Trust Based Scheme for QoS Assurance in Mobile Ad-Hoc Networks

International Journal of Network Security & Its Applications (IJNSA), Vol.4, No.1, January 2012
DOI : 10.5121/ijnsa.2012.4108 77
Trust Based Scheme for QoS Assurance in
Mobile Ad-Hoc Networks
Sridhar Subramanian1
and Baskaran Ramachandran2
1
Department of Computer Applications, Easwari Engineering College, Chennai, India.
ssridharmca@yahoo.co.in
2
Department of Computer Science & Engineering, CEG, Guindy, Anna University,
Chennai, India.
baskaran.ramachandran@gmail.com
ABSTRACT
A mobile ad-hoc network (MANET) is a peer-to-peer wireless network where nodes can communicate
with each other without the use of infrastructure such as access points or base stations. These networks
are self-configuring, capable of self-directed operation and hastily deployable. Nodes cooperate to
provide connectivity, operates without centralized administration. Nodes are itinerant, topology can be
very dynamic and nodes must be able to relay traffic since communicating nodes might be out of range.
The dynamic nature of MANET makes network open to attacks and unreliability. Routing is always the
most significant part for any networks. Each node should not only work for itself, but should be
cooperative with other nodes. Node misbehaviour due to selfish or malicious intention could significantly
degrade the performance of MANET. The Qos parameters like PDR, throughput and delay are affected
directly due to such misbehaving nodes. We focus on trust management framework, which is intended to
cope with misbehaviour problem of node and increase the performance of MANETs. A trust-based
system can be used to track this misbehaving of nodes, spot them and isolate them from routing and
provide reliability. In this paper a Trust Based Reliable AODV [TBRAODV] protocol is presented which
implements a trust value for each node. For every node trust value is calculated and based trust value
nodes are allowed to participate in routing or else identified to become a misbehaving node. This
enhances reliability in AODV routing and results in increase of PDR, decrease in delay and throughput
is maintained. This work is implemented and simulated on NS-2. Based on simulation results, the
proposed protocol provides more consistent and reliable data transfer compared with general AODV, if
there are misbehaving nodes in the MANET.
KEYWORDS
Ad-hoc, AODV, TBRAODV, MANET, Trust, Misbehaving node, Qos
1. INTRODUCTION
MANET is a highly challenged network environment due to its special characteristics
such as decentralization, dynamic topology and neighbour based routing. They don’t rely
on existing infrastructure to support communication. Each mobile node acts as an end node
when it is the source or destination of a communication and forwards packets for other nodes
when it is an intermediate node of the route. Mobile Ad-Hoc network [1] is a system of wireless
mobile nodes that self-organizes itself in dynamic and temporary network topologies. Mobile
ad hoc networks are suitable for dynamic environment where no infrastructure or temporarily
established mobile applications are used, which are cost effective. Ad hoc networks are easier
to deploy than wired networks and are found many applications, such as in rescue, battlefields,
meeting rooms etc., where either a wired network is unavailable or deploying a wired network
is inconvenient. Distributed state in unreliable environment, dynamic topology, limited network
capacity, variable link quality, interference and collisions, energy-constrained nodes, flat

78
addressing, scaling issues, heterogeneity are few challenges faced by MANET. Mobile ad hoc
network routing protocols face some challenges like node mobility that causes frequent
topology changes , the changeable and erratic ability of wireless links and packet losses.
Mobile nodes also face troubles like limited power, computing and bandwidth resources.
There have been many ad-hoc routing protocols, which fall into several categories: proactive
routing protocols such as dynamic Destination-Sequenced Distance-Vector routing (DSDV),
Optimized Link State Routing (OLSR), Topology Broadcast based on Reverse Path Forwarding
(TBRPF), on-demand routing protocols such as Dynamic Source Routing (DSR), AODV,
Signal Stability-based Adaptive routing (SSA). Proactive routing protocols have little delay for
route discovery and are robust enough to link breaks and obtain a global optimal route for each
destination. However, their routing overhead is also high. On-demand routing protocols are
easy to realize and their overhead is low. But routes in on-demand routing protocols are easy to
break in the case of topology variations. In AODV [2] node doesn’t have any information about
other nodes until a communication is needed. By broadcasting HELLO packets in a regular
interval, local connectivity information is maintained by each node. Local connectivity
maintains information about all the neighbours.
Recent Qos solutions are planned to operate on trusted environments and totally assume the
participating nodes to be cooperative and well behaved [3, 4]. Such assumptions are not valid in
dynamic environments like MANETs. Providing different quality of service levels in a
persistently changing environment is a challenge because: Unrestricted mobility causes QoS
sessions to suffer due to recurrent path breaks, thereby requiring such sessions to be re-
established over new paths. The link-specific and state-specific information in the nodes is
inherently imprecise due to the dynamically changing topology and channel characteristics.
Hence, incorrect routing decisions may chop down Qos parameters performance. Inadequate
bandwidth, storage space and battery life also drastically influence the performance of the QoS
parameters.
Most security schemes suggested for MANETs tend to build upon some fundamental
assumptions regarding the trustworthiness of the participating hosts and the underlying
networking system. If MANET is to achieve the same level of acceptance as traditional wired
and wireless network infrastructures, then a framework for trust management must become an
intrinsic part of its infrastructure. The inherent freedom in self-organized mobile ad hoc
networks introduces challenges for trust management, particularly when nodes do not have any
prior knowledge of each other. To assure that access to resources is given only to trusted nodes;
the trustworthiness among anonymous nodes needs to be formalized. The concept of trust
originally derives from social sciences and is defined as the degree of subjective belief about
the behaviours of a particular entity [5]. There are four major properties [6, 7] of Trust and they
are, Context Dependence where trust relationships are only meaningful in the specific contexts.
Function of Uncertainty where trust is an evaluation of probability of if an entity will perform
the action. Quantitative Value are where trust can be represented by numeric either continuous
or discrete value. Asymmetric Relationship are where trust is the opinion of one entity for
another entity.
This traditional AODV is to perform its job based on the trust values calculated for each node
and to decide whether to take part or to be isolated from routing. The trust value is calculated
for each node based on its success rate and failure rate of transmission. This trust value
calculated helps to identify whether the node will be reliable node for performing the routing or
may not be reliable for this current transmission. This trust based routing mechanism helps to
identify and eliminate misbehaving nodes in MANET and performs an efficient and effective
routing. This proposed work also improves the Qos parameters like packet delivery ratio and
delay.

79
2. LITERATURE SURVEY
Mobile Ad-Hoc Networks (MANETs) are adaptive and self-organizing, and as a
consequence, securing such networks is non-trivial. Mobile ad hoc networks are apt for
mobile applications either in antagonistic environments where no infrastructure is available, or
temporarily established mobile applications, which are cost decisive. In recent years,
application domains of mobile ad hoc networks gain more and more significance in non-
military public organizations and in commercial and industrial areas. Medium access control,
routing, resource management, quality of service and security are the research areas for mobile
ad hoc network. The importance of routing protocols in dynamic networks has directed a lot of
mobile efficient ad hoc routing protocols.
A security-enhanced AODV routing protocol called R-AODV (Reliant Ad hoc On-demand
Distance Vector Routing) [8] uses a modified trust mechanism known as direct and
recommendations trust model and then incorporating it inside AODV. This enhances security
by ensuring that data does not go through malicious nodes that have been known to misbehave.
Each node is given a trust value and this value is associated with the possibility of the node to
perform a packet drop. With the inclusion of trust mechanism, it is expected that using R-
AODV would result in a higher percentage of successful data delivery as compared to AODV.
It is also expected that the normalized routing load and end-to-end delay would increase.
A framework for estimating the trust between nodes in an ad hoc network based on quality of
service parameters using probabilities of transit time variation, deleted, multiplied and inserted
packets, processing delays to estimate and update trust [9]. This paper clearly shows that only
two end nodes need to be concerned and attain reduced overhead. The framework proposed in
this paper is applicable and useful to estimate trust in covert unobservable and anonymous
communications. This results in detecting regular packets drops and delay detection.
A schema is formed via direct and indirect approach to compute trust value among anonymous
nodes [10]. To evaluate trust values the parameters like reputation, knowledge, observation and
context were used. The trust schema that is build is used to allow resource to be shared among
trusted nodes. The result obtained is then mapped with the access privileges to take appropriate
actions.
A routing protocol, which adds a field in request packet and also stores trust value indicating
node trust on neighbour based on level of trust factor [11 is discussed here. The routing
information will be transmitted depending upon highest trust value among all. This not only
saves the node’s power by avoiding unnecessary transmitting control information but also in
terms of bandwidth (channel utilization), which is very important in case of MANET. The
malicious node can attack on the control packet and misbehave in the network. A trusted path is
used irrespective of shortest or longest path, which can be used for communication in the
network. It calculates route trust value on the complete reply path, which can be utilized by
source node for next forthcoming communication in the network. Thus security level is
improved and also malicious node attacks are prevented in the network.
A trust model introduced in the network layer leads to a secure route between source and
destination without any intruders or malicious nodes in the network [12]. This trust based
routing protocol concentrates both in route and node trust. Node Trust Calculation Process is
done by introducing a new data structure neighbour table in each node of the MANET. Node
trust is calculated by the collective opinion of node’s neighbours. The resultant trust value is
placed in trust value field of neighbour table. Node trust calculated based upon the information
that one node could collect about the other nodes. Route Trust Calculation Process is done
using a modified extended route table. With this minimum overhead, eliminates the malicious
node as well as establish a best-trusted route between source and destination.

80
TAODV [13], an enhanced AODV protocol was proposed with a concept of trust values for
calculating trust values of nodes. The changes made to the existing protocol are, two new
control packets TREQ (Trust request) & TREP (Trust Reply) and a modified extended routing
table with four new fields; positive events, negative events, route status, opinion. This provided
a reliable routing
3. PROPOSED WORK
Many trust management schemes have been proposed to evaluate trust values and most of the
trust-based protocols for secure routing calculated trust values based on the characteristics of
nodes behaving properly at the network layer. Trust measurement can be application dependent
and will be different based on the design goals of proposed schemes [14]. The trust
management metrics include overhead (e.g., control packet overheads), throughput, packet
delivery ratio, packet dropping rate, and delay.
Routing in mobile ad hoc networks is pretentious due to the dynamic nature of nodes, which are
not stable and keep moving. But still nodes communicate with each other and exchange data
within the available nodes on the network. The architecture of the proposed work is presented
in figure 1.The node trust plays a very crucial role in MANET routing. Trust factor here focuses
on identifying the nodes which not suitable for reliable routing and helps to select an alternate
path to carry on routing successfully using reliable nodes. The proposed work concentrates on
identifying these unreliable nodes using the trust level values calculated for each node.
Figure 1. Architecture of proposed TBRAODV routing in MANET
The trust level value calculation is based on the parameters shown in the table 1. The count
field describes about two criteria success and failure which describes whether the transmission

81
was a successful transmission or a failure. RREQ and RREP are the route request and route
reply respectively which are exchanged between nodes in the network. Data refers to the
payload transmitted by the node in the routing path.
Table 1. Trust value calculation parameters
Count Type RREQ RREP Data
Success Qrs Qps Qds
Failure Qrf Qpf Qdf
The parameter qrs is defined as the query request success rate which is calculated based on
number of neighbouring nodes who have successfully received (rreq) from the source node
which has broadcasted it, qrf defined as the query request failure rate which is calculated based
on number of neighbouring nodes which have not received the query request, qps is defines as
the query reply success rate which is calculated as successful replies (rrep) received by the
source node which has sent the rreq and qpf is defined as the query reply failure rate which is
calculated based on the number of neighbouring nodes which have not sent the replies for the
query request received. qds is defined as the data success rate calculated based on successfully
transmitted data and qdf is defined as data failure rate calculated based on data which have
failed to reach destination. However, it is known that for every network there will be minimum
data loss due to various constraints.
rfrs
rfrs
qq
qq
Qr
+
−
= (1)
pfps
pfps
qq
qq
Qp
+
−
= (2)
dfds
dfds
qq
qq
Qd
+
−
= (3)
Where Qr, Qp and Qd are intermediate values that are used to calculate the nodes Request rate,
Reply rate and Data transmission rate. The values of Qr, Qp, and Qd are normalized to fall in
range of -1 to +1. If the values fall beyond the normalized range then it clearly shows that the
failure rate of the node is high and denotes that the corresponding node may not be suitable for
routing.
dQDATATQpRREPTQrRREQTTL *)(*)(*)( ++= (4)
Where, TL is the trust level value and T(RREQ), T(RREP) and T(DATA) are time factorial at
which route request , route reply and data are sent by the node respectively. Apart from the
above mentioned normalised range, using the above formula the trust level value (TL) is
calculated for each node during routing and is checked against the threshold value (assumed to
be as 5). If lesser than threshold then there is a possibility for this node to be marked as
misbehaving node for the current transmission and will not be suitable for further routing and
an alternate path is selected for routing. However, this node may be the best node for some

82
other transmission between some other source and destination in the same network. TBRAODV
checks every node with its trust value to make itself robust and trustworthy for effective and
efficient routing and also to assure qos in MANET.
For the sample network shown in figure 2, the path selected is S F E G D. For
example, Node E has four neighbours and for this node the trust value calculation is to
be done.
Figure 2. Sample network to implement TBRAODV
For node E the trust value calculation table is given in table 2 which contains the
success and failure rate of route request, reply and data.
Table 2. Trust value calculation for Node E
Count Type RREQ RREP Data
Success 4 4 900
Failure 0 0 100
Qr = ( 4 - 0 ) / ( 4 +0 ) = 1
Qp = ( 4 - 0 ) / ( 4 +0 ) = 1
Qd = ( 900-100 ) / ( 900+100) = 0.8
The values of Qr, Qp, and Qd are falling within the normalized range fixed (i.e) -1 to +1.
Thus the trust value is calculated for the node E.
TL = 1*1!+1*2!+0.8*3! = 7.8 (which is more than 5) thus making this node a reliable node for
routing. This trust calculation is done for all nodes in the routing path to monitor nodes
behaviour. If the failure rate increases it automatically affects the Qr, Qp and Qd values thus
making them fall beyond the normalized values thus resulting in trust value less than the
threshold.

83
4. EVALUATION RESULTS
The performance of proposed TBRAODV protocol is analyzed using NS-2 simulator. The
network is designed using network simulator with maximum of 50 nodes. Other parameters
based on which the network is created are given in Table3. Results are obtained from this
simulation applying both general AODV and proposed TBRAODV protocols. The proposed
TBRAODV protocol has shown good improvement over the QoS parameters like PDR &
Delay. PDR is increased and delay is reduced compared to the general AODV. Throughput is
maintained. Graphs are used to compare the results of the existing AODV and proposed
TBRAODV protocol and clearly indicate the improvement of the proposed protocol.
Table 3. Simulation Parameter Values
Parameter Value
Network size 1600 x 1600
Number of nodes 50
Transmission range 250 meters.
Movement speed 100 kbps
Traffic type CBR
Packet size 5000
Simulation time 30 minutes.
Maximum speed 100 kbps
Time interval 0.01 sec.
MAC layer protocol IEEE 802.11
Protocol AODV
NS2 version 2.34
Simulation results were obtained and compared. The results show a good improvement than the
exiting approach. The proposed protocol has performed well than the existing AODV protocol
which lacks in Qos parameters like PDR and delay when compared with the proposed
TBRAODV protocol. The results obtained are shown in Table 4, which shows the values
obtained using general AODV and proposed TBRAODV at different node sizes. The traditional
AODV is affected due to the existence of misbehaving nodes, which results in low packet
delivery ratio and also causes the delay to increase. The proposed protocol has shown improved
Qos parameters values where trust values are used to identify the misbehaving nodes in the
route and immediately take an alternate path to successfully complete the routing. This
approach of the proposed TBRAODV protocol has resulted in an increased packet delivery
ratio and a decreased delay involved in routing.
Table 4. Comparison of Result with node size
Node
Size
General AODV Proposed TBRAODV
PDR Delay Throughput PDR Delay Throughput
25 82.98 0.24615 75771.43 92.20 0.22153 75771.43
50 70.05 0.84972 114559.89 91.06 0.64979 114559.89
100 64.43 1.44347 148339.67 90.03 0.92683 148339.67
200 62.36 1.65589 150748.56 84.32 0.93536 150748.56
300 60.65 1.78687 150836.74 81.26 0.94825 150836.74

84
Figure 3 indicates how the proposed TBRAODV protocol has shown a good decrease in Delay
when compared to the general AODV. Figure 4 shows the increase in PDR when compared
with the general AODV.
Figure 3. Comparison of general AODV Delay and TBRAODV Delay
Figure 4 . Comparison of general AODV PDR and TBRAODV PDR

85
5 CONCLUSION AND FUTURE ENHANCEMENTS
In this paper, a trust based reliable protocol TBRAODV is proposed. Trust level values for each
node are calculated to identify the misbehaving nodes during routing. If node is misbehaving
then it leads to an alternate path selection for further reliable routing. This trust based routing
mechanism has proved to be increasing the performance of the proposed TBRAODV protocol
and also shows good improvement of Qos parameters like PDR and delay. Rather implementing
reliability with trust alone some energy constraints on each node along with trust schemes for a
node will provide better reliability for MANET routing. The same scheme can also be
implemented on other MANET routing protocols and also implement some techniques for
authenticating the packet and the node which take part in routing.
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