GSJ: Volume 8, Issue 1, January 2020, Online: ISSN 2320-9186
www.globalscientificjournal.com
A Review - Communication Architectures and
Routing Protocols of Flying Ad-hoc network
Dr. P. Shanmugaraja †
, Mr. Mohamed Syed Ibrahim *, Mrs. Mary Theres Vini^
† Prof, ECE Dept Annamalai University- India, *Lecturer, Engg dept Ibra College of Technology-Oman, ^ Lecturer,
Computer science dept Thamirabarani Engg college - India
† [email protected], *[email protected], ^ [email protected]
Keywords—Ad-hoc Network; UAVs; FANETs; Routing
Abstract
With later Technical advance within the field of electronics,
sensors and communication frameworks, the generation of
small UAVs (Unmanned Aerial Vehicles) got to be
conceivable, which can be utilized for a few militaries,
commercial and civilian applications. However, the
capability of a single and little UAV is inadequate. Multiple-
UAVs can make a framework that's past the limitations of a
single UAV. A Flying Ad hoc Systems (FANETs) is such
kind of arrange that comprises of a bunch of little UAVs
connected in ad-hoc way, which are coordinates into a
group to achieve high level objectives. Versatility, need of
central control, self-organizing and ad-hoc nature between
the UAVs are the main features of FANETs, which seem
extend the network and extend the communication extend at
infrastructure-less range. On one hand, in case of
disastrous circumstances when ordinary communication
framework isn't accessible, FANETs can be used to supply a
quickly deployable, adaptable, self-configurable and
moderately little working costs organize; the other hand
connecting multiple UAVs in ad-hoc organize could be a
huge challenge. This level of coordination requires a fitting
communication architecture and routing protocols that can
be set up on highly dynamic flying hubs in arrange to set up
a solid and robust communication. The most commitment of
this paper incorporate the introduction of reasonable
communication engineering, and an overview of distinctive
directing conventions for FANETs. The open research
issues of existing routing protocols are too investigated in
this paper.
I. Introduction
Much appreciated to the later approach in electronics, sensors
and communication frameworks, the production of little
UAVs (Unmanned aerial Vehicles) has paved the way for the
conception of low-cost Flying ad-hoc network. Owning to the
flexibility, adaptability, generally small operating costly and
simple establishment, the utilization of FANETs has pulled in
more consideration and significance as of late in several
military, commercial and civilian applications like disaster
management [1], emergency administration and unfriendly
environment [2],destroy and look operations [3], border
surveillanceance [4], wildfire administration [5], transferring
systems [6, 7], estimation of wind [8],civil security [9],
agricultural remote sensing [10], traffic checking [11]. For
illustration, in case of calamitous situation, when standard
communication infrastructure collapsed or basically not
accessible, and where it is troublesome to install foundation in
a brief sum of time. FANETs can be used to offer an
effortlessly deployable and self-configured ad-hoc UAVs
organize to put through with the protect teams on the ground.
With the help of its multi-hop ad-hoc systems schema,
FANETs design approves that all the UAVs are
communicated with each other and to the base station
simultaneously without having any pre-defined fixed
infrastructure [12]. In this way, it cannot as it were convey the
aggregated information to the base station right away, but too
having the capability to share it among the associated UAVs.
Moreover, during the operation in case a few of the UAVs are
disengaged due to the climate condition, it can still make their
network to the organize through the other UAVs. Moreover,
due to the ad-hoc networking among the UAVs, it can fathom
the complications like brief extend, organize disappointment
and restricted direction which arise in a single UAV
framework [13]. Indeed in spite of the fact that, such
distinctive qualities make FANETs an suitable arrangement
for different sorts of scenarios, but they moreover bring some
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
100
GSJ© 2020 www.globalscientificjournal.com
challenging issues such as communications and organizing of
the different UAVs [14].The speed of a ordinary UAV ranges
from nearly 30-460 km/h with development to 3D-space.As
such, the organize topology will alter quickly that results
connectivity issue [15].Beneath these circumstances,
choosing an appropriate communication design and solid
directing conventions are required to supply strong
communication among the UAVs. Particularly, in this paper
we expressly center on communication structures and steering
conventions that are suitable for tending to the
communications issues between the UAVs. We compare the
characteristics of different communication designs and
steering conventions for networking of the different UAVs,
and talk about their advantages and impediments. The
Comparative examination of our review paper will give offer
assistance to arrange engineers in choosing effective
communication engineering and dependable routing protocols
for FANETs arrangement.
The rest of this paper is organized as takes after. Area II
introduces different communication models for FANETs. In
Area III, we offer broad audit of the existing routing
conventions, taken after by dialog on open research issues of
directing conventions in Segment IV. At last, concluding
remarks are displayed in Segment V.
II.Architecture of Communication approach
A communication design recognizes how information trade
between the base station and a UAV or between the UAVs. In
FANETs design, UAVs render real-time communication in ad
hoc way that can cancel the need for the framework and it
amends the communication range imperative [16]. FANETs
engineering performs significant part in scenarios where real-
time communication and run limitations are fundamental
issues, and where it is difficult to give framework [17]. In
FANETs, as the UAVs connect and segregate to the organize
habitually and, consequently, adhoc network between the
UAVs have been found to be the best solution in most cases.
Also, for fast and robust communication between the UAVs,
decentralized communication engineering is more
appropriate. There are several different communication
models proposed for multi-UAV systems [18], in which we
present three communication architectures for FANETs.
A. Unmanned Air Vehicle Ad-hoc network
In a “UAV advertisement Hoc network” engineering, all the
unmanned aerial vehicles (UAVs) are associated with each
other and the base station independently without having a pre-
existing communications set-up. In this particular design,
each and every UAV will be locked in within the information
forwarding of the FANETs framework. Within the UAV Ad-
hoc organize, a backbone UAV act as a door between the
ground station and the other UAVs as appeared in Fig.1.The
portal UAV carries wireless communication gadgets
competent of working on both a low power, brief extend for
communication with the UAV and a high power, long extend
for communicating with the ground station [19]. In this
structure, since as it were backbone UAV is connected with
the ground station, due to which the communication range of
the organize is essentially amplified. Moreover, the distance
between the numerous UAVs are moderately little, the
transceiver gadget in a UAV will be reasonable and
lightweight, which makes them more suitable for little sized
UAV Network. However, in order to maintain connectivity of
the network persistent, the mobility pattern such as speed and
directions need to be similar for all the connected UAVs in
Flying Ad-hoc Networks (FANETs). Hence, this network
architecture is best suitable for a group of similar and small
size UAVs to pursue persistent operations such as
autonomous aerial surveillance mission [20].
Figure 1: UAV Adhoc network
B. Multi-Group UAV Ad hoc Network
A multi-group UAV ad hoc is basically integration of both
ad-hoc position and a centralized network. In this organize as
appeared within the Fig.2, multiple UAVs are associated in an
ad hoc way inside a group, and the bunches are assist
associated through the backbone UAVs to the ground station
in a centralized manner. Intragroup communication is done
without involving the ground station, but inter-group
communication is performed with the assistance of the ground
station. This sort of UAVs network architecture is appropriate
for cases where huge numbers of UAVs are included in a
mission with distinctive flight and communication
characteristics. Be that as it may, due to its semi centralized
nature, this communication engineering is not robust.
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
101
GSJ© 2020 www.globalscientificjournal.com
Figure 2: Multi group UAV
C. Multi-Layer UAV Ad Hoc Network
A multi-layer UAV ad-hoc arrange is appeared in the Fig.3.In
this communication engineering numerous gather consist of
heterogeneous UAVs frame an ad-hoc organize inside an
individual gather. The lower layer is utilized for
communication between the UAVs and the upper layer is
utilized for communication between the spine UAVs of all the
connected bunches and the ground station. The spine UAV of
each bunch is associated with each other and as it were one
backbone UAV is advance straightforwardly associated to the
ground station. The communication or data trade between
multiple bunches does not have to be include or directed
through the ground station. The ground station as it were
forms that information that's ordained to it, comes about
incredibly diminished the communication stack and
computation on ground station. This communication
engineering is best suited for one-to-many UAVs operation.
Figure 3: Multilayer UAV Adhoc
III. Routing Protocols
The profoundly energetic nature of UAVs in FANETs causes
abrupt changes within the arrange topology and thus makes
routing among the UAVs a vital errand [22]. Considering
UAVto- UAV communication, the directing conventions
plays a imperative role in solid end-to-end information
transport and less directing overhead makes directing an
engaging investigate point within the zone of FANETs. Be
that as it may, the most challenge to plan routing protocols
which is reasonable to all scenarios and conditions is still
under investigate. Within the starting considers and tests of
FANETs, the existing MANET and VANET directing
protocols are favored and explored for FANETs. Be that as it
may, due to the UAVs particular traits, such as quick interface
quality changes and fast development in 3D-space, the
organize steering gets to be a crucial errand [23] and most of
the MANET and VANET routing protocols are not pertinent
straightforwardly for FANETs.
Figure 4: Load Carry and Deliver Routing
i. Static Routing Protocols
ii. Proactive Routing Protocols
iii. Reactive Routing Protocols
iv. Hybrid Routing Protocols
v. Geographic/Position Based Routing Protocols
vi. Hierarchical Routing Protocols
A. Static Routing Protocols
Each UAV features a steering table that isn't upgraded amid
the mission. Static routing protocols are appropriate in cases
when the topology of the organize does not alter and where
the choices in route selection are limited. Here, each UAV
communicate with other the UAVs or the ground station and
stores their data as it were. This leads in reducing the number
of communication links. Be that as it may, in case of a
disappointment for updating the routing table, it is obligatory
to wait until the mission is completed. As a result, there
protocols are not fault tolerant.
1) Load Carry and Deliver Routing (LCAD)
In Load Carry and Deliver Routing (LCAD) [25, 26] model, a
UAV store information from a source ground node, convey
this profitable information by flying to a goal ground node as
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
102
GSJ© 2020 www.globalscientificjournal.com
illustrated in Fig. 4. Indeed, in spite of the fact that at first in
LCAD, a single source and a single-destination situation was
inspected but practically, execution of multiple-source
multiple destination scenarios can too be conceivable
effectively in case required. This routing component is doable
for bulk information exchange and delay tolerant applications
with least bounces [27]. The main objectives of LCAD
steering is to maximize throughput and increase the security.
In any case, the most drawback of this protocol is, at
whatever point the remove increments between the
communicating UAVs, the transmission delay becomes
exceptionally expansive and unfortunate. To diminish the
transmission delay, numerous UAVs can be utilized on the
same path, where remove among the UAVs must be least and
speed of UAVs can be expanded.
2) Multilevel Hierarchical Routing (MLH)
Another set of directing arrangements for FANETs beneath
static routing is the multilevel hierarchical protocols [28].
MLH routing convention is outlined to bargain with the
organize scalability issue. Here, the arrange can be gathered
into a number of clusters assigned completely different
operation areas as outlined in Fig. 5. Each cluster incorporates
a cluster head (CH), which portray the entire cluster and has
connections outside cluster as well. It is also conceivable to
relegate distinctive errands to each cluster within the MLH
network. All the UAVs in a cluster are inside the direct
communication extend of the CH. The CH is directly or
indirectly connected with the upper layer UAVs or satellites.
MLH can produce better execution repercussions in the event
that the UAVs are arranged in numerous swarms with huge
operation region, and multiple UAVs are conveyed within the
arrange. Be that as it may, the most crucial plan issue for
MLH steering is the cluster data.
The high mobility of the UAVs required visit cluster
information, and in this way the versatility expectation
clustering address to fathom this issue with the forecast of the
network topology data by the assistance of the word reference
Tree structure prediction calculation [29] and interface close
time mobility model. In this show, the most elevated
weighted UAV among its neighbours is chosen as the cluster
head. The CH determination criteria can improve the
solidness of the clusters and the Cluster Heads (CHs).
Clustering calculation for UAV systems is displayed in [30].
It assigns the clusters on the ground to begin with, and after
that keep updating updating it during the operation. Ground
clustering determines the clustering arrange, and after that
select the CHs based on the geographical data. Additionally,
fair after the deployment of UAVs, the cluster structure is
calibrated concurring to the mission upgrades.
Figure 5: Multilevel Hierarchical Routing
3) Data Centric Routing(DCR)
Data-centric directing calculations usage on FANETs is
additionally conceivable, where information is asked and
collected with reference to the information characteristics
rather than sender or receiver IDs as appeared in Fig.6.
Clearly, since of the wireless nature of the communication
show of UAVs, multicasting can be favored rather than
unicasting. This routing algorithms can be select when the
information ask is produced by a number of UAVs, and data
distribution is done by on-demand algorithms. DCR can be
utilized in FANETs to supply numerous types of applications
on the homogeneous multi-UAV system in arrange construct
up" to construct up express information from a particular
mission area. Publish-subscribe show is more often than not
substantial for this sort of architecture [31, 32]. It interfaces
automatically to the data producers, which are called
distributers, with information consumers, called subscribers.
The producer node receives which information ought to be
distributed and after that begins data dissemination.
After coming to the distributed information to a UAV in the
organize, it attempts to discover the subscription message on
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
103
GSJ© 2020 www.globalscientificjournal.com
it and then advances that information towards the aiming
UAV. The main benefit of this directing calculation is that it
can as it were reports the registered substance to the
endorsers. Data-centric routing algorithms are decoupled in
three measurements:
•Space decoupling: Communicating UAVs can be anywhere
and knowing each other‟s ID or area isn't mandatory.
•Time decoupling: Communicating UAVs are not required to
be online at the same time and information can be sent to the
subscribers right away or later.
•Flow decoupling: Information conveyance can be finished
reliably by nonconcurrent communication structure.
Figure.6: Data Centric Routing
B. Proactive Routing Protocols
In this sort of directing convention, each node periodically
maintains one or more tables showing the total topology of
the organize. Owing to the proactive nature, this routing
protocol has advantage of having courses quickly accessible
when required. Be that as it may, it endures extra overhead
cost because of protecting up-to-date data and as a
consequence throughput of the organize may be influenced
since control messages are sent out pointlessly indeed when
there is no information activity. For this reason, proactive
routing protocol are not altogether great for exceedingly
energetic mobile and huge UAV systems. Moment, too for
cases when the network topology alters or association
disappointment happens, these routing conventions appears a
moderate response to disappointment. There are various
steering conventions that drop beneath this category [33].
1) Destination- Sequenced Distance Vector
(DSDV)
It is based on Bellman-Ford algorithm with little modification
required by making it more reasonable for UAV adhoc
networks. In DSDV each UAV must recognize everything
about all of the other UAVs associated within the arrange
[34]. The routing table here is intermittently overhauled
almost the entire network with grouping number to avoid
routing loops [35]. The recently utilized course with most
elevated grouping number is given preference over on a
course with least arrangement number. The main benefits of
DSDV are both the effortlessness and the utilization of the
arrangement numbers, which guarantees the circle free data
transmission [36]. In any case, the most disadvantage of this
routing algorithm is the occasional upgrading of up-to-date
directing table, which creates an overhead to the network.
This convention isn't appropriate for profoundly energetic
networks where topology changes more regularly. Moreover,
it back single path directing and does not back multipath
steering.
2) Optimized Link State Routing (OLSR)
Routes are persistently put away and overhauled in tables in
OSLR [37]. Subsequently, at whatever point a course is
required, the protocol determines the course rapidly to all
conceivable goals without any starting delay [38]. With the
point of setting up a communication handle between the
UAVs within the arrange running a convention occurrence,
OLSR employments a one of a kind bundle, which comprises
of more than one message. OLSR bundles can carry three
different type of messages, each one for a particular reason:
HELLO message, which is transmit occasionally to discover
network with neighbour, interface detecting, and MPR signalling; Topology Control (TC) message, which promote
to preserve interface states information and Numerous
Interface Announcement (MID) message, which accomplish
the numerous interface announcement on a node
[39].Therefore, this intermittent flooding behaviour comes
about within the form of expansive overhead.
With the utilize of MPRs instrument in OLSR, the message
overheads can be diminished, and the idleness can be
improved. Because the MPR UAV can as it were forward the
messages during the flooding handle. The sender UAV
indicates a set of MPR UAVs so that the MPR UAVs can
cover two bounce neighbours. A UAV which chooses another
UAV as a MPR UAV part is called MPR selector of that
node.Fig.7 appears the MPR selected by the source UAV. In
any case, the foremost noteworthy design parameters for
OLSR is the number of MPRs, which influences the delay
heightening. Clearly, as the number of MPR shrinks, the
overhead will diminish subsequently. On this way, a new
method is proposed for lessening the number of individuals of
MPR. Fig.8 appears a graph for the recommended DOLSR.
For each sending information parcels, the sender UAV
computes the distance to the recipient UAV, at that point in
case the remove is bigger than the greatest separate that can
be achieved by utilizing the directional radio wire (Dmax/2).
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
104
GSJ© 2020 www.globalscientificjournal.com
Figure 7: Multipoint Relay (MRP)
Figure 8: DOLSR Block Diagram
C. Reactive Routing Protocols
The receptive directing convention (RRP) is additionally
known as on demand routing convention, implies it finds or
keeps up a route on request. The steering table here is
intermittently updated, when there's a few information to
send, if there's no connection between two hubs, there's no
got to calculate a route between them. Hence these steering
conventions hold the routes only that are by and by in utilize
[41], therefore as a result it overcome the overhead issue of
PRP. In this steering model, there are two sorts of messages
produced: (1) Route Request and (ii) Route Reply message
[36]. Route Request message is transmitting from the source
UAV to all adjoining UAVs using flooding instrument to find
the way, and each UAV uses the same approach until it comes
to the goal UAV. While the Route Reply message is initiated
by the destination UAV and goes to the source UAV utilizing
the unicast communication mode. In this steering approach,
there's no ought to revive all tables within the organize.
1) Dynamic Source Routing (DSR)
In [42], Brown et al. developed FANETs test bed with
Dynamic Source Routing (DSR) [43] protocol. It allows a
network to be self-configuring, self-organizing and without
the need for having any available infrastructure. The main
objective of choosing DSR is its reactive nature and is mainly
used for multi-hop wireless mesh networks. In DSR the
source only tries to find a path to a destination in a scenario,
whenever it has data to send. DSR is more suitable than
proactive methods for FANETs, where the mobility of the
UAVs is high, and the topology is not stable [44]. Updating a
routing table by a proactive method is not that much optimal
due to the high mobility of the UAVs. However, repetitive
path finding by reactive method before each packet delivery
can also be exhaustive.
2) Ad Hoc On-Demand Distance Vector (AODV)
Ad Hoc On-Demand Separate Vector (AODV) is the
enhanced adaptation of both DSDV and DSR steering
conventions. It inherits occasional overhauls from DSDV and
hop-to- jump routing from DSR. Due to the responsive
behaviour, AODV find a route as it were when it is craved
and does not hold courses to destination that are not dynamic
within the communication process [45]. AODV steering
convention comprises of three stages :(i) route revelation (ii)
parcel transmitting (iii) course maintaining. Whenever a
source UAV wishes to send a parcel, it first initiates a course
disclosure operation to distinguish the location of the intended
UAV and after that forward bundle over a decided route
without having a circle amid bundle transmitting stage. Route
maintenance stage take put to re-establish interface
disappointment. This routing convention employments an
arrangement number to discover an up-to-date optimal course
towards the goal.
3) Time-slotted on-demand Routing
Time-slotted on-demand directing convention is also
proposed in [46] for FANETs. This directing calculation is
basically time-slotted form of Ad-hoc On-demand Distance
Vector Directing (AODV) [47]. AODV sends its control
packets on random-access mode, while time-slotted on-
demand protocol hones committed time spaces in which as it
were one UAV can send information bundle. This steering
strategy not as it were increment the usable transmission
capacity productivity, but moreover dodge the packet
collisions and increments the parcel conveyance proportion.
D. Hybrid Routing Protocols
The Hybrid Routing Protocol (HRB) may be a combination of
both proactive and reactive routing protocols, taking the best
features and to overcome the restrictions from both worlds.
Reactive routing conventions by and large needs additional
time to discover route and proactive routing protocols has
huge overhead of control messages. These deficiencies can be
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
105
GSJ© 2020 www.globalscientificjournal.com
mitigated by utilizing HRP. Crossover conventions are
especially appropriate for huge systems, and is based on the
concepts of zones where intra-zone directing is executed with
the assistance of proactive routing and inner-zone routing is
accomplished utilizing the reactive routing approach.
1) Zone Routing Protocol (ZRP)
This routing calculation is fundamentally based on the
concept of “zones” [48], and is reasonable for expansive
arrange ranges and diverse mobility patterns. In this steering
approach, each UAV has a different zone, and the zone of
neighbouring UAVs cover. The size of the zone is decided by
a sweep of length “R”. “R” is the number of UAVs to the
border of the zone. The number of UAVs within the zone can
be directed by altering the transmission control of the
UAVs.The steering inside the zone is called as intra-zone
directing. The intra-zone routing uses “proactive routing”
approach to preserve the routes. If the source and goal UAVs
are accessible within the same zone, the source UAV can
begin information communication instantly. The inter-zone
routing is responsible for sending information packets to
outside of the zone, and it utilizes receptive directing
approach to maintain and finding the ideal courses. The delay
caused by the route disclosure is minimized by utilizing
border casting [49]. Reply messages are as it were produced
by border UAVs of a zone. The border UAVs at that point
rehash either by selecting associate- or intra-zone routing as
required.
2) Temporarily Ordered Routing Algorithm
(TORA)
(TORA) is a highly versatile on-demand steering convention,
reasonable for multihop networks. In this steering approach,
each UAVs as it were update routing data approximately
adjoining UAVs. The key highlights of using this steering
calculation is to constrain the engendering of control message
in a exceedingly portable environment in arrange to minimize
quick responses to topological changes [50]. It deletes invalid
routes and looks for unused courses in a single-pass of the
distributed calculation. Especially, TORA employments
receptive routing protocols, but it moreover utilizes proactive
approaches in a few cases. It constructs and keeps up (DAG)
from the source to goal UAV. There are a few courses among
these UAVs in DAG. It is favored for fast computing of new
routes in case of disengaged joins and for enhancing
adaptability [51]. TORA isn't based on the most limited path
algorithm; longer courses are normally used to play down
network overhead. Each UAV has a parameter esteem known
as “height” in DAG, and no two UAVs have the same tallness
esteem. Data flow from the higher UAVs to lower UAVs like
top-down approach. It offers loop-free directing, since of no
information flow towards the higher tallness UAVs. Within
the course disclosure process, this tallness parameter is
returned to the asking UAV, and in this approach all the
middle of the road UAVs keep up their routing tables
concurring to the approaching courses and statures data.
E. Geographic/ Position Based Routing Protocols
Position-based routing protocols have been proposed to
assume information of the geological position data of UAVs
to supports effective directing [52]. In this sort of protocols,
they accept that the source UAV knows approximately the
physical position of the communicating UAVs and sends
message to the goal UAVs without course discovery.
Generally, each UAV decides its claim position with the help
of GPS framework or any other sort of situating office. This
routing calculation is essentially propelled by two subjects:
i) A position facility is ordinarily utilized by the sender of a
packet to find the physical position of the collector and (ii) A
forwarding approach is utilized to forward information
parcels to the intended UAV.
1) Greedy Perimeter Stateless Routing (GPSR)
Greedy Perimeter Stateless Routing (GPSR) [53], which is
also a position-based convention, having way better
performance comparatively to proactive and responsive
steering algorithms It was shown that “GPSR sending routing
protocols” are applicable for thickly sent UAVs Arrange. Be
that as it may, the reliability of the arrange can be an extreme
issue in circumstance of sparse deployments. A combination
of other mechanisms, such as confront directing, ought to be
utilized for the applications that target 100% reliability. Be
that as it may, at first for FANETs deployments the existing
MANET directing calculations have tried, in which most are
not well suited for FANETs, due to the UAV distinct
obstruction such as quick variety within the interface quality
and very high mobility of the flying nodes.
2) Geographic Position Mobility Oriented Routing
Geographic Position Portability Oriented Routing (GPMOR)
was displayed for FANETs in [55]. The customary position
based solutions as it were depending on the area data of the
UAVs. Be that as it may, GPMOR moreover figure out the
development of UAVs with “Gaussian-Markov portability
model”, and it utilizes this information to find the following
bounce. It is examined that this routing mechanism can give
information sending successfully with reference to bundle
conveyance proportion and inactivity.
F. Hierarchical Routing Protocols
In hierarchical routing protocols the capacity of choosing
proactive and of responsive steering depend on the various
leveled level of the organize in which a UAV dwells.
This particular routing is primarily decided with a
few proactive arranged courses and then makes a
difference the ask from by activated hubs through reactive
protocol at the lower levels. The most drawback of this
protocol include complexity and plot of tending to which
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
106
GSJ© 2020 www.globalscientificjournal.com
response to activity ask and as a repercussion it wrap the
interconnecting variables.
1) Mobility Prediction Clustering
Algorithm(MPCA)
Mobility Prediction Clustering Algorithm(MPCA) proposed
for UAV organizing [56] based on the traits of UAVs.
It administers on the lexicon of trie-structure prediction
algorithm and interface termination time to illuminate the
issues regarding high versatility of the
UAVs.The fundamental advantage of this algorithm is
to decrease the instability of clustering and improves
the arrange execution.
2) Clustering Algorithm of UAV networking
Clustering algorithm is based to overcome the difficulty of
managing out of locate UAVs. In case of multi
UAV framework, it constructs clusters on the ground, and
after that alter it within the space
to progress the steadiness and adaptability of near-space
clusters [57].
IV. Issues for Open research
Due to the quick versatility of UAVs, topology of the network
change quickly in FANETs that constitutes steering issue
among the UAVs. Since of this one of a kind FANETs
challenge, the existing MANET and
VANET directing conventions fall flat to meet all the
FANETs prerequisites. The directing calculations and
protocols should be advanced sufficient to upgrade routing
tables powerfully agreeing to the topological changes. Peerto-
peer network is required for collaborative coordination,
congestion control and collision avoidance among the UAVs
in FANETs. Be that as it may, it is
additionally conceivable to utilize FANETs in the form
of remote sensor systems to accumulate data from the
environment, which make distinctive activity design. All the
data are directed among a restricted number of UAVs that are
directly connected to a foundation. At the same time,
developing new directing calculations are too required that
can support peer to peer networks. Within the show time,
FANETs is still relatively an unused research range,
where modern routing algorithms affected and previous ones
are adjusted. Sum of the calculations is adequate, which can
be depicted by the requirements diversity and the attributes of
transmitted information. Information centric routing is an
optimistic approach for FANETs. With the back of the
publish-subscribe design of information centric algorithms, it
might be promising to make multi-UAV systems that can
validate different application scenarios. To the extent of our
understanding, data centric routing algorithm isn't examined
yet completely.
V. Conclusion
FANETs have ended up a developing research field, which
consists of a bunch of little UAVs associated in ad-hoc mode.
Such systems are recognized by a high mobility, frequent
topology changes and 3D-space movement of the nodes,
which constitutes organizing issues. In order to overcome
such kind of issues, choosing an appropriate communication
architecture and reliable routing protocols are required to
authenticate robust communication between the UAVs.In this
paper, we to begin with introduced three different
decentralized communication models, in which we proposed a
multi-layer UAV ad hoc network more reasonable for
FANETs. In this way, we explored different routing
protocols alongside open inquire about issues. We trust this
investigation will offer assistance organize engineers for
FANETs deployment. We moreover accept that FANETs will
be ubiquitous technology within the future.
VI. References
[1] M. Erdelj, E. Natalizio,K.R. Chowdhury and I.F Akyildiz,
“Help from the sky:Leveraging UAVs for disaster
management,” IEEE Pervasive Computing ,vol.16, Issue: 1,
March 2017 .
[2] ANCHORS project. "[Online]. Available:
http://anchorsproject.org/index.
php/en/home/14-das-projekt -i m-ueherhl ick17 -
projectoverview.htm!.
[Accessed on 02 February 2016].
[3] J. George, P.B. Sujit and J. Sousa, “Search strategies for
multiple UAV search and destroy missions,” Journal of
Intelligent and Robotics Systems 61 (2011), pp.355–367.
[4] Z. Sun, P. Wang, M.C. Vuran, M. Al-Rodhaan, A. Al-
Dhelaan and I.F. Akyildiz, “BorderSense: border patrol
through advanced wireless sensor networks,” Ad Hoc
Networks 9 (3) (2011),pp. 468–477.
[5] C. Barrado, R. Messeguer, J. Lopez, E. Pastor, E.
Santamaria and P. Royo, “Wildfire monitoring using a mixed
air-ground mobile network,” IEEE Pervasive Computing 9 (4)
(2010),pp. 24–32.
[6] E.P. de Freitas, T. Heimfarth, I.F. Netto, C.E. Lino, C.E.
Pereira, A.M. Ferreira, F.R. Wagner and T. Larsson, “UAV
relay network to support WSN connectivity,” ICUMT, IEEE,
2010, pp. 309–314.
[7] F. Jiang and A.L. Swindlehurst,“Dynamic UAV relay
positioning for the ground-to-air uplink,” IEEE Globecom
Workshops, 2010.
[8] A. Cho, J. Kim, S. Lee and C. Kee, “Wind estimation and
airspeed
calibration using a UAV with a single-antenna GPS receiver
and pitot
tube,” IEEE Transactions on Aerospace and Electronic
Systems 47 (2011),pp.109–117.
[9] I. Maza, F. Caballero, J. Capitan, J.R. Martinez-De-Dios
and A. Ollero, “Experimental results in multi-UAV
coordination for disaster
management and civil security applications,”Journal of
Intelligent andRobotics Systems 61 (1–4) (2011),pp.563–585.
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
107
GSJ© 2020 www.globalscientificjournal.com
[10] H. Xiang and L. Tian, “Development of a low-cost
agricultural remote sensing system based on an autonomous
unmanned aerial vehicle,” Biosystems Engineering 108 (2)
(2011), pp.174–190.
[11] E. Semsch, M. Jakob, D. Pavlicek and M. Pechoucek,
“Autonomous UAV Surveillance in Complex Urban
Environments,” Web Intelligence, 2009, pp. 82–85.
[12] Bekmezci, M Ermis and S Kaplan, “Connected multi
UAV task planning for flying ad hoc networks,”
Communications and Networking
(BlackSeaCom), IEEE International Black Sea Conference,
2014, pp. 28- 32.
[13] V. Sharma and R. Kumar, “A cooperative network
framework for multi- UAV guided ground ad hoc networks,”
Journal of Intelligent & Robotic Systems, vol. 77, no. 3, pp.
629–652, Mar. 2015.
[14] Bekmezci, O. K. Sahingoz, and S. Temel, “Flying ad-hoc
networks(FANETs): A survey,”Ad Hoc Networks vol. 11, no.
3, pp. 1254-1270,
2013. [15] E. W. Frew and T. X. Brown, “Networking issues
for small unmanned aircraft systems,'' J. Intell. Robot. Syst.,
vol. 54, no. 1, pp. 21-37, 2008. [16] L. Gupta, R. Jain, and G.
Vaszkun, “Survey of important issues in UAV
communication networks,” IEEE Communications Surveys &
Tutorials, vol. 18, no. 2, pp. 1123–1152, 2015.
[17] Bekmezci, İ., and Ulku, E, “Location information
sharing with multi token circulation in flying Ad Hoc
networks,” Proceedings of 7th International Conference on
Recent Advances in Space Technologies (RAST) Istanbul,
Turkey,2015.
[18] Jun Li, Yifeng Zhou and L. Lamont, “Communication
architectures and protocols for networking unmanned aerial
vehicles,” IEEE Globecom Workshops, pp. 1415–1420, 2013.
[19] O. Sahingoz, “Mobile networking with UAVs:
Opportunities and
challenges,” in Unmanned Aircraft Systems (ICUAS), 2013
International Conference on, May 2013, pp. 933–941.
[20] R. W. Beard, T. W. Mclain, D. B. Nelson, D. Kingston
and D. Johanson, “Decentralized cooperative aerial
surveillance using fixed wing miniature UAVs,” Proceedings
of the IEEE, vol. 94, no. 7, pp. 1306 - 1324, July 2006.
[21] E. A Marconato, D. F Pigatto,C. Branco, J. A Maxa, N.
Larrieu, et al, “IEEE 802.11n vs. IEEE 802.15.4: A study on
communication QOS to provide safe FANETs”, 46th annual
IEEE/IFIP international conference on dependable systems
and networks workshop (DSN-W), june 2016, pp.184-191.
[22] W. Zafar and Bilal M. Khan, “Flying ad-hoc networks:
Technological and social implications,” IEEE Technol. Soc.
Mag., vol. 35, no. 2, pp 67-74, June 2016.
[23] K. Zhang, W. Zhang, and J.-Z.Zeng, “Preliminary Study
of Routing and
Date Integrity in Mobile Ad Hoc UAV Network,” in
Apperceiving
Computing and Intelligence Analysis, 2008.ICACIA 2008.
International
Conference on, Dec 2008, pp. 347–350.
[24] M. H. Tareque, M. S. Hossain, and M. Atiquzzaman,
„„On the routing in flying ad hoc networks,‟‟ in Proc.
Federated Conf. Comput. Sci. Inf. Syst. (FedCSIS), pp. 1–9,
Sep. 2015.
[25] Cheng, C.M., Hsiao, P.H., Kung, H.T., Vlah, D.:
Maximizing throughput of UAV-relaying networks with the
load-carry-and-deliver paradigm. In: IEEE Wireless
Communications and Networking Conference (WCNC 2007)
(2007).
[26] Le, M., Park, J.S., Gerla, M.: UAV Assisted disruption
tolerant routing. In: Military Communications Conference,
MILCOM 2006, pp. 1–5 (2006)
[27] Jonson, T., Pezeshki, J., Chao, V., Smith, K., Fazio, J.:
Application of Delay Tolerant Networking (DTN) in airborne
networks. In: IEEE Military Communications Conference-
(MILCOM 2008), pp. 1–7 (2008).
[28] Lamont, G.B., Slear, J.N., Melendez, K.: UAV swarm
mission planning and routing using multi-objective
evolutionary algorithms. In: IEEE Symposium on
Computational Intelligence in Multicriteria Decision Making,
pp. 10–20 (2007)
[29] C. Konstantopoulos, D. Gavalas, G. Pantziou, A mobility
aware technique for clustering on mobile ad-hoc networks, in:
Proceedings of the 8th International Conference on Distributed
Computing and Networking, ICDCN‟06, Springer-Verlag,
Berlin, Heidelberg, 2006, pp. 397–408.
[30] L. Kesheng, Z. Jun, Z. Tao, The clustering algorithm of
UAV networking in near-space, in: 8th International
Symposium on Antennas, Propagation and EM Theory, 2008
(ISAPE 2008), 2008, pp. 1550–1553.
[31] J. Ko, A. Mahajan, R. Sengupta, A network-centric UAV
organization for search and pursuit operations, Aerospace
Conference Proceedings, 2002, vol. 6, IEEE, 2002, pp. 2697–
2713.
[32] J. Lopez, P. Royo, E. Pastor, C. Barrado, E. Santamaria,
A middleware architecture for unmanned aircraft avionics, in:
Proceedings of the 2007 ACM/IFIP/USENIX International
Conference on Middleware Companion, MC ‟07, ACM, New
York, NY, USA, 2007, pp. 24:1–24:6
[33] P. L. Yang, C. Tian, and Y. Yu, “Analysis on optimizing
model for proactive ad hoc routing protocol," in Proc.
Military Commun. Conf.
(MILCOM), vol. 5, Atlantic City, NJ, USA, pp. 2960-2966,
Oct. 2005.
[34] Muneer Bani Yassein and “Nour Alhuda” Damer “Flying
Ad-HocNetworks: Routing Protocols, Mobility Models,
Issues,” International
Journal of Advanced Computer Science and Applications,
vol. 7, no. 6, pp.162-168, 2016.
[35] Perkins, C.E., Bhagwat, P.: Highly dynamic
estinationSequencedDistance-Vector Routing (DSDV) for
mobile computers. In: proceedings of the Conference on
Communications Architectures, Protocols and
Applications (SIGCOMM „94), pp. 234–244 (1994).
[36] OKSahingoz. “Routing ptocols in flying Ad-hoc
networks (FANETs): Concepts and challenges”. Journal of
Intelligent & Robotic Systems, pp.513-27. April 2014.
[37] Singh, J.; Mahajan, R. Performance analysis of AODV
and OLSR usingOPNET. Int. J. Comput. Trends Technol.
2013, 5, 114–117.
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
108
GSJ© 2020 www.globalscientificjournal.com
[38] PJacquet, T.Clausen, L. Viennot, "Optimized link state
routing [OLSR]protocol for adhoc network", in proceedings
of IEEE Multi Topic Conference, lNMlC, March 2001.
[39] A. Zaballos, A. Vallejo, G. Corral and J. Abella, “Ad-
Hoc Routing
Performance Study Using OPNET Modeler,” Barcelona,
2006.
[40] A.I. Alshabtat, L. Dong, J. Li, F. Yang, “Low latency
routing algorithm for unmanned aerial vehicles ad-hoc
networks”, International Journal of Electrical and Computer
Engineering 6 (1), 2010, pp. 48–54.
[41] Habib, S., Saleem, S., & Saqib, K. M., “Review on
MANET routing
protocols and challenges”, IEEE Student Conference on
Research and Development SCOReD , pp. 529-533 , 2013.
[42] T. Brown, S. Doshi, S. Jadhav, D. Henkel, R.
Thekkekunnel, A full scale wireless ad hoc network test bed,
in: Proc. of International Symposium on Advanced Radio
Technologies, Boulder, CO, 2005, pp. 50–60.
[43] D.B. Johnson, D.A. Maltz, Dynamic source routing in ad
hoc wireless networks, in: T. Imielinski, H.F. Korth (Eds.),
Mobile Computing, The Kluwer International Series in
Engineering and Computer Science, vol. 353, Springer, US,
1996, pp. 153–181.
GSJ: Volume 8, Issue 1, January 2020 ISSN 2320-9186
109
GSJ© 2020 www.globalscientificjournal.com