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8/9/2019 WSN in Military
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Paper lD# 900610 PDF
WIRELESS SENSOR NETWORK DESIGN FOR TACTICAL MILITARY APPLICATIONS
: REMOTE LARGE-SCALE ENVIRONMENTS
Sang Hyuk Lee, Soobin Lee, Heecheol Song, and Hwang Soo Lee
Department
of
Electrical Engineering, KAIST
Daejeon, South Korea
{Ish6456, caesI, heecheol.song}@mcl.kaist.ac.kr, hwanglee@ee.kaist.ac.kr
ABSTRACT
Wireless sensor networks
WSNs)
can be used by the
military for a number ofpurposes such as monitoring or
tracking the enemies and force protection. Unlike
commercial WSNs, a tactical military sensor network has
different priority requirements for military usage.
Especially in the remote large-scale network, topology,
self-configuration, network connectivity, maintenance, and
energy consumption are the challenges. In this paper, we
present an overview of application scenarios in remote
large-scale WSNsfocusing on theprimary requirementsfor
tactical environments. We propose a sensor network
architecture based on the cluster-tree based multi-hop
model with optimized cluster head election and the
corresponding node design method to meet the tactical
requirements. With the proposed WSN architecture, one
can easily design the sensor network for military usage in
remote large scale environments.
Index Terms
-
Military sensor networks, Architecture,
Design, Self-organization, Cluster head election.
I. INTRODUCTION
In the information age, tactical military sensor network
systems have been researched for the Network Centric
Warfare (NCW) in many military forces around the world.
As NCW is a highly orchestrated dynamic autonomous
digital battlefield communications command/control and
situational awareness network, commander can see, decide
and shoot the target in advance due to preoccupying the
highly advanced situation awareness. The US Army's
Future Combat System also uses the Unattended Ground
Sensor network to detect, locate and identify enemy targets
with lighter armor protection on the battlefield. These
sensors can be deployed statically by hand or randomly in
remote area by Unmanned Aerial Vehicles (UAVs) and
artillery [1]-[5].
Despite the advantages of the sensor network in military
applications, Commercial-off-the-shelf sensor network
systems cannot offer the solution due to the tactical
constraints and requirements, especially in remote large
scale environments. There have been large amount
of
research on tactical military wireless sensor networks
(WSNs) and significant progress has been achieved .
Nevertheless, most of the developed and designed military
sensor models are not operated in the remote large-scale
with thousands of nodes but in the static deployment
environment with several nodes.
In this paper, we propose a design approach for the
military WSN in remote large-scale environments based on
the military requirements. Since WSNs in remote large
scale environments cannot be managed manually, after
being distributed, sensor nodes have to organize and heal
themselves in an energy-efficient manner while
guaranteeing the network connectivity, low probability of
intercept (LPI) and low probability of detection (LPD) for
security [6].
The remaining sections of this paper are presented as
follows; Section II introduces the tactical military WSN
applications. Section III
presents the considerations and
requirements
of the tactical WSN. Section N discusses the
network architecture and node design of the tactical WSN.
Finally, we conclude in Section V.
II APPLICATIONS
There are several possible scenarios for tactical military
applications such as:
WSNsfor friendly forces protection: In the area
of
active
engagement, it is essential for friendly forces to prevent
their base, armory, and communication center from being
attacked [7]. To realize its efficient defense, sensor node
models and architectures have been researched and
developed successively. These developed models have
been also used in Iraq war.
lof7
978-1-4244-5239-2/09/$26.00 2009 IEEE
8/9/2019 WSN in Military
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Paper ID# 900610 PDF
C>
'
I
'
'
Figure 1.The operation concept
of
tactical sensor network in remote
large-scale environment
Soldier-worn sensor system: Advanced Soldier Sensor
Information System and Technology (ASSIST) program
has been performed in DARPA [8]. The objective of
ASSIST is to provide a report or debrief that describes any
event encountered during the mission and to use reported
information for the future operations and missions.
WSNs in remote large-scale areas:
In this application, as
mentioned in section I thousands of sensor nodes are
deployed in enemy forces areas and organize by themselves.
Sensor nodes also maintain their connectivity
autonomously . Since these sensor nodes cannot be
recharged, the energy efficiency of the sensor nodes
becomes an important issue. Unlike the previous scenarios ,
this application has a lot of constraints and considerations
for usage in military environments.
Fig. 1 shows the last scenario
of
tactical military sensor
network. The following is the operational procedures:
Requesting distribution of tactical sensors in a specific
area.
Thousands of sensors are deployed by UAV drop or
artillery methods
During an initialization period, sensor nodes organize
the network by themselves.
Sensor nodes report information to a sink node or
UAVs/UGVs
In this application, sensor nodes identify forces using
RFID or key-exchange and track the enemy forces using
variable sensors.
III REQUIREMENTS
Design goal for military WSNs depends on the application.
In this section, we outline several design considerations and
requirements which influence the overall design of the
tactical military WSN in remote large-scale areas. These
requirements have the realistic assumptions as the
following:
Unattended wireless sensor networks.
Fixed sensor nodes after random distribution.
Sensor nodes with same capabilities such as
transmission range and energy except the sink node
which has powerful energy and pre-scheduled location.
A. Scalable Self-Organization
Since thousands of sensor nodes in remote areas cannot
be managed by military personnel, they must identify
neighbors within communication range and configure the
network autonomously. In addition, the network should
cope with self-healing and self-reconfiguring. Several
papers proposed seIf-organizati
onlse
If-configuration
algorithms for the WSNs [9]-[12]. However, the proposed
algorithms are on the assumption that the sensor nodes
have a long transmission range which is possible to reach
from all nodes to the sink. This assumption is not suitable
for the design
of
scalable networks in large-scale areas
since the distance between a sink node and sensor nodes
becomes longer . We should design a suitable self
organization algorithm considering network scalability.
B. Guarantee ofNetwork Connectivity
While energy efficiency is the most important in
commercial sensor networks, network connectivity
becomes more significant than energy problems in tactical
WSNs. There can be missed or delayed mission critical
information due to only a few isolated sensor nodes in the
network, and this may result in a wrong decision on the
battlefield. We should consider the self-organization
algorithm guaranteeing network connectivity.
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(c) Single-hop based on clustering (d) Multi-hop based on clustering
Figure 3. Tactical military sensor network structure
In this section, we propose a design approach for military
WSN in remote large-scale environments based on the
requirements mentioned in section III. First, we find the
suitable network architecture and design the sensor model
at each layer's view-point.
IV DESIGN
F. Security
Military WSNs, especially distributed in the enemy
s
area,
should consider security factors. Unlike the commercial
WSNs, all possible design techniques for LPD, LPl and
Anti-jamming should be considered at each layer of sensor
node [7].
D. Information Flow
There are 3 types
of
information flow in WSNs. The first
type is one-way communication from sensors to the sink or
the gateway. The second type is two-way information flow
which can manage sensor nodes by sending control
message from the sink (C2: Command and Controller) to
sensor nodes. The last type is multi-way information flow
which can be applied to multi-media applications [14]. In
our design, we only consider the first type
of
information
flow, since it is sufficient to gather the mission critical
information with low cost.
E
QoS
Data type can be classified QoS parameters in military
WSNs as following:
Emergency Data: This mission critical information
should be guaranteed to deliver to the sink (C2) with
both low delay and high reliability.
Monitoring and Tracking Data: Since sensor nodes
cannot distinguish the target whether enemy or others
such as animal, military WSNs should monitor and
track all targets with guarantee of low delay until the
target becomes identified.
Periodic Simple Data:
A condition
of
sensor nodes
such as remaining energy could be a simple data type.
As this periodic data is not critical to operate the
mission, the high reliability is sufficient regardless of
real-time delivery .
A. Network Architecture Design
: Cluue rHead
.:
o
Cluster Member
o
Sink
o 0 0
(b) Multi-hop based on flat
i t
Sink
(a) Single-hop based on flat
o Level i l
0 0
O . 0 0 .....
>
0
_______
i
A) [ B
O
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40
Figure 6. Orphan node ratio with 20 percentage of cluster head
(2) Cluster-Tree Creation
After being distributed, sensor nodes should self-organize
cluster tree topology as illustrated in Fig. 3. First, the sink
or cluster head sends beacon messages with (i) level to
neighbor nodes within its transmission range. After
receiving beacons, the node sends association request
messages to the sink or cluster head to join the network.
After receiving all association request and confirm
messages, the cluster head election algorithm is performed
by individual member nodes or by cluster head. In Fig. 3,
the sensor node A or B which was elected as a cluster head
sends a beacon message to neighbor nodes within its
(1) Topology
Ibriq (15] and Younis (16] grouped all WSN topologies
into 4 types of models as shown in Fig. 2. Among these
types, we consider the multi-hop based clustering model as
the ideal network topology meeting the requirements for
the following reasons:
Scalability: In the single-hop models (Fig. 2 - a, c), all
sensor nodes transmit their data to the sink node
directly. These architectures are infeasible in large
scale areas because transmission becomes expensive in
terms
of
energy consumption, and in the worst case, the
sink node may be unreachable. Also, implementation
of LPD/LPI may be impossible due to long range
transmission. Consequently, multi-hop models (Fig. 2
b, d) are suitable in large-scale environments in respect
of scalability.
Overhead and energy consumption: In multi-hop
models, we can consider the flat model (Fig. 2 - b) and
the cluster-based model (Fig. 2 - d). Since all nodes
should share some information such as routing table in
the flat based model, overhead may be increased
compared to the cluster-based model. Additionally, in
the multi-hop based on clustering model, sensor nodes
can maintain low energy consumption because
particular cluster heads aggregate data and transmit to
the sink node.
Resource management:
In the flat model, resources are
shared and managed by individual nodes. As a result,
resources usage may not be efficient. In the cluster
based model, we can apply hybrid media access control
mechanisms to cluster heads and members differently.
We can allocate orthogonal resources to clusters
reducing collision between clusters and reuse the
resources cluster by cluster (17], [18].
As a result, the multi-hop based on clustering model is
appropriate as the military WSN in large-scale areas.
30
40
25
0
30
15
ROUND(S)
20
10
Cluster Head Probaility( )
'.
10
o ...
Centralized ClusterHead Election
Localized Cluster Head Election
__ Cluster Head Rallo wtth Cenllallzed Election
Orphan Node Ratio with Ctmtraliled Election
.......Cluster Head Ratio WIth Localized sieenen
, - . OrphanNodeRano wtlh Localized Election
f duste
r head receive the association request.
Cneck. IhE
El:
O/NT;
JV hf d =.Q l rr
;
I f
N
he J > I ) {
NCH- j1oor N haJJ ;
Selectthe
NCH
number of nodes in thehighest EL;
Register the seleeled nodes to cluster
head
;
RE gistcr the other nodes 10 members
Else {
Seleet the 1 highest node as a duster head ;
Regis/c r the selected nodes to cluster
head
;
Regis/er till othernodes to lIIelllllel s ;
30
n - Parent probability.
EI. - Residual Energy Level.
':T
=
The nnmber ofnodessendingassociation reque
sllo
a cluster head in each cluster.
' :CH - The number of candidate cluster heads
~
.Q
a;
0::
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Z
c
:
10
3
100
8/9/2019 WSN in Military
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Paper ID# 900610 PDP
transmission range with the increased (i+1) level like the
sink's role, and the other nodes act as members of the sink.
In case
of
the node C which received more than two
beacons from different cluster heads, the lower level and
higher received strength signal indicator could be a
criterion to select its cluster head for making a shortest path
from a sensor node to the sink and saving energy as well.
Cluster head election algorithm in cluster tree was
proposed in TEEN [9], HEED [11], and the modified
LEACH [19] in which cluster head election is performed
by each member node individually based on the pre
defined probability. However, this localized cluster head
election leads to lower network connectivity with dead
zone and forms the asymmetric tree topology in which
cluster heads get congregated to the particular areas
of
network. Instead of the localized election, we design the
optimized cluster head election algorithm. This algorithm,
as seen in Fig. 4, is performed by cluster heads of each
level to improve the network connectivity and reduce
orphan nodes. In the optimized election, the cluster head
check the residual energy level (EL) of
sensor nodes on
receiving the association request from the non-joined nodes.
If N_head is equal or bigger than 1, cluster head elects the
next level's cluster heads based on the EL and probability.
If N _ head is lower than 1, cluster head select one, the
biggest EL node, as a cluster head of next level. It means
that we try to elect at least one cluster head to reduce the
dead zone.
Fig. 5 and Fig. 6 represent the results of the local and
central cluster head election algorithm with 500 simulation
times. 1000 sensor nodes are randomly distributed in
1DOOm x 1DOOm and each node has 100m transmission
range. In Fig. 5, orphan node ratio based on the optimized
election has lower than that of the localized election until
the cluster head probability reaches to 30 %. The ratio of
the elected cluster head in the distributed election shows
that it has low ratio
of
cluster head as compared with the
cluster head probability up to 25%. On the other hand, the
optimized one has the linear rising result in proportion to
the cluster head ratio. In Fig. 6, the optimized election has
high network connectivity with near zero orphan nodes. In
addition, we can expect that the optimized election
algorithm lead to low energy consumption because most of
sensor nodes do not need to consume the energy for
maintenance of orphan node. However, in the localized
election, the average ratio of orphan node is 8% and the
ratio of orphan node in each ROUND is inconsistent. As a
result, the proposed optimized election can guarantees
network connectivity.
(3) Maintenance
After forming the network, the WSN need the
maintenance operation since the dead zones or orphan
nodes could take place in the WSN. We propose solutions
with prediction and recovery.
In the case of the former, the sensor network changes
cluster heads periodically. LEACH changes cluster head in
every ROUND [10]. We also apply a ROUND concept to
our model changing cluster heads in every ROUND for
high network life-time as shown Fig. 7. Round Order (RO)
is bounded by every network set-up phase in which cluster
heads are changed. Each RO has several Beacon Orders
(BOs) in which CSMA and contention free period are
included.
In the latter case, a network must cover the un-predictable
conditions. For example, if node does not receive any
beacon message or
if
cluster head get disappeared due to
exhaustion of
energy or enemy's attack, network might
have a critical dead zone. As a result, the sensing data
cannot be delivered to the sink. In our design, after cluster
tree creation, a network enters the maintenance procedure
for the orphan node such as a node D in Fig. 3. During the
recovery procedure, an orphan node D sends the
association message to rejoin with the nearest candidate
cluster head registered at initial cluster tree creation time. If
there is no candidate cluster head but only member node E
and F which cannot send beacons, the orphan node D keeps
on sending the non-joined messages until one
of
the
members receives the message. If received, member
transfers the non-joined information of the orphan node to
its cluster head (node B, G). The cluster head changes the
role
of
that member node E and F to a cluster head, and
finally the orphan node can join with the lower level node
E.
B. Sensor Node Design
(1) Network Layer
Since one-way communications are only required to our
model, it is possible to select the path toward the sink
automatically after cluster tree creation. The cluster heads
with i
level
just
send the collected data to its neighbor
cluster heads with i-I level and finally to the sink node.
However, we need to consider other routing protocols, if
the other two information flows would be considered.
(2) MAC Layer
One of the advantages
of
clustering model is that we can
reuse the resource and apply various media access
mechanisms to MAC layer such as TDMA and CSMA. In
Fig. 7, there are a contention access period and a contention
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Round Order(RO)
BeaconOrder O)
time
ACKNOWLEDGMENT
This research was supported by the MKE(The Ministry of
Knowledge Economy), Korea, under the ITRC
(Information Technology Research Center) support
program supervised by the lITA(Institute for Information
Technology Advancement).
Figure
7.
Time line
showing
the
tactical sensor network
operation
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In this paper, we discussed a tactical WSN architecture
with sensor nodes in remote large-scale environments. To
satisfy the tactical WSN needs, we defined the various
requirements, and finally proposed
the
cluster-tree based
multi-hop sensor network with the optimized cluster head
election. The prediction and recovery mechanisms for
maintenance of the network are also designed.
Studies satisfying other tactical requirements (e.g. ,
security, QoS, inter-working with tactical backbone) are
being conducted in order to design more useful tactical
WSN system.
V. CONCLUSION
free period in one frame, and we can use two different
media access mechanisms to each period to guarantee the
reliability of data delivery - contention free mode such as
TDMA
applied to the links from the cluster head to the sink
which is a trunk pipe-l ine in WSN,
contention access mode
such as
CSMA
applied to the link from members to cluster
heads.
(3) Physical Layer
As mentioned in the requirements section, we should
design radio based on LPI, LPD, and anti- jamming. Time
hopping impulse radio UWB is the most possible solut ion
satisfying the requirements. Because UWB sends pulse
of
very short duration, enemy cannot intercept or detect easily
while enabling high data rate, low power, and low cost
radios [6]. Unlike LEACH s adaptive long range
transmission, adaptive short range transmission should be
applied to our model for avoidance
of
enemy s intercept
and detection.
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