Load Balanced Cross Layer Based Multipath Routing in Mobile Adhoc Network

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Load Balanced Cross Layer Based Multipath Routing in Mobile Adhoc Network

M. Anuradha

A.Sheryl Oliver J.Jean Justus

1Associate Professor, Department of Computer Science and Engineering, St.Joseph’s College of Engineering, Chennai, India.

Abstract-Multipath routing in Mobile Ad-Hoc Network (MANET) usually results in end to end delay and overload in nodes. It is quite difficult to resolve these issues, but it can be reduced by implementing the cross-layered multi-path routing technique we propose in this paper. The initial step involves setting the optimal or better route using the cross-layer metric parameter, followed by sorting the cross-layered metric in descending order. The cross-layer metric is calculated using Expected Transmission Time, residual energy and the load balancing factor of the network. To balance the load, the primary and secondary paths are assessed by calculating the bandwidth that is available. This allows the network to split the data into parts and transmit these parts over the primary and secondary paths. Apart from this being a superior load balancing procedure, this technique avoids congestion during transmission. The success of this technique has been further validated by the findings of the simulation results.

Keywords - MANET, Multipath routing, Load Balancing, Bandwidth, Cross layer metric.

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1. Intro duction

MANET is a group of wireless nodes that can grow into their own network because they don't need an infrastructure. MANETS have become significantly popular in computing due to the dynamic configuration of the nodes in this network without an infrastructure .Communication in networks is enabled when one node exchanges packets with another node and this is supported in MANET through the concept of multi-hop. In a decentralized system network, correspondence commonly includes impermanent multi-hop relays, where the nodes rely on each other instead of relying on any fixed infrastructure. In MANETs every node is assumed to be identical to the other nodes in the network, where each node is viewed as fit for moving information between the discretionary source and destination. Thus, every node in a MANET is given the choice of donning the role of a source, destination, or a router [1-2].

Mobility, despite being a characteristic property of MANET, causes issues like high data relay, low packet delivery ratio, low stability and reliability in routing to occur. This pushes the network to reconsider the degree of the node mobility offered [3]. Another main function of MANET is maintaining connectivity with minimum resources and overhead control – the self- configuration ability for changing network topology [4].MANETs can likewise be characterized as an independent system of mobile routers and related hosts linked by wireless links. These links form an arbitrary graph in union. The constrained transmission range causes the nodes in the network to act as a router to forward packets to further nodes and this can be achieved through a suitable routing protocol [4]. The Mobile Nodes (MN) act as routers or endpoints and have to manage their limited power supply, and use the residual energy to participate in the communication pipeline [13].

1.1.Multipath Routing in MANET

Multipath routing is intended to provide the nodes in a Mobile Ad Hoc Network with multiple paths. Multipath routing protocols are actively exploring all possible alternative routes from the source to send a packet. This protocol serves to be more efficient in cases where route failures occur more frequently[8-9].

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ISSN: 2005-4238 IJAST

1.2.Load Balancing for Multipath Routing

Load balancing is used in networking to divert packets from MNs which have higher facility to those nodes with lesser or zero packets using the existing multiple paths. Therefore, the probable of congestion network can be controlled and improves the overall rate of transmission of the dynamically altering network load. This also improves the throughput of the overall network and helps provide better quality of service (QoS). Packet distribution is based on the destination address in pre-destination load balancing of the router. In cases where the network consist of two paths, where the paths have the same bandwidth, the router transmit one packet to the first end source over the 1^st path and 2 ^nd packet meant for the same end source using the 2 ^nd path.

It is through the use of load balancing system applying in a network that it is potential to allocate the workload across multiple paths to accomplish optimal resource utilization, decrease response time, optimize throughput, enhance network lifetime and potentially remove overload.

It increases a sense of reliability in multiple paths through redundancy [5-7].

2. Related Work

Previously, a Multi-Objective Cross-Layer based multipath routing protocol was proposed using MANET [12]. A Cross Layer Metric(CLM) is hybrid with the routing protocol to compute on best possible route decided by the CLM.

An alternative proposal is to develop a load balancing technique for cross-layered multipath routing. Firstly, the available K multiple paths are sorted, preferably in descending order of the metric derived for the cross-layer network. Following this, the bandwidth across the primary and secondary paths is then calculated. The data meant for transmission is split into P+(K-1) parts.

Here P is a major chunk of data to be transmitted across the primary path. The leftover data packets will be transmitted across K-1 available secondary paths. Apart from avoiding congestion, it also provides better load balancing.

Hesham Ali et al., [6] have introduced a load balancing parallel routing protocol (LBPRP) to enhance the network life time and no of nodes in MANET routing.

Sushil Chandra Dimri et al.,[10] have projected a queuing delay-based traffic distribution method and implemented a k-path routing in a MANET for transferred the data from source to destination. This scheme can enhance the network system reliability and diminishing of system delay.

Vinothkumar et.al.,[11] in MAC layer the load-aware routing metric combines with traffic loads to optimize load balancing effect, into a multipath routing protocol. This scheme approach overcome the congestion problem and better route selection in multi path routing.

3. Load Balancing for Cross Layer Based Multipath Routing

3.1 Overview

Our aim is to propose a technique for load balancing meant specifically for cross layer based multipath routing is sown in Fig.1.. Here, multiple paths are sorted based on the descending order of the cross-layer metric and are subsequently established. To balance the load in the overall network, the available bandwidth is calculated across the primary and secondary paths.

Following which, the data was divided into parts and transmitted across the primary and secondary paths which avoids congestion and improves load balancing.

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Fig. 1. Block Diagram of Load Balancing for Cross-Layer based Multipath Routing 3.2 Cross-Layer Metric

The network decides the best or the most optimum route using the parameter of CLM. The CLM calculated using Expected Transmission Time (ETT), residual energy and the load balancing factor of the network.[12]

TRES

LBF CLM ETT

. .

* .





 (1)

TRES : Total residual energy LBF: Load Balancing Factor.

, , : Normalization constants range ( 0 to 1) . 3.3. Multipath Route Establishment

In multi path route S (Source) and D (Destination) RREQ - Route request and RREP - Route reply Ni -Intermediate node

When source wants to transmit a data packet to destination (D), broadcasts RREQ packet towards D through the intermediate nodes (Ni).

RREQ packet is received by all nodes.

S Ni D

• Intermediate node receiving the RREQ updates the route cache .The format of routing table as shown in Table1.

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Table 1. Format of Routing Table

Format of Routing Table Source

ID

Sequence Number

Destination ID

Previous hop node ID

Hop count

Cross Layer Metric

• Intermediate node re-broadcasts the RREQ to its adjacent node or sends RREP if the node is destination(D.) This process is continue until RREQ reaches D.

 Consider the sample network in Fig.2 where the messages RREQ and RREP are broadcasted and replied in between source node S and destination node D.

Fig. 2. Multipath Route Discovery

• From Fig 2 Each intermediate node Ni updates the RREP cache for the next-node of the RREP and then unicasts this RREP in the reverse-path using the earlier-stored previous- hop node information and is process continued till RREP reaches S.

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Fig. 3. Path Selection

3.4.Estimation of Maximum Available Bandwidth

To obtain optimal load balancing, the available bandwidth of the primary and secondary path is calculated.

The maximum unused bandwidth (MBui) of node Ni is estimated using the following formula.







 ⁿ

j ij MAX

ui BW TF

MB

1

Eq.(2) where

BWmax is the maximum bandwidth or node capacity.

TFij is the traffic flow from node Ni to Nj (bits/second), Nj is the neighbor of i.

The maximum available bandwidth (MBai) of Ni is estimated using the following formula:







 ⁿ

j ij ui

ai MB TF

MB

1

Eq. (3) The total available bandwidth across the path p is then given by





 ^m

i

ai

ap MB

MB

1

Eq. (4) where m is the number of nodes along the path p.

3.3 Load Balancing Algorithm

Let {Pj}, j=1,2...K be the set of paths established using multipath route discovery. Sort {Pj}in the ascending order of cross-layer metric CLM. (i.e.) The path with lowest CLM is path P1 and next lowest CLM is path P2 and so on such that PK is having highest CLM. The path P1 is selected as the primary path and remaining (K-1) paths P2,P3,....PK-1 are considered as secondary paths.

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Start Let j=1

Estimate the traffic load T along the path Pj

If T > MBapj, then

Find the over loaded traffic OT = T- MBapj

Let T=T/2 and let T^j= T/2+OT Transmit T along Pj

j=j+1

If T^(j-1) > MBapj, then OT = T^j-1- MBapj

T= T^j-1/ 2 and T^j= T^j-1/ 2 + OT Transmit T along the path Pj

Else

Transmit T^j-1along the path Pj

Go to 20.

End if

If j< (K-1), then Repeat from 11 End if

End if Stop

P is major chunk of data to be transmitted across the primary path and the remaining parts of data will be transmitted across the K-1 secondary paths based on the available bandwidth along the paths.

Example:

Consider Fig 3, P1 = [S-3-6-7-D]

P2= [S-2-10-12-D]

P3=[S-5-4-15-8-D]

P4=[S-13-14-11-D]

Let CLM1=0.4, CLM2=0.7, CLM3=0.6 and CLM4=0.5 be the CLM values for the paths P1,P2,P3 and P4, respectively.

Let MBa1= 5 Mb, MBa2= 4.5 Mb, MBa3= 4 Mb and MBa4=3 Mb be the available bandwidths along the paths P1,P2,P3 and P4.

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The paths are arranged as {P1,P4,P3 and P2} based on the CLM values, where P1 is the primary path and remaining paths are considered to be secondary paths.

Let the traffic load of P1 at time t1 be 7 Mb which is greater than MBa1=5Mb.

Then OT = 7-5 = 2Mb. Then T = 7/2 = 3.5Mb and T¹= 3.5+2 = 5.5Mb.

Now T¹> MBa4 = 3 Mb. Then OT = 5.5-3 = 2.5Mb. T=5.5/2 = 2.725Mb and T²= 2.725+2.5=5.125Mb.

Now T²> MBa3=4Mb. Then OT=5.125-4=1.125Mb.

T=5.125/2=2.5625MbandT³=2.5625+1.125=3.6875Mb.

Now T³< MBa2=4.5Mb.

Hence the traffic load 7Mb along P1 is split as follows:

 3.5Mb along P1

 2.725Mb along P4

 2.5625Mb along P3

 3.6875Mb along P2.

4 Results and discussion

4.1 Simulation Parameters

Simulation of the proposed LBCMR protocol simulated in NS2, whereas IEEE 802.11 is used for wireless sensor networks in the MAC layer. In this simulation, the number of flows is varied as 2,4,6,8 and 10 respectively and network area is 1250 m x 1250 m with simulation time of 50 seconds. and simulated traffic is Constant Bit Rate (CBR). The simulation parameters are shown in Table 2.

TABLE 2 Simulation Parameters

No. of Nodes 110

Area 1250 X 1250

MAC 802.11

Simulation Time 50 sec Traffic Source CBR

Flows 2,4,6,8 and 10

Propagation TwoRayGround

Antenna Omni Antenna

Initial Energy 10.3 J Transmission

Power 0.3

Receiving Power 0.3

Transmission Rate 50,100,150,200 and 250Kb

4.2 Performance Metrics

We compare the LBPRP [6] protocol with our proposed LBCMR protocol. Since LBPRP [6]

balances the load of the remaining data by calculating maximum available bandwidth similar to

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LBCMR, it will be suitable to compare the performance of both these protocols We calculate performance of the proposed method with following parameters such as Average Packet Delivery Ratio, Residual Energy, Throughput and Packet Drop.

4.3.Based on Flows

Figures 4 to 7 show the results of delay, delivery ratio, residual energy and throughput by varying the number of flows from 2 to 10 for the CBR traffic in LBCMR and LBPRP protocols.

Fig. 4. Flows Vs Delays

Fig 4 shows the delay occurred for LBCMR and LBPRP techniques when the flows are varied.

The increase in flows results in increase in delay. As seen from the figure, the delay of LBCMR increased from 0.45 to 6.36 and the delay of LBPRP increases from 5.06 to 8.88. Hence LBCMR has 54% lesser delay than LBPRP technique.

Fig. 5. Flows Vs Delivery Ratio

In Fig 5 the increase in flows results in decrease in delivery ratio. As seen the delivery ratio of LBCMR decreased from 0.99 to 0.61 and the delivery ratio of LBPRP decreases from 0.70 to 0.25 Hence LBCMR has 54% higher delivery ratio than LBPRP technique.

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Fig. 6. Flows Vs Residual Energy

Fig 6 shows that the residual energy of LBCMR decreased from 15.37 to 12.29 and the residual energy of LBPRP decreases from 13.46 to 10.66 Hence LBCMR has 13% higher residual energy than LBPRP technique.

Fig. 7. Flows Vs Throughput

When comparing the performance of the two protocols, we infer that LBCMR outperforms LBPRP by 54% in terms of delay, 60% in terms of delivery ratio, 12% in terms of residual energy and 76% in terms of throughput.

Table 3. Improvement in Percentage of LBCMR with LBPRP for Varying Flows

Flows Delay (%)

Delivery Ratio (%)

Residual Energy (%)

Throughput (%)

2 91.0 29.0 12.4 65.1

4 82.5 67.0 13.0 80.5

6 44.1 75.0 8.10 81.4

8 23.5 71.7 15.4 80.4

10 28.35 58.14 13.23 70.66

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4.4. Based on Rate

Figures 8 to 11 represent the results of delay, delivery ratio and also include residual energy and throughput by varying the transmission rate from 50, 100, 150, 200, and 250Kb for the CBR traffic in LBCMR and LBPRP protocols

Fig. 8. Rate Vs Delay

Fig. 9. Rate Vs Delivery Ratio

Fig. 10. Rate Vs Delivery Ratio

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Fig. 11. Rate Vs Throughput

. When comparing the performance of the two protocols, we infer that LBCMR outperforms LBPRP by 62% in terms of delay, 53% in terms of delivery ratio, 23% in terms of residual energy and 71% in terms of throughput. Table 4 presents the percentage wise improvement of LBCMR over LBPRP for varying Rate.

Table 4 Improvement in Percentage of LBCMR over LBPRP for Varying Transmission Rate

Rate (Kb/s)

Delay (%)

Delivery Ratio (%)

Residual Energy (%)

Throughput (%)

50 86.5 35.9 29.7 61.7

100 91.9 52.4 28.7 72.7

150 72.0 58.8 26.7 73.8

200 29.9 61.1 18.5 74.0

250 28.3 58.1 13.2 70.6

5. Conclusion

In this paper, a load balancing technique for cross-layer based multipath routing is proposed.

This technique establishes multiple paths which are sorted based on the cross-layer metric in the descending order. To balance the load, the available bandwidths among the primary and secondary paths are calculated. Then the data intended for transmission is split based on the available bandwidth and sent across the primary and secondary paths to avoid congestion and improve overall load balancing. The simulation results reveal that this proposed technique minimizes end to end delay and overhead. In future work the optimized routes for the MANET can be identified this work can be extended by traffic, Hybrid based load balancing using machine learning algorithms and the load can be balanced among those routes by deep learning techniques.

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References

[1] Patil, Rekha, and A. Damodaram. "Cost based power aware cross layer routing protocol for Manet." IJCSNS International Journal of Computer Science and Network Security 8.12 (2008): 388-393.

[2] Yi, Jiazi, et al. "Multipath optimized link state routing for mobile ad hoc networks."

ELSEVIER, Ad Hoc Networks 9.1, Volume 9, Issue 1, January 2011, Pages 28–47.

[3] Amri, Huda Al, Mehran Abolhasan, and Tadeusz Wysocki. "Scalability of MANET routing protocols for heterogeneous and homogenous networks." Computers & Electrical Engineering 36.4 (2010): 752-765.

[4] Kunz, Thomas. "Energy-efficient MANET routing: ideal vs. realistic performance." Wireless Communications and Mobile Computing Conference, 2008. IWCMC'08. International.

IEEE, 2008.

[5] Hoang, Vinh Dien, Zhenhai Shao, and Masayuki Fujise. "Efficient Load balancing in MANETs to Improve Network Performance." In ITS Telecommunications Proceedings, 2006 6th International Conference on, pp. 753-756. IEEE, 2006.

[6] Ali, Hesham A., Taher T. Hamza, and Shadia Sarhan. "Manet Load Balancing Parallel Routing Protocol." International Journal of Computer Science 9 (2012).

[7] S.Venkatasubramanian and N.P.Gopalan, “Multi-path QoS Routing Protocol for Load Balancing in MANET”, International Journal of Networking & Parallel Computing, Volume 1, Issue 3, Dec2012-Jan2013

[8] Caleffi, Marcello, Giancarlo Ferraiuolo, and Luigi Paura. "A reliability-based framework for multi-path routing analysis in mobile ad-hoc networks." International Journal of Communication Networks and Distributed Systems 1.4 (2008): 507-523.

[9] P.Maheswaravenkatesh, A. Sivanantha Raja, T. Jayasankar & K.VinothKumar, “QoS Aware and Green Hybrid Access Network” Appl. Math. Inf. Sci. vol.11, no.3, May 2017, pp.819–825

[10] Chandra Dimri, Sushil, Sushil Kumar Chamoli, and Durgesh Pant. "Delay based Traffic Distribution of Heavy Traffic on K-Paths to achieve the Load Balancing and to minimize the Mean System Delay in MANET." International Journal of Computer Applications 63.22 (2013): 25-30.

[11] K. Vinoth Kumar, T. Jayasankar, M. Prabhakaran and V. Srinivasan, “ EOMRP: Energy Optimized Multipath Routing Protocol for Wireless Sensor Networks,” International Journal of Printing, Packaging & Allied Sciences, Vol. 4, No. 1, December 2016, pp 336-343.

[12] M. Anuradha and DR.G.S. Anandha Mala, “Multi-Objective Cross –Layer based Multi-path routing protocol in MANET”, Journal of Theoretical and Applied Information Technology, October 2014. Vol. 68 No.3

[13] Kaoutar Ourouss, Najib Naja, and Abdellah Jamali. “Mobility Based Investigation of Load Balancing and Energy Efficiency of MANets Routing Protocols.” In International Conference on Wireless Networks and Mobile Communications (WINCOM), Fez, Morocco 2016.

[14] K.VinothKumar, T.Jayasankar, M.Prabhakaran and V. Srinivasan, “Fuzzy Logic based Efficient Multipath Routing for Mobile Adhoc Networks”, Appl. Math. Inf. Sci. vol.11, no.2, March 2017, pp.449–455.

[15] Maryam Asgaria, Abbas Karimib , Mohammad Shahverdy , Maryam Mohammadi “A Learning Automata-Based Approach For Dynamic Load Balancing In Manet” International Transaction Journal of Engineering, Management, & Applied Sciences &

Technologies,2019, Volume 10 No.3 ISSN 2228-9860.