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, [email protected]

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.

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978-1-4244-5239-2/09/$26.00 2009 IEEE


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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

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ROUND(S)

20

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Cluster Head Probaility( )

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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

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EI. - Residual Energy Level.

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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

REJo'ERENCES

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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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WSN in Military