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ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010




               A Cross-Layer Based Multipath Routing
              Protocol To Improve QoS In Mobile Adhoc
                             Networks
                                                              S.Venkatasubramanian1
                                      Asst.Professor/Department of computer science & Engineering,
                                                    Saranathan college of Engineering,
                                                Panjapur, Tiruchirapalli, India Pin: 620 012
                                                         veeyes@saranathan.ac.in

Abstract                                                                           of service (QoS). When the nodes communicate over
                                                                                   wireless links then all the nodes should fight against the
In Mobile ad hoc networks, due to the high packet loss rates                       unpredictable character of the wireless channels and
and frequent topological changes, the unbalanced transport                         intrusion from the additional transmitting nodes. Even if
layer and reserved amount of traffic is carried out by the
network. In a QoS based routing metric for MANETs, it is
                                                                                   the user-required QoS in wireless ad hoc networks is
necessary to combine the minimum available bandwidth and                           attained, these factors make it as a challenging problem to
end-to-end delay along with the congestion around a link. In                       use on the data throughput.
this paper, a cross layer based multipath routing (CBMR)
protocol to improve QoS in mobile ad hoc networks to allot                         Due to the mobility of the nodes, repeated route changes
weights to individual links, depending on the metrics link                         cause difficulty in implementing ad hoc networks. Due to
quality, channel quality and end-to-end delay is developed. In                     the high packet loss rates and regular topological changes,
order to validate load balancing and interference between the                      the transport layer is not balanced and the inhibited amount
links using the same channel, the individual link weights are                      of traffic is carried out by the network. The three famous
integrated into a routing metric. Therefore, the weight value
helps the routing protocol to avoid the routing traffic through
                                                                                   problems in ad hoc networks are: due to the intrusion and
the congested area hence the traffic is balanced and the                           movement of nodes, the reliability of the packet delivery is
network capacity is improved. Then the proportion of traffic                       not sufficient, incomplete bandwidth due to channel
to be routed to each neighbor is selected to execute routing                       limitations and the inhibited node life span caused as an
such that the weight of the node is a minimum. We also                             outcome of small battery size.
propose an enhanced TCP congestion control mechanism for
wireless networks, based on a cross-layer scheme. By our                           B. Problems of Adhoc Routing Protocols
simulation results, the robustness of our protocol achieves
increased packet delivery ratio with reduced latency was                           (i) An excellent scalable QoS architecture is required for
demonstrated.                                                                      the huge dimension of ad hoc networks. An ad hoc
                                                                                   network may not want to (or be able) to limit the number
Index Terms: CBMR,QoS,Congestion,MANET
                                                                                   of hosts concerned in the network. The potential for the
                                                                                   collisions and contention increases when several nodes
                            I .Introduction                                        join as ad hoc network or the data traffic increases and due
                                                                                   to this the protocols face the challenging task to route data
A. Quality of Service (QoS) in MANET                                               packets and results in scalability. The scalability problems
                                                                                   have been considered in the QoS in ad hoc networks in the
Ad hoc wireless network is a special case of wireless                              previous works.
network which consists of backbone infrastructure which
is determined before. This can be made flexible and                                 (ii) By the Network Interface Queues (IFQ) which are
organized quickly by using the features of the wireless ad                         implemented by AODV [1], TORA [2] and DSR [3], the
hoc networks. However, using this property important                               packets which are ready to be transmitted are buffered.
technological challenges are also created. There are many                          These packets are received by the network protocol stack.
challenges including the issues of efficient routing,                              Generally, the maximum numbers of packets which are
medium access, power management, security and quality                              present in the IFQ are limited. In addition to this, a
1
  The Author is an part-time research scholar in the area of wireless adhoc        maximum timeout policy for packets in the IFQ is
networks at Anna University,Trichy,India and can be reached at                     implemented by the IFQ. Therefore any packet in
919443144356
                                                                                   expectation of a route in the IFQ for a huge period may be
                                                                                   discarded without any notification [4]. Hou and Tipper [5]


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    © 2010 ACEEE
    DOI: 01.ijns.01.01.09
ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010


have stated that the edge over of the IFQ of congested
nodes is one of the key motives for the rejection in                 The remainder of the paper is organized as follows. In
throughput for congested networks running DSR.                       Section II some of the existing work in this area is
                                                                     reviewed. The system design and overview are presented
(iii) The existing routing protocols faced a problem, called         in the Section III. Section IV presents the details of
      the communication Gray Zone problem, which is a                estimating the QoS based routing metrics. Section V
      major challenge [4]. Based on the control (RREQ)               describes our proposed QoS based robust multipath routing
      packets, the detection and establishments of end to            protocol in detail. The experimental results are presented
      end routes are carried out in most of the routing              in Section VI.
      protocols like AODV. However, these control packets
      and data packets have different properties. For
      example, when RREQ packets are compared with the                                 II. RELATED WORK
      data packets, it shows that RREQ packets are smaller
      and are transmitted at lower bit rates. The                    Andre Schumacher, et. al. (2006), have approached the
      bidirectional RREQ packets can be transmitted or               problem of load balancing for wireless multihop networks
      received by the nodes which are at the distance. On            by distributed optimization using an approximation
      the other hand, as a result of the above mentioned             algorithm for minimizing the maximum network
      property, the high bit-rate data packets cannot be sent        congestion and implement it as a modification of the DSR
      or received. Due to the resultant “fragile” link which         routing protocol. The algorithm was based on shortest-path
      triggers link repairs, high control overhead for               computations that are integrated into the DSR route
      protocols like AODV is obtained.                               discovery and maintenance process. Therefore, it does not
                                                                     rely on the dissemination of global information within the
(iv) The essential element of any QoS-enabled routing                entire network [7].Kaixin Xu, et. al., (2003) have proposed
     protocol is the end-to-end delay estimation. In order to        a Scalable QoS architecture suitable for large scale mobile
     calculate the end-to-end delay, the existing protocols          ad hoc networks with the help of the scalable LANMAR
     establish the time taken to route RREQ and RREP                 routing protocol. They have also introduced the mobile
     packets along the specified path. However, RREQ and             backbone network structure to enhance the network
     RREP packets are impossible to meet the similar                 performance [8].Jianbo Xue, et. al., (2003) have proposed
     levels of traffic delay and loss like data packets which        a QoS framework for MANETs Adaptive Reservation and
     are considerably different from usual packets.                  Pre-allocation Protocol (ASAP). By using two signaling
                                                                     messages, ASAP provides fast and efficient QoS support
In order to monitor the movement of the node and that a              while maintaining adaptation flexibility and minimizing
route is about to break, the communication is based on the           wasted reservations [9].
received power of the forwarding node. Therefore, the
quality of the route is measured. Based on the measured              Jangeun Jun and Mihail L. Sichitiu, (2003) have exposed a
quality of the route, the link breakage can be assumed. A            significant fairness problem existent practically in all
smaller end-to-end delay and a larger throughput to a host           wireless multihop networks. They showed that a network
can be obtained by using a proactive fault tolerant routing          layer solution can restore fairness at the expense of
with QoS aware multipath route discovery.                            bandwidth efficiency[10].Michael Gerharz, et. al., (2003)
                                                                     have have outlined that it is a very complex task to reserve
In this paper, a cross layer based multipath routing                 or even measure available bandwidth in wireless multihop
(CBMR) protocol to improve QOS in mobile ad hoc                      networks. They have introduced and evaluated the DLite
networks intended for mobile ad hoc networks has been                algorithm, an approach to service differentiation in ad hoc
developed. In this paper, the facility to determine multiple         networks. It applies a fair queuing scheme with separate
routes to a host and switch between them to expand the               queues for each service class. Late packets of delay
definition of AOMDV [6] has been employed. Enabling a                constrained classes were dropped in intermediate routers.
QoS constrained route from source to destination is one of           [11].
the objectives of the routing protocol. The route chosen by
the protocol must send packets with minimum bandwidth                Duc A. Tran and Harish Raghavendra, (2006) have
and end-to-end latency, in particular. The protocol should           proposed CRP [12], a congestion-adaptive routing protocol
satisfy the above constraints and also select the most               for MANETs. CRP tried to prevent congestion from
robust among all possible candidate routes.Different from            occurring in the first place, rather than dealing with it
wired networks, TCP over wireless networks needs to be               reactively. Xiaoqin Chen et al.,(2007) [13] have proposed
cross-layer designed which depends on information of                 a congestion- aware routing protocol for mobile ad hoc
MAC. However, it is difficult to apply existing cross-layer          networks which uses a metric incorporating data-rate,
design into hybrid networks. In this paper, we have also             MAC overhead, and buffer delay to combat congestion.
proposed an enhanced TCP congestion control mechanism
for wireless networks, based on a cross-layer scheme.

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© 2010 ACEEE
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ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010


Ming Yu et al.,(2007) [14] have proposed a link                     routing traffic through congested area. Subsequently, the
availability-based QoS-aware (LABQ) routing protocol for            selection of the proportion of traffic to be routed to each
mobile ad hoc networks based on mobility prediction and             neighbor is made to perform routing such that the weight
link quality measurement, in addition to energy                     of the node is a possible minimum.
consumption estimate..Hongxia Sun et al [15], proposed an
adaptive QoS routing scheme which is supported by cross-
layer cooperation in ad hoc networks. By considering the             IV. ESTIMATING QOS-BASED ROUTING METRICS
influence of node mobility and lower-layer link
performance, the cross-layer mechanism provides up-to-              A. Estimating Link Quality
date local QoS information for the adaptive routing
                                                                    Each node in the network estimates its quality of links with
algorithm. Based on the current network status, the
                                                                    its one-hop neighbors. If Nq is the number of HELLO
multiple QoS requirements are satisfied by adaptively
                                                                    packets received during a time window Twin and Pq is the
using forward error correction and multipath routing
                                                                    percentage of HELLO packets received in the last r
mechanisms. Al-khwildi et al [16], have proposed a novel
                                                                    seconds, then the link quality Lq is measured as
routing technique called Adaptive Link-Weight (ALW)
routing protocol which selects an optimum route on the
                                                                             Lq = δ. Pq + (1 – δ) . Nq                    (1)
basis of available bandwidth, low delay and long route
lifetime. Those technique adapts a cross-layer framework
                                                                    The estimated link quality is maintained by each node in
where the ALW is included with application and physical
                                                                    its NT. The average link quality of all the links across the
layer.
                                                                    path P, gives the route quality Rq of the path. RREQ
                                                                    packets of the reverse path and RREP packets of the
 III. SYSTEM DESIGN AND PROTOCOL OVERVIEW                           forward path accumulate the estimated Lq values.The
                                                                    value δ is application specific.
We devise the model by considering a mobile ad hoc
network in which each node utilizes IEEE 802.11 DCF for             B. Estimating End to End Delay
medium access control (MAC). At the application layer,
intra-flow interference occurs for the same flow which is           There is a significant variation between the end-to-end
transmitted on different wireless links. But it has been            delay reported by RREQ-RREP measurements and the
presumed as a single data flow.                                     delay experienced by actual data packets. We address this
A QOS based multipath routing protocol intended for                 issue by introducing a DUMMY-RREP phase during route
mobile ad hoc networks is put forwarded. In this paper, we          discovery. The source saves the RREP packets it receives
employed the facility to determine multiple routes to a host        in a RREP TABLE and then acquires the RREP for a route
and switch between them to expand the definition of                 from this table to send a stream of DUMMY data packets
AOMDV [6].Enabling a QoS constrained route from                     along the path traversed by this RREP. DUMMY packets
source to destination is the objective of the routing               efficiently imitate real data packets on a particular path
protocol. The route chosen by the protocol must send                owing to the same size, priority and data rate as real data
packets with minimum bandwidth and end-to-end latency,              packets. H is the hop count reported by the RREP. The
without facing congestion. The protocol should satisfy the          number of packets comprised in every stream is 2H. The
above constraints and also select the most robust among all         destination computes the average delay Davg of all
possible candidate routes.                                          DUMMY packets received, which is sent through a RREP
                                                                    to the source. The source selects this route and sends data
A QoS-based routing metric for MANETs should                        packets only when the average delay reported by this
incorporate minimum available bandwidth and end-to-end              RREP is inside the bound requested by the application.
latency along with congestion around a link. Congestion is          The source performs a linear back-off and sends the
related to channel quality, which depends on the MAC                DUMMY stream on a different route selected from its
access contention and channel reliability. So our algorithm         RREP TABLE when the delay exceeds the required limit.
should rely on the following metrics to allocate weights to
                                                                    C. Estimating Channel Quality
individual links.
     • End-to-End Delay                                             The channel quality can be represented by both the channel
     • Channel Quality                                              occupancy and channel reliability.
     • Link Quality
                                                                    C.1. Channel Occupation
The individual link weights are combined into a routing             In this network, we consider IEEE 802.11 MAC with the
metric to validate the load balancing and interference              distributed coordination function (DCF). It has the packet
between links using the same channel. Consequently, the             sequence as request-to-send (RTS), clear-to-send (CTS),
traffic is balanced and the network capacity is improved as         data and acknowledgement (ACK). The amount of time
the weight value assists the routing protocol to evade              between the receipt of one packet and the transmission of

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© 2010 ACEEE
DOI: 01.ijns.01.01.09
ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010


the next is called a short inter frame space (SIFS). Then             SSRC with an initial value of 0, when it transmits the RTS
the channel occupation due to MAC contention will be                  frame successfully. By this way, when a node starts to
                                                                      transmit a new RTS frame, SSRC will be the initial value
       Cocc = tRTS + tCTS + 3tSIFS + tacc            (2)              of 0, in spite of the initial RTS which was transmitted
                                                                      successfully or discarded. Obviously, the node would not
Where tRTS and tCTS are the time consumed on RTS and                  know the RTS retry count of the last frame for its resetting
CTS, respectively and tSIFS is the SIFS period. tacc is the           which results that its channel state cannot be known.
time taken due to access contention. The channel
occupation is mainly dependent upon the medium access                 To solve this problem, the value of SSRC is recorded when
contention, and the number of packet collisions. That is,             each RTS frame is retransmitted. The packet to be
Cocc is strongly related to the congestion around a given             transmitted will be marked as “1” in its congestion
node. Cocc can become relatively large if congestion is               experience bit when it exceeds the given the threshold “2”,
incurred and not controlled, and it can dramatically                  which shows an imminent congestion in ECN mechanism.
decrease the capacity of a congested link.

Therefore, in the design of a congestion-aware metric for               VI. QOS BASED ROBUST MULTIPATH ROUTING
networks, the access contention should be considered to                                 PROTOCOL
more accurately indicate channel capacity.
                                                                      For establishing multiple disjoint paths, we adapt the idea
C.2. Channel Reliability                                              from the Adhoc On-Demand Multipath Distance Vector
The channel reliability also affects the packet transmission          Routing (AOMDV) [6]. The multiple paths are computed
in MANETs and factors such as interference and fading in              during the route discovery.
the channel may lead to occurrence of packet losses. In
802.11 DCF, several failed retransmissions lead to packets            We now introduce the weight metric W which assigns a
being dropped. In addition to performance deterioration               cost to each link in the network. The weight W combines
due to congestion with respect to packet losses, higher               the link quality Lq , channel quality Cocc and the average
packet retransmissions involved owing to augmented                    delay Davg , to select maximum throughput paths, avoiding
packet losses lead to more congestion. A successful                   the most congested links.For an intermediate node i with
transmission of a packet on an unreliable links would                 established transmission with several of its neighbours, the
consume more time on MAC overhead.                                    W for the link from node i to a particular neighboring node
                                                                      is given by
          V. CROSS-LAYER DESIGN OF TCP                                         W = Lq + Cocc + Davg                      (3)

                                                                      A. Route Request
Currently, the main method of congestion control over
wired network is an optimization framework based on                   During the route discovery phase of the protocol, each
utility functions Moreover this method is not applicable              intermediate node uses an admission control scheme to
to the wireless networks. This is because due to the                  check whether the flow can be accepted or not. If accepted,
immanent interference of wireless links the metrics like              a Flow Table (FT) entry for that particular flow is created.
queue length on routers, sending rate of links cannot                 The FT contains the fields Source (Src), Destination (Dst),
characterize the congestion price.                                    Reserved Bandwidth (BWres), Minimum bandwidth
In this paper, according to the RTS retry counts, the ECN             (BWmin). Each node collects the bandwidth reserved at its
scheme will mark packets. IEEE 802.11 is the standard                 one hop neighbors (piggybacked on periodic HELLO
protocol for wireless adhoc networks. It provides two                 packets) and stores it in its Neighbor Table (NT) .The
options for accessing namely the basic scheme and                     Neighbor Table contains fields Destination (Dst), Reserved
RTS/CTS scheme. In this paper only this RTS/CTS                       Bandwidth (BWres), No. of Hello Packets (No Hello).
scheme is considered because it is used more in ad hoc
networks than the basic scheme. But our design can also be            Consider the scenario
applied to the basic scheme.
                                                                      Let us consider the route
In RTS/CTS scheme, in order to record the retransmit
count of RTS frame in the current node, each node                              S -- R1 – R2 – R3 – D
maintains a variable SSRC. When a node fails to transmit
RTS frame, then it will retransmit this RTS frame and                 To initiate QoS-aware routing discovery, the source host S
increases SSRC by 1 at the same time. The sender will                 sends a RREQ. When the intermediate host R1 receives
report a link failure notification to the network layer if the        the RREQ packet, it first estimates all the metrics as
value of the SSRC reaches 7 and discards the RTS frame                described in the previous section.
and the data frame to be transmitted together and resets
SSRC to an initial value of 0. Also the node refreshes the

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© 2010 ACEEE
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The host R1 then calculates its weight WR1 using (3).                               Table1: Simulation Parameters


                     WR1
                                                                        No. of Nodes                25,50,75 and 100
         RREQR1 ====== R2                                               Area Size                   1000 X 1000
R2 then calculates its weight WR2 in the same way and                   Mac                         802.11
adds it to the weight of R1. R2 then forward the RREQ                   Radio Range                 250m
packet with this added weight.                                          Simulation Time             100 sec
                                                                        Traffic Source              CBR
                                                                        Packet Size                 512
                      WR1+ WR2                                          Mobility Model              Random Way Point
         RREQR2 ============= R3                                        Speed                       5m/s to 20m/s
Finally the RREQ reaches the destination node D with the                Pause time                  5s
sum of node weights
                                                                  B. Performance Metrics
                    WR1+ WR2 + WR3
        RREQR3    ================          D                     We compare our CBMR protocol with the AOMDV [6],
                                                                  CARM [13] and LABQ [14] protocol. We evaluate mainly
B. Route Reply                                                    the performance according to the following metrics, by
                                                                  varying the nodes as 25, 50, 75 and 100.
The Destination node D send the route reply packet RREP
along with the total node weight to the immediate                 Control overhead: The control overhead is defined as the
upstream node R3 .                                                total number of routing control packets normalized by the
                                                                  total number of received data packets.
                 WR1+ WR2 + WR3
         RREP ================            R3                      Average end-to-end delay: The end-to-end-delay is
                                                                  averaged over all surviving data packets from the sources
Now R3 calculates its cost C based on the information             to the destinations.
from RREP as
                                                                  Average Packet Delivery Ratio: It is the ratio of the No.
CR3 = (WR1+ WR2 +WR3) - (WR1+ WR2)                (4)             of packets received successfully and the total no. of
                                                                  packets sent
By proceeding in the same way, all the intermediate hosts
calculate its cost.                                               C. Results

On receiving the RREP from all the routes, the source             C.1. Varying No. Of Nodes
selects the route with minimum cost value.
                                                                  In the first experiment, the performance of the protocols is
The simulation results in the next section showed that            measured by varying the no. of nodes as 25, 50, 75 and
these calculations did not increase the overhead                  100. From Figure 1, we can see that the packet delivery
significantly.                                                    ratio for CBMR increases, when compared to AOMDV,
                                                                  CARM and LABQ, since it utilizes robust links.

             VII. SIMULATION RESULTS                              From Figure 2, it is evident that the average end-to-end
                                                                  delay of the proposed CBMR protocol is less when
A. Simulation Model and Parameters                                compared to the AOMDV, CARM and LABQ protocol.
NS2 simulator is used to simulate our proposed protocol.          Figure 3 shows that the control overhead of the protocols.
In our simulation, the channel capacity of mobile hosts is        Since CBMR make use of HELLO packets for cost
set to the same value: 2 Mbps. We use the distributed             estimation, the values are considerably less in CBMR
coordination function (DCF) of IEEE 802.11 for wireless           when compared with AOMDV, CARM and LABQ.
LANs as the MAC layer protocol. It has the functionality
to notify the network layer about link breakage.

In our simulation, each node moves independently with the
same average speed is assumed. The simulated traffic is
Constant Bit Rate (CBR). Our simulation settings and
parameters are summarized in table 1




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                                   Packet Delivery Ratio                                                       Packet Delivery Ratio

                    100                                                                            120
                                                                                                   100                                         CBMR
                     80                                         CBMR
                                                                                                    80




                                                                                      ratio(%)
        ratio(% )


                                                                                                                                               AOMDV
                     60                                         AOMDV                               60
                                                                                                                                               CARM
                     40                                         CARM                                40
                                                                                                    20                                         LABQ
                     20                                         LABQ
                                                                                                     0
                          0                                                                              250        500          750   1000
                              25       50       75       100
                                                                                                                          Rate
                                            Nodes


                                                                                                               Fig.4: Rate Vs Delivery Ratio
                               Fig 1: Nodes Vs Delivery Ratio
                                                                                 From Figure 5, we can see that the average end-to-end
                                       End-to-End Delay
                                                                                 delay of the proposed CBMR protocol is less when
                                                                                 compared to AOMDV, CARM and LABQ.
                    0.8
                                                                                 Figure 6 shows the control overhead of the protocols.
                    0.6                                         CBMR             Since CBMR make use of HELLO packets for cost
       Delay(s)




                    0.4
                                                                AOMDV            estimation, the values are considerably less in CBMR
                                                                CARM             when compared with AOMDV, CARM and LABQ.
                    0.2                                         LABQ

                     0
                              25       50           75   100
                                            Nodes                                                                   End-to-End Delay


                                                                                                   0.6
                                    Fig. 2: Nodes Vs Delay                                         0.5                                         CBMR
                                                                                                   0.4
                                                                                        Delay(s)




                                                                                                                                               AOMDV
                                                                                                   0.3
                                     Control Overhead                                                                                          CARM
                                                                                                   0.2
                                                                                                   0.1                                         LABQ

                    1.2                                                                              0
                      1                                         CBMR                                     250        500          750   1000
                    0.8                                         AOMDV                                                     Rate
       ratio




                    0.6
                    0.4                                         CARM
                    0.2                                         LABQ
                      0                                                                                           Fig. 5: Rate Vs Delay
                              25       50       75       100
                                         Nodes                                                                    Control Overhead

                                                                                                   1.2
                                                                                                    1
                                   Fig. 3: Nodes Vs Overhead                                                                                   CBMR
                                                                                                   0.8
                                                                                      ratio(%)




                                                                                                                                               AOMDV
                                                                                                   0.6
B. Varying the Transmission Rate                                                                   0.4
                                                                                                                                               CARM
In the second experiment, we measure the performance of                                            0.2
                                                                                                                                               LABQ
the protocols by varying the transmission rate as                                                   0
250,500,750 and 1000 Kb.                                                                                 250        500          750   1000
                                                                                                                          Rate
From Figure 4, we can see that the packet delivery ratio for
CBMR is more, when compared to AOMDV, CARM and
LABQ since it utilizes robust links.                                                                             Fig 6: Rate Vs Overhead




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© 2010 ACEEE
DOI: 01.ijns.01.01.09
ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010


                      CONCLUSION                                           Communications, vol. 2, pp: 1018- 1023, 13- 16 October
                                                                           2003, Doi: 10.1109/MILCOM.2003.1290305.
In a QoS based routing metric for MANETs, it is necessary             [9] Jianbo Xue, Patrick Stuedi and Gustavo Alonso, "ASAP: An
to combine the minimum available bandwidth and end-to-                     Adaptive QoS Protocol for Mobile Ad Hoc Networks",
end delay along with the congestion around a link. MAC                     IEEE Proceedings on Personal, Indoor and Mobile Radio
                                                                           Communications, vol. 3, pp: 2616- 2620, 7- 10 September
access contention and channel reliability induces
                                                                           2003, Doi: 10.1109/PIMRC.2003.1259201.
congestion that is related to channel quality. In this paper          [10] Jangeun Jun and Mihail L. Sichitiu, "Fairness and QoS in
we have developed a cross layer based multipath routing                    Multihop Wireless Networks", in proceedings of 58th IEEE
(CBMR) protocol to improve QoS in mobile ad hoc                            Conference on Vehicular Technology, vol. 5, pp: 2936-
networks to allot weights to individual links, depending on                2940,       6-       9      October        2003,     Doi:
the metrics link quality, channel quality and end-to-end                   10.1109/VETECF.2003.1286161.
delay. The weight value helps the routing protocol to avoid           [11] Michael Gerharz, Christian de Waal, Matthias Frank and
the routing traffic through the congested area and hence                   Paul James, "A Practical View on Quality-of-Service
the traffic is balanced and the network capacity is                        Support in Wireless Ad Hoc Networks", Proc. of the 3rd
                                                                           IEEE Workshop on Applications and Services in Wireless
improved. Then the proportion of traffic to be routed to
                                                                           Networks (ASWN), pp: 185-196, Berne, Switzerland, July
each neighbor is selected to execute routing such that the                 2003.
weight of the node is a minimum. We have also proposed an             [12] Duc A. Tran and Harish Raghavendra, "Congestion
enhanced TCP congestion control mechanism for wireless                     Adaptive Routing in Mobile Ad Hoc Networks", IEEE
networks, based on a cross-layer scheme. By simulation                     Transactions on Parallel and Distributed Systems, Vol. 17,
results, we have demonstrated that the robustness of our                   no. 11, November 2006.
protocol achieves increased packet delivery ratio with                [13] Xiaoqin Chen, Haley M. Jones, A .D .S. Jayalath,
reduced latency. The security challenges of our proposed                   "Congestion-Aware Routing Protocol for Mobile Ad Hoc
protocol will be the subject of our future work.                           Networks", in proceedings of 6th IEEE Conference on
                                                                           Vehicular Technology, pp: 21- 25, 30 September- 3 October,
                                                                           Baltimore, 2007, Doi: 10.1109/VETECF.2007.21.
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                                                                           link availability-based QoS-aware routing protocol for
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                                                                 48
© 2010 ACEEE
DOI: 01.ijns.01.01.09

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A Cross-Layer Based Multipath Routing Protocol To Improve QoS In Mobile Adhoc Networks

  • 1. ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010 A Cross-Layer Based Multipath Routing Protocol To Improve QoS In Mobile Adhoc Networks S.Venkatasubramanian1 Asst.Professor/Department of computer science & Engineering, Saranathan college of Engineering, Panjapur, Tiruchirapalli, India Pin: 620 012 veeyes@saranathan.ac.in Abstract of service (QoS). When the nodes communicate over wireless links then all the nodes should fight against the In Mobile ad hoc networks, due to the high packet loss rates unpredictable character of the wireless channels and and frequent topological changes, the unbalanced transport intrusion from the additional transmitting nodes. Even if layer and reserved amount of traffic is carried out by the network. In a QoS based routing metric for MANETs, it is the user-required QoS in wireless ad hoc networks is necessary to combine the minimum available bandwidth and attained, these factors make it as a challenging problem to end-to-end delay along with the congestion around a link. In use on the data throughput. this paper, a cross layer based multipath routing (CBMR) protocol to improve QoS in mobile ad hoc networks to allot Due to the mobility of the nodes, repeated route changes weights to individual links, depending on the metrics link cause difficulty in implementing ad hoc networks. Due to quality, channel quality and end-to-end delay is developed. In the high packet loss rates and regular topological changes, order to validate load balancing and interference between the the transport layer is not balanced and the inhibited amount links using the same channel, the individual link weights are of traffic is carried out by the network. The three famous integrated into a routing metric. Therefore, the weight value helps the routing protocol to avoid the routing traffic through problems in ad hoc networks are: due to the intrusion and the congested area hence the traffic is balanced and the movement of nodes, the reliability of the packet delivery is network capacity is improved. Then the proportion of traffic not sufficient, incomplete bandwidth due to channel to be routed to each neighbor is selected to execute routing limitations and the inhibited node life span caused as an such that the weight of the node is a minimum. We also outcome of small battery size. propose an enhanced TCP congestion control mechanism for wireless networks, based on a cross-layer scheme. By our B. Problems of Adhoc Routing Protocols simulation results, the robustness of our protocol achieves increased packet delivery ratio with reduced latency was (i) An excellent scalable QoS architecture is required for demonstrated. the huge dimension of ad hoc networks. An ad hoc network may not want to (or be able) to limit the number Index Terms: CBMR,QoS,Congestion,MANET of hosts concerned in the network. The potential for the collisions and contention increases when several nodes I .Introduction join as ad hoc network or the data traffic increases and due to this the protocols face the challenging task to route data A. Quality of Service (QoS) in MANET packets and results in scalability. The scalability problems have been considered in the QoS in ad hoc networks in the Ad hoc wireless network is a special case of wireless previous works. network which consists of backbone infrastructure which is determined before. This can be made flexible and (ii) By the Network Interface Queues (IFQ) which are organized quickly by using the features of the wireless ad implemented by AODV [1], TORA [2] and DSR [3], the hoc networks. However, using this property important packets which are ready to be transmitted are buffered. technological challenges are also created. There are many These packets are received by the network protocol stack. challenges including the issues of efficient routing, Generally, the maximum numbers of packets which are medium access, power management, security and quality present in the IFQ are limited. In addition to this, a 1 The Author is an part-time research scholar in the area of wireless adhoc maximum timeout policy for packets in the IFQ is networks at Anna University,Trichy,India and can be reached at implemented by the IFQ. Therefore any packet in 919443144356 expectation of a route in the IFQ for a huge period may be discarded without any notification [4]. Hou and Tipper [5] 42 © 2010 ACEEE DOI: 01.ijns.01.01.09
  • 2. ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010 have stated that the edge over of the IFQ of congested nodes is one of the key motives for the rejection in The remainder of the paper is organized as follows. In throughput for congested networks running DSR. Section II some of the existing work in this area is reviewed. The system design and overview are presented (iii) The existing routing protocols faced a problem, called in the Section III. Section IV presents the details of the communication Gray Zone problem, which is a estimating the QoS based routing metrics. Section V major challenge [4]. Based on the control (RREQ) describes our proposed QoS based robust multipath routing packets, the detection and establishments of end to protocol in detail. The experimental results are presented end routes are carried out in most of the routing in Section VI. protocols like AODV. However, these control packets and data packets have different properties. For example, when RREQ packets are compared with the II. RELATED WORK data packets, it shows that RREQ packets are smaller and are transmitted at lower bit rates. The Andre Schumacher, et. al. (2006), have approached the bidirectional RREQ packets can be transmitted or problem of load balancing for wireless multihop networks received by the nodes which are at the distance. On by distributed optimization using an approximation the other hand, as a result of the above mentioned algorithm for minimizing the maximum network property, the high bit-rate data packets cannot be sent congestion and implement it as a modification of the DSR or received. Due to the resultant “fragile” link which routing protocol. The algorithm was based on shortest-path triggers link repairs, high control overhead for computations that are integrated into the DSR route protocols like AODV is obtained. discovery and maintenance process. Therefore, it does not rely on the dissemination of global information within the (iv) The essential element of any QoS-enabled routing entire network [7].Kaixin Xu, et. al., (2003) have proposed protocol is the end-to-end delay estimation. In order to a Scalable QoS architecture suitable for large scale mobile calculate the end-to-end delay, the existing protocols ad hoc networks with the help of the scalable LANMAR establish the time taken to route RREQ and RREP routing protocol. They have also introduced the mobile packets along the specified path. However, RREQ and backbone network structure to enhance the network RREP packets are impossible to meet the similar performance [8].Jianbo Xue, et. al., (2003) have proposed levels of traffic delay and loss like data packets which a QoS framework for MANETs Adaptive Reservation and are considerably different from usual packets. Pre-allocation Protocol (ASAP). By using two signaling messages, ASAP provides fast and efficient QoS support In order to monitor the movement of the node and that a while maintaining adaptation flexibility and minimizing route is about to break, the communication is based on the wasted reservations [9]. received power of the forwarding node. Therefore, the quality of the route is measured. Based on the measured Jangeun Jun and Mihail L. Sichitiu, (2003) have exposed a quality of the route, the link breakage can be assumed. A significant fairness problem existent practically in all smaller end-to-end delay and a larger throughput to a host wireless multihop networks. They showed that a network can be obtained by using a proactive fault tolerant routing layer solution can restore fairness at the expense of with QoS aware multipath route discovery. bandwidth efficiency[10].Michael Gerharz, et. al., (2003) have have outlined that it is a very complex task to reserve In this paper, a cross layer based multipath routing or even measure available bandwidth in wireless multihop (CBMR) protocol to improve QOS in mobile ad hoc networks. They have introduced and evaluated the DLite networks intended for mobile ad hoc networks has been algorithm, an approach to service differentiation in ad hoc developed. In this paper, the facility to determine multiple networks. It applies a fair queuing scheme with separate routes to a host and switch between them to expand the queues for each service class. Late packets of delay definition of AOMDV [6] has been employed. Enabling a constrained classes were dropped in intermediate routers. QoS constrained route from source to destination is one of [11]. the objectives of the routing protocol. The route chosen by the protocol must send packets with minimum bandwidth Duc A. Tran and Harish Raghavendra, (2006) have and end-to-end latency, in particular. The protocol should proposed CRP [12], a congestion-adaptive routing protocol satisfy the above constraints and also select the most for MANETs. CRP tried to prevent congestion from robust among all possible candidate routes.Different from occurring in the first place, rather than dealing with it wired networks, TCP over wireless networks needs to be reactively. Xiaoqin Chen et al.,(2007) [13] have proposed cross-layer designed which depends on information of a congestion- aware routing protocol for mobile ad hoc MAC. However, it is difficult to apply existing cross-layer networks which uses a metric incorporating data-rate, design into hybrid networks. In this paper, we have also MAC overhead, and buffer delay to combat congestion. proposed an enhanced TCP congestion control mechanism for wireless networks, based on a cross-layer scheme. 43 © 2010 ACEEE DOI: 01.ijns.01.01.09
  • 3. ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010 Ming Yu et al.,(2007) [14] have proposed a link routing traffic through congested area. Subsequently, the availability-based QoS-aware (LABQ) routing protocol for selection of the proportion of traffic to be routed to each mobile ad hoc networks based on mobility prediction and neighbor is made to perform routing such that the weight link quality measurement, in addition to energy of the node is a possible minimum. consumption estimate..Hongxia Sun et al [15], proposed an adaptive QoS routing scheme which is supported by cross- layer cooperation in ad hoc networks. By considering the IV. ESTIMATING QOS-BASED ROUTING METRICS influence of node mobility and lower-layer link performance, the cross-layer mechanism provides up-to- A. Estimating Link Quality date local QoS information for the adaptive routing Each node in the network estimates its quality of links with algorithm. Based on the current network status, the its one-hop neighbors. If Nq is the number of HELLO multiple QoS requirements are satisfied by adaptively packets received during a time window Twin and Pq is the using forward error correction and multipath routing percentage of HELLO packets received in the last r mechanisms. Al-khwildi et al [16], have proposed a novel seconds, then the link quality Lq is measured as routing technique called Adaptive Link-Weight (ALW) routing protocol which selects an optimum route on the Lq = δ. Pq + (1 – δ) . Nq (1) basis of available bandwidth, low delay and long route lifetime. Those technique adapts a cross-layer framework The estimated link quality is maintained by each node in where the ALW is included with application and physical its NT. The average link quality of all the links across the layer. path P, gives the route quality Rq of the path. RREQ packets of the reverse path and RREP packets of the III. SYSTEM DESIGN AND PROTOCOL OVERVIEW forward path accumulate the estimated Lq values.The value δ is application specific. We devise the model by considering a mobile ad hoc network in which each node utilizes IEEE 802.11 DCF for B. Estimating End to End Delay medium access control (MAC). At the application layer, intra-flow interference occurs for the same flow which is There is a significant variation between the end-to-end transmitted on different wireless links. But it has been delay reported by RREQ-RREP measurements and the presumed as a single data flow. delay experienced by actual data packets. We address this A QOS based multipath routing protocol intended for issue by introducing a DUMMY-RREP phase during route mobile ad hoc networks is put forwarded. In this paper, we discovery. The source saves the RREP packets it receives employed the facility to determine multiple routes to a host in a RREP TABLE and then acquires the RREP for a route and switch between them to expand the definition of from this table to send a stream of DUMMY data packets AOMDV [6].Enabling a QoS constrained route from along the path traversed by this RREP. DUMMY packets source to destination is the objective of the routing efficiently imitate real data packets on a particular path protocol. The route chosen by the protocol must send owing to the same size, priority and data rate as real data packets with minimum bandwidth and end-to-end latency, packets. H is the hop count reported by the RREP. The without facing congestion. The protocol should satisfy the number of packets comprised in every stream is 2H. The above constraints and also select the most robust among all destination computes the average delay Davg of all possible candidate routes. DUMMY packets received, which is sent through a RREP to the source. The source selects this route and sends data A QoS-based routing metric for MANETs should packets only when the average delay reported by this incorporate minimum available bandwidth and end-to-end RREP is inside the bound requested by the application. latency along with congestion around a link. Congestion is The source performs a linear back-off and sends the related to channel quality, which depends on the MAC DUMMY stream on a different route selected from its access contention and channel reliability. So our algorithm RREP TABLE when the delay exceeds the required limit. should rely on the following metrics to allocate weights to C. Estimating Channel Quality individual links. • End-to-End Delay The channel quality can be represented by both the channel • Channel Quality occupancy and channel reliability. • Link Quality C.1. Channel Occupation The individual link weights are combined into a routing In this network, we consider IEEE 802.11 MAC with the metric to validate the load balancing and interference distributed coordination function (DCF). It has the packet between links using the same channel. Consequently, the sequence as request-to-send (RTS), clear-to-send (CTS), traffic is balanced and the network capacity is improved as data and acknowledgement (ACK). The amount of time the weight value assists the routing protocol to evade between the receipt of one packet and the transmission of 44 © 2010 ACEEE DOI: 01.ijns.01.01.09
  • 4. ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010 the next is called a short inter frame space (SIFS). Then SSRC with an initial value of 0, when it transmits the RTS the channel occupation due to MAC contention will be frame successfully. By this way, when a node starts to transmit a new RTS frame, SSRC will be the initial value Cocc = tRTS + tCTS + 3tSIFS + tacc (2) of 0, in spite of the initial RTS which was transmitted successfully or discarded. Obviously, the node would not Where tRTS and tCTS are the time consumed on RTS and know the RTS retry count of the last frame for its resetting CTS, respectively and tSIFS is the SIFS period. tacc is the which results that its channel state cannot be known. time taken due to access contention. The channel occupation is mainly dependent upon the medium access To solve this problem, the value of SSRC is recorded when contention, and the number of packet collisions. That is, each RTS frame is retransmitted. The packet to be Cocc is strongly related to the congestion around a given transmitted will be marked as “1” in its congestion node. Cocc can become relatively large if congestion is experience bit when it exceeds the given the threshold “2”, incurred and not controlled, and it can dramatically which shows an imminent congestion in ECN mechanism. decrease the capacity of a congested link. Therefore, in the design of a congestion-aware metric for VI. QOS BASED ROBUST MULTIPATH ROUTING networks, the access contention should be considered to PROTOCOL more accurately indicate channel capacity. For establishing multiple disjoint paths, we adapt the idea C.2. Channel Reliability from the Adhoc On-Demand Multipath Distance Vector The channel reliability also affects the packet transmission Routing (AOMDV) [6]. The multiple paths are computed in MANETs and factors such as interference and fading in during the route discovery. the channel may lead to occurrence of packet losses. In 802.11 DCF, several failed retransmissions lead to packets We now introduce the weight metric W which assigns a being dropped. In addition to performance deterioration cost to each link in the network. The weight W combines due to congestion with respect to packet losses, higher the link quality Lq , channel quality Cocc and the average packet retransmissions involved owing to augmented delay Davg , to select maximum throughput paths, avoiding packet losses lead to more congestion. A successful the most congested links.For an intermediate node i with transmission of a packet on an unreliable links would established transmission with several of its neighbours, the consume more time on MAC overhead. W for the link from node i to a particular neighboring node is given by V. CROSS-LAYER DESIGN OF TCP W = Lq + Cocc + Davg (3) A. Route Request Currently, the main method of congestion control over wired network is an optimization framework based on During the route discovery phase of the protocol, each utility functions Moreover this method is not applicable intermediate node uses an admission control scheme to to the wireless networks. This is because due to the check whether the flow can be accepted or not. If accepted, immanent interference of wireless links the metrics like a Flow Table (FT) entry for that particular flow is created. queue length on routers, sending rate of links cannot The FT contains the fields Source (Src), Destination (Dst), characterize the congestion price. Reserved Bandwidth (BWres), Minimum bandwidth In this paper, according to the RTS retry counts, the ECN (BWmin). Each node collects the bandwidth reserved at its scheme will mark packets. IEEE 802.11 is the standard one hop neighbors (piggybacked on periodic HELLO protocol for wireless adhoc networks. It provides two packets) and stores it in its Neighbor Table (NT) .The options for accessing namely the basic scheme and Neighbor Table contains fields Destination (Dst), Reserved RTS/CTS scheme. In this paper only this RTS/CTS Bandwidth (BWres), No. of Hello Packets (No Hello). scheme is considered because it is used more in ad hoc networks than the basic scheme. But our design can also be Consider the scenario applied to the basic scheme. Let us consider the route In RTS/CTS scheme, in order to record the retransmit count of RTS frame in the current node, each node S -- R1 – R2 – R3 – D maintains a variable SSRC. When a node fails to transmit RTS frame, then it will retransmit this RTS frame and To initiate QoS-aware routing discovery, the source host S increases SSRC by 1 at the same time. The sender will sends a RREQ. When the intermediate host R1 receives report a link failure notification to the network layer if the the RREQ packet, it first estimates all the metrics as value of the SSRC reaches 7 and discards the RTS frame described in the previous section. and the data frame to be transmitted together and resets SSRC to an initial value of 0. Also the node refreshes the 45 © 2010 ACEEE DOI: 01.ijns.01.01.09
  • 5. ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010 The host R1 then calculates its weight WR1 using (3). Table1: Simulation Parameters WR1 No. of Nodes 25,50,75 and 100 RREQR1 ====== R2 Area Size 1000 X 1000 R2 then calculates its weight WR2 in the same way and Mac 802.11 adds it to the weight of R1. R2 then forward the RREQ Radio Range 250m packet with this added weight. Simulation Time 100 sec Traffic Source CBR Packet Size 512 WR1+ WR2 Mobility Model Random Way Point RREQR2 ============= R3 Speed 5m/s to 20m/s Finally the RREQ reaches the destination node D with the Pause time 5s sum of node weights B. Performance Metrics WR1+ WR2 + WR3 RREQR3 ================ D We compare our CBMR protocol with the AOMDV [6], CARM [13] and LABQ [14] protocol. We evaluate mainly B. Route Reply the performance according to the following metrics, by varying the nodes as 25, 50, 75 and 100. The Destination node D send the route reply packet RREP along with the total node weight to the immediate Control overhead: The control overhead is defined as the upstream node R3 . total number of routing control packets normalized by the total number of received data packets. WR1+ WR2 + WR3 RREP ================ R3 Average end-to-end delay: The end-to-end-delay is averaged over all surviving data packets from the sources Now R3 calculates its cost C based on the information to the destinations. from RREP as Average Packet Delivery Ratio: It is the ratio of the No. CR3 = (WR1+ WR2 +WR3) - (WR1+ WR2) (4) of packets received successfully and the total no. of packets sent By proceeding in the same way, all the intermediate hosts calculate its cost. C. Results On receiving the RREP from all the routes, the source C.1. Varying No. Of Nodes selects the route with minimum cost value. In the first experiment, the performance of the protocols is The simulation results in the next section showed that measured by varying the no. of nodes as 25, 50, 75 and these calculations did not increase the overhead 100. From Figure 1, we can see that the packet delivery significantly. ratio for CBMR increases, when compared to AOMDV, CARM and LABQ, since it utilizes robust links. VII. SIMULATION RESULTS From Figure 2, it is evident that the average end-to-end delay of the proposed CBMR protocol is less when A. Simulation Model and Parameters compared to the AOMDV, CARM and LABQ protocol. NS2 simulator is used to simulate our proposed protocol. Figure 3 shows that the control overhead of the protocols. In our simulation, the channel capacity of mobile hosts is Since CBMR make use of HELLO packets for cost set to the same value: 2 Mbps. We use the distributed estimation, the values are considerably less in CBMR coordination function (DCF) of IEEE 802.11 for wireless when compared with AOMDV, CARM and LABQ. LANs as the MAC layer protocol. It has the functionality to notify the network layer about link breakage. In our simulation, each node moves independently with the same average speed is assumed. The simulated traffic is Constant Bit Rate (CBR). Our simulation settings and parameters are summarized in table 1 46 © 2010 ACEEE DOI: 01.ijns.01.01.09
  • 6. ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010 Packet Delivery Ratio Packet Delivery Ratio 100 120 100 CBMR 80 CBMR 80 ratio(%) ratio(% ) AOMDV 60 AOMDV 60 CARM 40 CARM 40 20 LABQ 20 LABQ 0 0 250 500 750 1000 25 50 75 100 Rate Nodes Fig.4: Rate Vs Delivery Ratio Fig 1: Nodes Vs Delivery Ratio From Figure 5, we can see that the average end-to-end End-to-End Delay delay of the proposed CBMR protocol is less when compared to AOMDV, CARM and LABQ. 0.8 Figure 6 shows the control overhead of the protocols. 0.6 CBMR Since CBMR make use of HELLO packets for cost Delay(s) 0.4 AOMDV estimation, the values are considerably less in CBMR CARM when compared with AOMDV, CARM and LABQ. 0.2 LABQ 0 25 50 75 100 Nodes End-to-End Delay 0.6 Fig. 2: Nodes Vs Delay 0.5 CBMR 0.4 Delay(s) AOMDV 0.3 Control Overhead CARM 0.2 0.1 LABQ 1.2 0 1 CBMR 250 500 750 1000 0.8 AOMDV Rate ratio 0.6 0.4 CARM 0.2 LABQ 0 Fig. 5: Rate Vs Delay 25 50 75 100 Nodes Control Overhead 1.2 1 Fig. 3: Nodes Vs Overhead CBMR 0.8 ratio(%) AOMDV 0.6 B. Varying the Transmission Rate 0.4 CARM In the second experiment, we measure the performance of 0.2 LABQ the protocols by varying the transmission rate as 0 250,500,750 and 1000 Kb. 250 500 750 1000 Rate From Figure 4, we can see that the packet delivery ratio for CBMR is more, when compared to AOMDV, CARM and LABQ since it utilizes robust links. Fig 6: Rate Vs Overhead 47 © 2010 ACEEE DOI: 01.ijns.01.01.09
  • 7. ACEEE International Journal on Network Security, Vol 1, No. 1, Jan 2010 CONCLUSION Communications, vol. 2, pp: 1018- 1023, 13- 16 October 2003, Doi: 10.1109/MILCOM.2003.1290305. In a QoS based routing metric for MANETs, it is necessary [9] Jianbo Xue, Patrick Stuedi and Gustavo Alonso, "ASAP: An to combine the minimum available bandwidth and end-to- Adaptive QoS Protocol for Mobile Ad Hoc Networks", end delay along with the congestion around a link. MAC IEEE Proceedings on Personal, Indoor and Mobile Radio Communications, vol. 3, pp: 2616- 2620, 7- 10 September access contention and channel reliability induces 2003, Doi: 10.1109/PIMRC.2003.1259201. congestion that is related to channel quality. In this paper [10] Jangeun Jun and Mihail L. Sichitiu, "Fairness and QoS in we have developed a cross layer based multipath routing Multihop Wireless Networks", in proceedings of 58th IEEE (CBMR) protocol to improve QoS in mobile ad hoc Conference on Vehicular Technology, vol. 5, pp: 2936- networks to allot weights to individual links, depending on 2940, 6- 9 October 2003, Doi: the metrics link quality, channel quality and end-to-end 10.1109/VETECF.2003.1286161. delay. The weight value helps the routing protocol to avoid [11] Michael Gerharz, Christian de Waal, Matthias Frank and the routing traffic through the congested area and hence Paul James, "A Practical View on Quality-of-Service the traffic is balanced and the network capacity is Support in Wireless Ad Hoc Networks", Proc. of the 3rd IEEE Workshop on Applications and Services in Wireless improved. Then the proportion of traffic to be routed to Networks (ASWN), pp: 185-196, Berne, Switzerland, July each neighbor is selected to execute routing such that the 2003. weight of the node is a minimum. We have also proposed an [12] Duc A. Tran and Harish Raghavendra, "Congestion enhanced TCP congestion control mechanism for wireless Adaptive Routing in Mobile Ad Hoc Networks", IEEE networks, based on a cross-layer scheme. By simulation Transactions on Parallel and Distributed Systems, Vol. 17, results, we have demonstrated that the robustness of our no. 11, November 2006. protocol achieves increased packet delivery ratio with [13] Xiaoqin Chen, Haley M. Jones, A .D .S. Jayalath, reduced latency. The security challenges of our proposed "Congestion-Aware Routing Protocol for Mobile Ad Hoc protocol will be the subject of our future work. 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Das, "On- Demand Multipath Distance Vector Routing in Ad Hoc Networks", in proceedings of 9th IEEE International Conference on Network Protocols, pp: 14- 23, 11- 14 November 2001. [7] Andre Schumacher, Harri Haanpaa, Satu Elisa Schaeffer, and Pekka Orponen, "Load Balancing by Distributed Optimization in Ad Hoc Networks", in proceedings of 2nd International Conference on Mobile Ad-hoc and Sensor Networks, vol. 4325, pp: 874- 885, Berlin- Heidelberg, 2006. [8] Kaixin Xu, Ken Tang, Rajive Bagrodia, Mario Gerla and Michael Bereschinsky, "Adaptive Bandwidth Management and QoS Provisioning in Large Scale Ad Hoc Networks", in proceedings of IEEE Conference on Military 48 © 2010 ACEEE DOI: 01.ijns.01.01.09