Rough set based QoS enabled multipath source routing in MANET

International Journal of Electrical and Computer Engineering (IJECE)
Vol. 10, No. 2, April 2020, pp. 1915~1923
ISSN: 2088-8708, DOI: 10.11591/ijece.v10i2.pp1915-1923  1915
Journal homepage: http://ijece.iaescore.com/index.php/IJECE
Rough set based QoS enabled multipath source routing
in MANET
Prathviraj N.1
, Santosh L. Deshpande2
1
Manipal School of Information Sciences, Manipal Academy of Higher Education, Manipal INDIA
2
Department of PG Studies Visvevaraya Technological University, Balagavi, INDIA
Article Info ABSTRACT
Article history:
Received Jul 6, 2019
Revised Oct 12, 2019
Accepted Oct 21, 2019
The single constrained Quality of Service (QoS) routing in Mobile Ad-hoc
NETwork (MANET) is disastrous in consideration of MANET
characteristics, inference, collision and link failure as it maintains a single
path. The QoS enabled routing yields better packet delivery and maintains
consistency among nodes in the network by incorporating multi-constrained
and multipath routing. The Dynamic Source Routing (DSR) is best suited
source routing algorithm to maintain multipath information at the source
node, but performance degrades with larger number of mobile nodes. Multi-
layer mechanism should be incorporated to maintain QoS metric information
spreads across multiple layers of TCP/IP protocol stack. The proposed
multipath QoS enabled source routing provides balanced routing by making
use of all these features. The imprecise decision making strategy called
Rough Set Theory (RST) is used at destination node for decision making.
The Route REQuest (RREQ) messages coming from different routes are
filtered by considering the QoS metrics of each and every route by making
use of RST. The Route REPly (RREP) messages are generated and delivered
to the source node for filtered RREQ messages. The proposed routing
algorithm will reduce load on the network by reducing number of control
messages exchanged for route establishment. This will evenly distribute load
among all the nodes and it also avoid the scenarios like few nodes starved for
resources. Finally, multipath routing always provides alternate routing option
in case of route failure.
Keywords:
Cross layer
Manet
Multipath
Quality of service
Rough set theory
Copyright © 2020 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Prathviraj N.,
Manipal School of Information Sciences,
Manipal Academy of Higher Education,
Manipal, India.
Email: praj151986@gmail.com
1. INTRODUCTION
The wireless medium and randomness feature of nodes makes Mobile Ad-hoc NET (MANET) work
in a different way compared to other wired and wireless networks. MANET is spread across indefinite
boundary and is open to interference from unwanted signals. MANET works without any centralized
communication system, here each and every mobile node communicates directly with Independent Basic
Service Set (IBSS) [1-2]. The IBSS works in a distributed manner by synchronizing all nodes to a common
clock without any infrastructure support. The routing uses deterministic approach for delivering the packets
effectively and routing algorithms used in these types of dynamic network should adapt quickly to
nondeterministic nature of the MANET. Many traditional ad-hoc routing protocols have been proposed till
now, such as DSR, Ad Hoc On-Demand Distance Vector (AODV), Temporally Ordered Routing Algorithm
(TORA) etc. MANETs practical implementation and use in the real world multimedia application demands
more than what traditional best effort protocols are able to deliver [3]. The multimedia application always

 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1915- 1923
1916
demands certain guaranteed delivery of information with respect to certain QoS metrics such as bandwidth,
delay, jitter, packet loss rate, hop count and path reliability [4]. Enabling QoS in routing should consider
multi-layer design methods [5], here input from physical, data link and network layer are integrated in order
to satisfy the needs of resource demanding applications.
The path reliability here in MANET depends on the link stability of each link from source to
destination because of varying mobility of the mobile nodes. Very frequent movement of mobile nodes with
different speed results in link breaks and network partition [6]. In both the cases the source node needs to
rediscover a path from source to destination. The rediscovery process increases the routing delay if
the network is very dense, which results in slow convergence thus reduces the throughput. The established
QoS routing depends on one or two fixed static QoS metrics; most of the time relay on hop count, delay and
bandwidth. Along with this QoS routing comes with additional overhead of disseminating QoS information
while routing [7]. This makes the selected best path runs out of QoS resources and leads to amplification of
issues with respect to MANET. The QoS provisioning is very important aspect in any novel routing
algorithm; in order to achieve this multi path, multi-layer and stability features should be incorporated.
The multipath aims to balance utilization of resources among the nodes. The available multiple paths
between source and destination will be add-on in consideration of dynamic nature of MANET [8]. The QoS
enabled routing requires collection of present scenario from the lower MAC and physical layers. The input
collected from lower layers will give the real time QoS requirement and it can be used for designing the QoS
enabled routing protocol. Routing the packets in consideration of stability of the path will give protection
from non-availability of the path. The stability of the path can be downsized to stability of link involved in
the path construction [9]. Here stability is dependent on parameters like signal strength, relative speed
between nodes, energy etc.
Multi path routing is about maintaining multiple paths between source and destination;
it will consider QoS aspects as well as dynamic and non-deterministic nature of MANET. So ultimately
multi-path routing overcomes problems with respect to single path routing but it comes with the overhead of
computing and maintaining more than one path. On-demand nature of source routing protocol overrides
the requirement of periodic exchange of route advertisement packet for neighbor detection present in
the other protocol [10, 11]. The DSR is a representative of on-demand routing protocols, where multiple
paths can be returned to the source nodes. The generally used standard single constrained QoS routing
algorithm makes an extra overhead compared to other best-effort routing algorithm, since extra information
being communicated to maintain QoS. These factors lead to a higher drain of resources on mobile nodes.
Numerous attempts have been made to optimize multi-constraint QoS routing with consideration of two or
more fixed QoS parameters. The limited applicability in terms of fixed QoS parameters in such methods
leads to performance degradation in other QoS aspects. The genetic algorithm enabled multi constrained QoS
routing [12] proposed to reserve resources required by collecting all nodes state information. Collecting and
maintaining the state information is an overhead in this methodology. Practically there is still space for
a novel multi-constrained QoS routing which incorporates multiple QoS parameters with minimum overhead.
A novel routing should balance and extend the lifetime of nodes in the network by balancing the load
among all nodes.
The Rough Set Theory (RST) is an excellent mathematical tool to build the decision model from
the large set of inconsistent data with multiple attributes [13, 14]. Extracting decision model in terms of rules
from inconsistent data is a crucial task without considering any additional information on data. This concept
can be considered as another approach to deal with vagueness and imprecise, unlike dealing only with precise
data set in fuzzy set theory. Suppose, QoS parameter of the different route is considered as a set of objects U
called universe and an equivalence relation R U×U. The proposed multipath QoS enabled source routing
overcomes the drawback identified in single constrained and multi constrained QoS routing. The decision
rules derived from RST are applied to limit the control message exchanged in route discovery process.
The decision rules are used to filter the RREQ message and RREP messages will be generated only for
selected RREQ messages. Since decision rules are framed considering all QoS aspects, selected routes will
be able to balance QoS resource in network. The rest of the research article spans across different sections.
Section 2 gives reflection on literature study. The proposed multipath QoS enabled source routing is
discussed under section 3. In section 4 experimental setup and results are discussed. Finally section 5
concludes the research article.
2. REFLECTION ON LITERATURE
The delay, energy, throughput, packet loss rate and jitter are the commonly used metrics by
MANET applications to specify QoS requirements to any routing protocol. In accordance with this, these are
frequently used as constraints on route discovery and selection [15]. Each and every QoS metric is identified

Int J Elec & Comp Eng ISSN: 2088-8708 
Rough set based QoS enabled multipath source routing in MANET (Prathviraj N.)
1917
by expected reference point, which will be considered as a constraint in QoS routing. For example Minimum
Required Throughput or Capacity (b/s), Maximum Tolerable Delay (s), Jitter, Maximum Tolerable Packet
Loss Ratio (PLR). The application running on MANET typically requires more than one of the above
mentioned QoS requirements.
The routing protocols adopted in MANET provide different routing strategy. Few routing protocols
considers QoS aspects in route discovery stage, few other routing protocols do not consider QoS [16].
Along with this some routing protocols are working with MAC layer and others are not. Based on these
prerequisites QoS protocols can be classified into three categories: first, reserving quantified resource and
availability of those resources in any network conditions, called as pseudo-hard QoS. TDMA is one of
the examples for such contention free MAC solution. Providing guaranteed QoS service in MANET scenario
is extremely hard. Second, reserving the resources and likely utilize lesser resources than reserved, called as
soft-QoS. These routing strategies are dependent on contended MAC protocol, so work on available
resources. Third, without reserving the resources attempting to forward route request message under
favorable scenarios, called as no QoS. These routing strategies are independent of MAC protocol and do not
promising any QoS guarantee. The aim of such protocols is to provide immediate delivery without promising
anything [17, 18]. The QoS routing protocols can be classified under different categories for the better
understanding of how these protocols are working to enable QoS in routing [19]. So the QoS protocols can be
classified under 3 different categories: first, based on the QoS approach incorporated in routing.
QoS approach again can be classified under two different categories. Coupled QoS approach, in which QoS
provisioning is closely associated with routing and any change in routing may fail to provision guaranteed
QoS. The decoupled QoS approach does not depend on any particular routing protocol. Second, QoS
provisioning can also be classified according to layer on which these protocols are provisioning QoS aspects.
The protocols working on MAC layer make use of random back off and channel sensing mechanism, these
protocols will be suitable for real time traffic expecting guaranteed bandwidth. Third, QoS provisioning is
not dependent on any routing algorithm or layers. This is considered as QoS framework for providing better
service in terms of packet delivery.
The deployment of QoS aspects in MANET routing focus only throughput and delay to some extent.
Even though throughput and delay are prominent QoS aspects to be considered, relying only on these leads to
compromise in other QoS parameter. The characteristics of MANET shift the focus from single constrained
QoS to multi-constrained QoS. The complexity involved in multi constrained makes QoS routing
NP-complete problem [20]. The QoS guarantee mechanism incorporates input from all layers of TCP/IP, here
every layer is responsible for corresponding QoS metric [21, 22]. The network layer is having the impact on
very critical QoS metric like multimedia QoS and network resources. The data link layer is responsible for
setting up the priorities for the business flow, to ensure compliance of end to end QoS and scheduling
the channel selection. The physical layer is responsible for controlling the throughput, error rate and sending
rate to achieve QoS requirement. The different business requirement demands different categories of QoS
requirement and these QoS requirements can be satisfied from different layers of the protocol stack [23, 24].
So, each layer of the protocol stack should be considered independently to meet the business requirement of
various QoS demanding application. The load balancing among all nodes in the MANET improves
performance of the node in all QoS aspects. Load balancing mitigates network congestion and increases
the overall network throughput. It also processes every packet and every flow for every destination
independently. The existing multi path routing protocols utilizes all available path to deliver packets to
the destination. Here load balancing is implemented [25] by sharing the load among all available paths.
3. QoS ENABLED MULTIPATH SOURCE ROUTING
QoS enabled multipath routing is intended for deriving multiple reliable routes from source to
destination with consideration of multiple QoS aspects. The proposed routing algorithm should consider
multiple QoS metric such as minimum bandwidth, balanced energy consumption, minimum end to end delay
and maximum packet delivery fraction. The availability of QoS metric related information is limited to
different layers of protocol stack. So, the proposed algorithm should perform the multi-layer mechanism to
collect QoS metric information from different layers. The mobile node participating MANET routing
maintains route cache, it keeps track of available active route information from that particular source node to
different destination. The mobile node initiating packet delivery has to first check in its route cache for
availability of active route information. If active route is not available then route discovery process is
initiated by the source node. The route discovery process works in two stages: route request and route reply.

 ISSN: 2088-8708
1918
The packet generated for route request message consists of different QoS metric information
collected from different layer in addition to regular route request (RREQ) message. The destination node
receives RREQ message from different route with varying QoS metric information. The rough set theory
decision rules are applied to filter the RREQ message and for the filtered RREQ message RREP message will
be generated. The RREP message delivered to the source node consists of route information to
the destination.
3.1. QoS enabled multipath
The multiple paths between source and destination will be discovered in the route discovery process
of DSR. These available multiple paths will be used if there is congestion on the path with first priority or if
the path is unavailable due to movement of nodes. So, multipath routing enhances the performance of packet
delivery by compensating the unpredictable nature of MANET. Benefits of multipath routing comes with
some drawbacks like computation overhead and extra routing table space to maintain multiple paths.
The flexible nature of on demand source routing makes it simpler to compute and maintain multiple paths.
This will lessen the overhead of multipath.
3.2. QoS enabled cross layer
The QoS guaranteed routing in ad-hoc network takes input from all the layers of TCP/IP protocol
stack, each and every layer contributing to collect input for QoS parameters. So, QoS enabled multipath
algorithm is a multi-layer design which incorporates input from all layer of the TCP/IP protocol stack.
The proposed algorithm collects QoS requirements from application layer, end-to-end throughput and latency
from transport layer, throughput from data link layer, bandwidth and energy from physical layer.
3.3. QoS Enabled route reliability
The path reliability is defined as the ability of the path to successfully deliver data packets to
the destination. Predicting the ability of path in dynamic scenario like MANET is difficult job. The ability of
the path is dependent on resources available on all intermediate nodes; accumulation of this information will
be the deciding factor for the reliability of the path. Here resources are nothing but QoS parameters, which
includes different classes of parameters like additive, comparative and multiplicative. In multi parameters
decision making significance of all the parameters has to be taken into consideration separately.
The significance of parameter is evaluating how much that parameter is important to successfully
transmit data. The significance of the particular QoS parameter is calculated by evaluating impact of negating
that QoS from routing information table. Let QoS and route be a set of condition and decision attributes.
Let energy be a condition attributes, i.e., energy QoS. The representation of degree of dependency of
condition with dependency is shown as . Difference in eliminating energy from condition leads
to lower the degree of dependency. This can be represented as follows:
{ } (1)
The difference will yield the significance of attribute energy and it is represented using .
QoS enabled route parameters
3.4. Bandwidth estimation
Make sure that channel used for packet forwarding is free and channel utilization is estimated by
the bandwidth. The availability of bandwidth information is from data link layer, multi-layer mechanism is
incorporated to fetch the bandwidth information. The available bandwidth at the time of arrival of RREQ
message is calculated by considering the consumed bandwidth from the raw bandwidth. The comparative
strategy is used to compute the bandwidth in the RREQ message traversal, whichever link is having low
bandwidth availability is stored in the RREQ.
3.5. Delay estimation
The delay involved in delivering the packet from source to destination is accumulation of a delay in
all intermediate nodes participating in the traversal of packets. Estimation of the delay is based on the round
trip time and queuing delay. The queuing delay is impacted by number of packets already arrived and waiting
in a buffer, i.e. load on the node. The round trip time is accumulation of processing delay and transmission
delay. The processing delay is time required to extract packet header information to get to know where to
direct the packet. The transmission delay is time required to transmit and to receive the packet. The additive
strategy of all such delays in the packet traversal is maintained in the packet header.

1919
3.6. Energy estimation
The significance of energy parameter in QoS routing very high, so energy estimation should be done
very carefully. The remaining energy should be considered out of initial energy after consuming the energy
for other packet traversal. The energy parameter of the arrival RREQ message is compared with remaining
energy of the node, whichever is low updated in the RREQ message. The nodes remaining energy is updated
by considering energy consumed for transmission and reception of the current packet traversal.
3.7. Route finding process
The node which intend to send the message, check for available route information in the route
cache. If routes are available sender will make use of the existing routes for message delivery. If no routes
are available sender makes an attempt to initiate route discovery process. In the route discovery process two
types of messages exchanged between source and destination: RREQ and RREP. Nodes in the MANET
prone to changes its position dynamically, restricts all routes to expiration time. The correction of routes
from the missing link will initiate route maintenance phase, here missing link will be identified and reported
back to the source node.
3.7.1. Route request
The RREQ packet consists of IPV4 address of source and destination node, unique route
identification number, route record to keep track of all intermediate nodes it passes through and for QoS
parameters. The intermediate node checks the incoming RREQ packets route identification and make sure
that same packet is not received through other nodes. If it has already received simply discard the packet,
otherwise compare the QoS parameters make the updation in RREQ.
3.7.2. Rough set theory
The routing problems in dynamic nature MANET identify the requirement of dynamically changing
QoS parameters in routing condition balance the trade-off between QoS parameter. The RSES is used to
analyse the values of QoS parameters with different techniques like data discretization, reduction, decision
rules and prediction. The significance of the particular attribute or condition values will be calculated based
on the impact of that attribute in the decision rules. The Rough Set Exploration System (RSES) is used for
data exploration, discretization, reduction and decision making. It is an open source tool helps in
understanding tabular data set generated from stack parameter configuration and makes decision with respect
to reason for variation in different QoS parameters. In order to ensure good decision has been made accuracy
and coverage of the decision will be displayed for all QoS parameters.
The discretization is the partition of set of values into subset based on the cuts fulfilling some
standard condition. Here partition is done to make sure that if subset falls under certain decision rule than all
QoS values that comes under particular subset will be in aligned with the respective decision rule.
The Figure 1 shows the discretization of values into multiple subsets based on the cut set from the original
decision table. The cut set will give the boundary for the partition. So the discretization will be helpful to take
the decision rule with respect to subset and for all the values of subset decision rule will be applied.
Figure 1. Transformation of original data set into discretized information

 ISSN: 2088-8708
1920
The decision rule table consists of set of rules which specifies the different QoS condition to be
considered before forwarding packet. The RSES will come up with set of decision rules as shown in Figure 2,
based on the discretized decision table and significance of the attribute. The coverage of the decision rule
should be all rows of the decision table. The impact of energy parameter on the decision rule is 0.5, based on
energy parameter decision can be taken on the decision attribute. The removal of energy leads to loss of 50%
consistency of decision rule. The impact of all other parameter like hops, goodput, delay, PER is 0.25 means
removal of other parameter leads to loss of 25% consistency of decision rule.
Figure 2. Rule set generated from RST
3.7.3. Route reply
The RREP packet is generated for RST filtered paths by the destination node, which will place all
relevant information in reply message. The RREP will take same path which will earlier used by RREQ,
since this route information is stored in the packet. Otherwise traversal of the RREP packet will takes place
by referring to cache of the intermediate node and this route information in the route record. Once source
node receives such RREP packet through different path, now source node knows how to communicate with
the destination.
3.7.4. Route Maintenance
Since source node receives multiple RREP messages and multiple paths are maintained, route
maintenance in the proposed algorithm is simpler. To get to know existing path is not available for message
transfer two types of feedback message is exchanged, i.e. Route Error (RERR) and Acknowledgment (ACK).
The existence of the path is confirmed to neighboring nodes by communicating ACK packet on delivery of
the packet to next hop. Whenever ACK packet is not received RERR packet is initiated and delivered to
the source node. Alternate path maintained by source node through multipath routing comes to help and new
packet is send through alternate path.
4. EXPERIMENTAL SET UP AND RESULT
The simulation environment developed with variable number of mobile nodes like 25, 30…75
within a 1000m×1000m area. Each mobile node has its own radio propagation range and these nodes are
placed with in their range. The 5 sec is set as pause time and mobility speed is established between 2 m/s to
12 m/s for these mobile nodes. To analyze the performance of MQSR over the DSR different application
level traffic and transport layer protocols were incorporated. The experimentation setup includes CBR and
FTP as application traffic, here CBR uses UDP and FTP uses TCP as transport layer protocol.
The experimental results are analyzed with respect to packet drop, delay and throughput for variable
number of mobile nodes. The Figure 3 depicts the packet drop variation for MQSR and DSR routing for
variable number of mobile nodes. The packet drop of DSR gradually increases with respect to number of
mobile nodes but MQSR controls the packet drop even with more number of nodes. The Figure 4 depicts
variation of delay in packet arrival with respect to MQSR and DSR for different size of network.

1921
The performance of DSR gradually degrading in terms of delivering packet on time as there is an increase in
number of nodes participating in the network. On the other hand MQSR steadily delivering the packet
without much delay even with more number of nodes. The Figure 5 represents the throughput variation with
respect to MQSR and DSR for variable number of mobile nodes. Like packet drop and delay throughput also
degrading as there is increase in number of nodes for DSR routing algorithm. On the other hand MQSR
shows not much drop in throughput with higher number of mobile nodes.
Figure 3. Packet drop variation Figure 4. Delay variation
Figure 5. Throughput variation
5. CONCLUSION
The proposed multipath QoS enabled source routing algorithm incorporates multipath and multi-
layer mechanism into DSR. The extended version of DSR enhances the performance of packet delivery by
taking into consideration of all QoS metric from different layers of protocol stack. The RST based route
filtering at the destination node and generation of the RREP message only for filtered route makes the
balanced usage of nodes over the network. It also overrides the drawback of DSR specifically with more
number of nodes. The performance of MQSR compared against DSR with respect to packet drop, delay and
throughput. The experimental results clearly shows better performance in MQSR against DSR especially in
larger networks.
REFERENCES
[1] Ashtiani H, Moradi H, Pour P, Nikpour, "A Survey of MANET Routing Protocols in Large-Scale and Ordinary
Networks," Global Journal of Computer Science and Technology, Vol. 10(13):39–46, 2010.
[2] Cho AM, Moe A A., "Energy efficient multipath routing for mobile ad hoc networks," International Journal of
Information Technology Modeling and Computing, Vol. 2(3):11–18, 2014.
[3] D. B. Johnson and D. A. Maltz, "Dynamic source routing in ad hoc wireless networks, in mobile computing,"
edited by Tomaz Imielinski and Hank Korth, Chapter 5, Kluwer academic publishers, pp. 153-181, 1996.

 ISSN: 2088-8708
1922
[4] Georgios Parissidis, "Multi-path Routing Protocols in Wireless Mobile Ad Hoc Networks”: A Quantitative
Comparison Springer-Verlag Berlin Heidelberg, 2009.
[5] A. M. Satyabrata Ch., “QoS Issues in Ad Hoc Wireless Networks,” IEEE Commun. Mag., pp. 142–148,
2001.
[6] Gizem, Aksahya & Ayese, Ozcan , “Multipath Routing with Load Balancing in Wireless Ad Hoc Networks”,
Coomunications & Networks, Network Books. ABC Publishers. ROMA I N G R O L EAU, 2009.
[7] Primo Skraba, Hamid Aghajan and Ahmad Bahai, “Cross-Layer Optimization for High Density Sensor Networks,”
USA: Springer Berlin / Heidelberg. Vol. 17, 2004.
[8] Pawlak Z., “Rough Sets,” International Journal of Computer and Information Sciences, vol. 11, no. 5,
pp. 341-356, 1982.
[9] Pradeep, B.S. and Soumya, S., “A new method for load balancing and QOS in on demand protocols – in the
MANET’s perspective,” International Journal of Advanced Networking and Applications, Vol. 1, No. 4,
pp.275–281, 2010.
[10] Prathviraj N and Santosh L Deshpande, “Rough Set Approach for Solving Mulit Constrained QoS Routing
Problems in MANET,” IEEE WISPNET , pp. 1193–1196, 2016.
[11] Prathviraj N, Santosh L Deshpande, “Rough Set-Based Analysis of Multilayer Stack Parameter on QoS of
MANET,” Lecture Notes on Data Engineering and Communications Technologies , vol. 28, pp. 217-229, 2019.
[12] S.-J. Lee, C.-K. Toh, and M. Gerla, “Performance Evaluation of TableDriven and On-Demand Ad Hoc Routing
Protocols,” in Proceedings of IEEE PIMRC’99, Osaka, Japan, pp. 297-301, 1999.
[13] S. R. Das, R. Castaneda and J. Yan, “Simulation Based Performance Evaluation of Mobile, Ad Hoc Network
Routing Protocols,” ACM/Baltzer Mobile Networks and Applications (MONET) Journal, pages 179-189, 2000.
[14] Suresh HN, Varaprasad G, Jayanthi G., “Designing energy routing protocol with power consumption optimization
in MANET,” IEEE Transactions on Emerging Topics in Computing. Vol. 2(2):192 –197, 2014.
[15] S.Venkatasubramanian and Dr.N.P.Gopalan, “A Quality of Service Architecture for Resource Provisioning and
Rate Control in Moblie Ad-hoc Network,” International Journal of Ad hoc, Sensor & Ubiquitous Computing
(IJASUC) Vol.1, No.3., 2010.
[16] Varshavsky, A. Reid, B. de Lara, “A cross-layer approach to service discovery and selection in MANETs,”
Canada: Mobile Adhoc and Sensor Systems Conference (IEEE), 2005.
[17] K. Jayabarathan, J., Avaninathan, S., Savarimuthu,R. “QoS enhancement in MANETs using priority aware
mechanism in DSR protocol,” J Wireless Com Network, 2016.
[18] R. Asokan, A. Natarajan, “Performance Evaluation of Energy and Delay Aware Quality of Service(QoS) Routing
Protocols in Mobile Adhoc Networks,” International Journal of Business Data Communications and Networking,
4 , pp. 52-63,2008.
[19] H Shen, L Zhao, “ALERT: an anonymous location based efficient routing protocol on MANETs,” IEEE Trans.
Mob. Comput. 12(6), 1079–1093, 2013.
[20] XM Zhang, Y Zhang, F Yan, A Vasilakos, “Interference-based topology control algorithm for delay-constrained
mobile ad hoc networks,” IEEE Trans. Mob. Comput. 14(4), 742–754, 2015.
[21] SS Chaudhari, RC Biradar, “Survey of bandwidth estimation techniques in communication networks,” Wirel. Pers.
Commun. 83(2), 1425–1476, 2015.
[22] S. Fu and Y. Zhang, “CRAWDAD data set due/packet-delivery (v. 201503-30),” http://crawdad.org/due/packet-
delivery/.
[23] S. Fu and Y. Zhang, “Experimental Study for Multi-layer Parameter Conﬁguration of WSN Links,” IEEE 35th
International Conference on Distributed Computing Systems, pp. 369-378, 2015.
[24] V.V Mandhare and R.C. Thool, “Improving Qos of Mobile Ad hoc Network using Cache update scheme in
Dynamic Source Routing protocol,” 7th international conference on communication, computing and virtualization,
Vol(79), pp.692-699. 2016.
[25] Yuh-Shyan Chen, Shin-Jr Jan and Ming-Chin Chuang, “A Shoelace-Based QoS Routing Protocol for Mobile Ad
Hoc Networks Using Directional Antenna,” Wireless Personal Communications, SpringerLink., 2009.
BIOGRAPHIES OF AUTHORS
Prathviraj N. received his B.E in Computer Science and Engineering and MTech in Software
Engineering from Visvesvaraya Technological University Belagavi, India, in 2009 and 2012
respectively. He is currently pursuing his PhD from Visvesvaraya Technological University
under the guidance of Dr Santosh Deshpande. His research interest includes ad-hoc networks,
wireless sensor networks, rough set theory. He is working as an Asst.Professor in Manipal
School of Information Science, Manipal Academy of Higher Education Manipal, India.

1923
Dr Santosh L. Deshpande, received his B.E in Electronics and Communication Engineering
from Shivaji University Kolhapur in 1996 and M.Tech in Computer Engineering from National
Institute of Technology Karnataka in 2005. He obtained his Ph.D from J NTU Hyderabad in
2011. His research interest includes ad-hoc network, network security and wireless sensor
network. Presently he is working as Professor and Head in Dept. of PG Studies VTU Belagavi,
India.

Rough set based QoS enabled multipath source routing in MANET

More Related Content

What's hot (20)

Similar to Rough set based QoS enabled multipath source routing in MANET (20)

More from IJECEIAES (20)

Recently uploaded (20)

Rough set based QoS enabled multipath source routing in MANET