other public places are xed, the node density is relatively
large, the movement trajectory of nodes depends on the
habits of human life, and the network topology is constantly
changing, real-time global network knowledge is dicult
to obtain. erefore, according to the characteristics of the
urban scenario, proposing a DTN routing algorithm that
issuitablefortheurbanscenariohasbeenoneofthekey
problems in the eld of DTN.
In this paper, we propose a DTN routing algorithm based
on tokens. e algorithm divides the urban map into grids,
and xed sink stations are established in specic grids. e
Hindawi
Journal of Sensors
Volume 2017, Article ID 6523076, 9 pages
https://doi.org/10.1155/2017/6523076