effective bandwidth utilization in a multi-protocol label...

International Research Journal of Applied Sciences, Engineering and Technology

Vol.5, No.12; December-2019;

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Official Publication of Center for International Research Development Double Blind Peer and Editorial Review International Referred Journal; Globally index

Available www.cird.online/IRJASET: E-mail: [email protected] pg. 6

EFFECTIVE BANDWIDTH UTILIZATION IN A MULTI-PROTOCOL

LABEL SWITCHING NETWORK USING LOAD BALANCING SCHEME

Ogbu, Mary N.C., Onoh, Greg N., and Abonyi, Dorathy O. Department of Electrical and Electronics Engineering, Enugu State of University of Science and Technology Enugu, Nigeria.

Abstract: Bandwidth is one of the major performance metrics that telecommunication operators and Internet Service Provider (ISP)

use to evaluate their network. As the growth for Internet usage with several real time applications increases tremendously, there is

need for users to utilize the available bandwidth in an optimal way. This has put more pressure on operators and service providers to

provide adequate service for real time traffic. Unfortunately there has not been an improved quality of services provided to users

because of poor utilizations of available bandwidth. In an IP-based network like Multi-Protocol Label Switching in Virtual Private

network (MPLS-VPN), there is every need to manage efficiently the traffic across the Internet. To achieve this, load balancing model

was employed in an enabled MPLS network. This paper carried out an investigation on the impact of load balancing model for effective

utilizations of bandwidth in an MPLS-VPN. A virtual machine instance of Label Switch Router (LSR) was created using virtualization

process. Logical mapping of the LSR was carried out on the model. The work was simulated on MATLAB Simulink with two fast Ethernet

interface ports between banks headquarter and two branches at egress and ingress routers with and without load balancing. The

simulation results shows that the bandwidth utilizations traffic at egress and ingress routers for the ports with the model were uniformly

distributed to approximately 3Kbytes per second.

Keywords: MPLS-VPN, load balancing, bandwidth utilization, Quality of Service

1. INTRODUCTION

The basic common resources with high demand which many

service providers and telecommunication operators need to

provide to their customers is the reserved bandwidth between the

users. In a huge data center network, large amount of traffic

needs to be transmitted from one network node to thousands of

intermediary nodes. The usage of internet is becoming more

popular day by day. The more popular is the Internet, the more

the number of users. Several servers are interconnected together

using different protocols to communicate to each other. As the

traffic increases the tendency of unbalanced traffic applications

over the network nodes keep on increasing. The scalability

features provided by the MPLS network enables huge traffic

applications into the network and that need to be balanced.

Utilization of network bandwidth need not to be over or under

rather an optimal usage is an ideal in Virtual Private Network

over enabled MPLS system.

Abdullateef Aliyu (2016) reported that the bandwidth utilization

of Nigeria broadband system from the West Coast companies are

still under-utilized. Countries seeking job, growth and wealth

creation must address the issue relating to increase in its access

to broadband system. Broadband system is an enabling means to

other economic and human activities of a country especially for

future development of that nation. Bandwidth of Nigerian

telecommunication operators and Internet Service Providers

(ISP) were not yet utilized as expected by the ITU because of

some of the challenges. Nigeria National Broadband Plan

highlighted these challenges as power supply, high costs for

leasing of the transmission infrastructure, poor performance of

the transmission technology, multiple taxation/ regulations,

long delay in procuring approval for such rights of the way,

vandalism and disruption caused by road works. In order to

utilize this bandwidth as expected by the ITU, Nigeria

government has been advice to establish a national backbone

infrastructure that will make the carrying and distribution of high



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data capacity from the shores of the country to the hinterland

possible. Based on this many ISPs and telecommunication

operators have started implementing bandwidth utilization

services at their network especially at the MPLS backbone

routers.

Load balancing scheme is the mechanism that facilitate this

optimal usage of bandwidth. The ability of the intermediary

devices (routers) to distribute the client’s request across various

number of servers within the network is known as a Load

balancing. Load Balancing is a step by step ways of ensuring

consistent balance of workload on the network resource pools.

In data communication network ordinary traffic management

technique could not effectively enhance the network quality of

service (QoS) in terms of bandwidth usage. With the help of

load balancing model, network traffic between routers in an

MPLS –VPN can be observed. This will address the issue of

bandwidth allocation to real time applications for different VPN

users sharing the same resources over MPLS networks. The

existing load balancing technique adopts an approach that have

complex design. Hence, there is every need to adopt a technique

that will reduce the traffic overhead using weighted least Load

balancing model. A simple algorithm of virtual logical active for

the purpose of reengineering the traffic flow in an MPLS-VPN

network was developed.

2 RELATED WORKS

Mahalakshmi and Ramaswamy (2012) used Hose Model to

develop a multipath routing scheme for Virtual Private

Networks. The proposed scheme established various multiple

paths for the traffic between source and destination. With this

mechanism, the overall network utilization increased and

performance in terms of delay, packet loss was enhanced. Singh,

Chandhari, and Saxena (2012) surveyed various load balancing

mechanism in an IP/ MPLS networks. Some of the techniques

were Periodic Multi-Steps algorithm (PEMS), Load

Distribution in MPLS (LDM), Topology-based Static Load

balancing algorithm (TSLB), Dynamic Load balancing

algorithm (DLB), Load Balancing over Widest Disjoints Paths

(LBWDP), Resource-based Static Load balancing algorithm

(RSLB), Dynamic Online Routing Algorithm (DORA),

Minimum Interference Routing Algorithm (MIRA) etc. In order

to balance the load among different paths analysis of these

techniques were done. According to the authors, bandwidth

resources were limited in an IP network, thus traffic needs to be

engineered in order to overcome the limitation. Hence, the

authors requested that ISP should make adequate services

especially for voice and video traffics to be more available for

efficiency performance of an IP network.

Kayamak and Rojas-Cessa (2015) carried out research work

which evaluated the performance of per-packet load balancing in

Data Center Network (DCN). The network metrics used for the

evaluation were flow completion time and throughput. Banu and

Ramachandran (2013) proposed MPLS load balancing technique

to enhance the quality of service for VoIP application. The

research work was implemented with effective flow

classification technique. Also voice packet based on their flow

arrival rate and bandwidth utilization was prioritized. Load

unbalanced situation and congestion increase that resulted due to

link failure in the network were enhanced with the proposed

technique. Rainbow Fair Queuing mechanism was used to create

free label Switched Paths for multipath dispersion and

congestion free.

Hayian et.al (2009) proposed multi-Internet Service Provider

load balancing optimization model based on BP neural networks

in order to solve the problem of manual strategy choice when

they use the campus network of multiple ISP. The model

replaced the manual strategy choice, automatically evaluate and

forecast the quality of service performance of the networks. The

effectiveness of the model was verified with the experimental

results. Some conventional load balancing technique cannot be

used because of its cost-effective. Many researchers has

concentrated on Software Defined technique that can improve

transmission of data across network.

Anastasi, Coppola, Dazzi and Distefano (2016) focused on

provision of QoS guarantee for bandwidth utilization of any

cloud networks. An admission control test model was adopted in

the work for Service Level Agreement (SLA) specifications. The

study enforced such bandwidth guarantee by leveraging Linux

Traffic Control (TC) technology. An experimental setup was

conducted in order to validate the approach. It was observed that

the Linux TC was very effective in the proposed

approach.Porwal, Yadar and Charhate (2008) carried out a

comparative analysis of Non-MPLS and MPLS taking into

considerations the behavior of multimedia applications in a

heavy load network. MPLS-based and IP-based (Non-MPLS)

networks were simulated with and without Traffic Engineering.



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From the simulation result, performance metrics were properly

enhanced for the network with TE.

3 THEORY

Bandwidth in networking is defined as the amount of data

transferred from one point to another in a network at any given

time. It is expressed as bits per second or bytes per second.

However, bandwidth utilization is the percentage of data rate

used in a network during traffic flow. Optimal bandwidth

utilization is usually achieved with load balancing mechanism

that comprises traffic engineering and scheduling. Load

balancing scheme is a technique used to ensure uniform

distribution of traffic workloads at various remote VPN sites.

The technique balances the incoming (ingress) and outgoing

(egress) traffic into virtual machines. It works with Traffic

Engineering (TE) and Resource Allocation/Scheduling (RAS) to

reduce congestion in the network, improve the utilization of

various network paths, reserved network resources thereby

providing more effective network performance in terms of

bandwidth. This technique makes use of load balancer

instantiation (a way of creating virtual machine instances) by

logically mirroring the image of a single balancer into multiple

ones. There are different types of load balancer techniques such

as round robin, weighted round robin, weighted least connection

and random. This study made use of weighted least connection

load balancing scheme which considered two things: the weight

component of the devices and current number of connections

connected to each device.

Traffic Engineering (TE) is an IP-based mechanism that controls

the data traffic and provides optimization of its performance by

utilizing the network resources optimally. (Mishra and Ahmad,

2014). It has been a challenging task to provide good traffic

engineering through traditional IP networks. The IP packets are

forwarded by mainly choosing the shortest path firstly from

source to destination using OSPF protocol in traditional IP. This

causes low end-to-end delay and packet losses during the video,

voice and data applications delivery. TE in MPLS is used to

solve this issue. MPLS in VPN uses traffic engineering to ensure

traffic across the network with the aim of balancing load on the

various routers, switches and links in the network so that there

will be no over- or under-utilization of individual components.

The primary characteristics of TE are optimum resource

utilization, resource reservation and fault-tolerance (Ahmad, S.

et al. 2015). Traffic management, distribution of topological

information, direction along the computed paths and path

selection are factors needed to obtain these TE characteristics.

4 LOAD BALANCING MODEL IN AN MPLS-VPN

QoS performance in terms of bandwidth utilization was studied

by using a simulation approach. The simulation platform

employed in this work is based on OPNET 17.5 software version.

The background dataset used in the study was obtained from the

simulation done between bank headquarter and two branches as

VPN customer transmitting packet via ISP MPLS backbone.

Having designed the MPLS-VPN topology in the simulation tool

palate and configured the profiles, a load balancing model for

proper investigation of bandwidth utilizations was developed.

In this section MPLS-VPN load balancing model that will help

to improve the resource allocation problem on bandwidth

utilization with respect to QoS was developed. As traffic on the

network devices increase, some devices cannot bear the crisis,

thus load balancer was developed in Label Switched Router

(LSR) of the MPLS backbone. This was done by employing

what is called virtual instantiation which is an instance of a single

balancer with configurations. A virtual machine instance was

created in order to support connections of headquarter to the

remote ends. By using hypervisor it means using an intermediary

engine that can pull out what is needed from Central Processor

Unit (CPU)/memory’s hardware at any site and push to the

processor during data communications.

In the system, while the core layer addresses issues of resource

control, security and traffic switching, the load balancer model

takes care of traffic integration while offering fault tolerance to

remote VPN sites. Remote users R, receive services from

Internet via the load balancer gateways Gg. All jobs or tasks sent

by the remote users Ri, represents a request to network resources

Nr in the CBMV. The resource pools in the CBMV processes all

user requests via the Internet, however the load balancer has

virtual machine processors that are connected via high speed

interconnection links Hil.The load balancer allocates the

jobs/requests received from Users Ui, to the remote VPN

processors/sites. The Vm processors at the VPN sites execute

the traffic received from the load balancer and send it back to the

Users Ui using CBMV label stacking for optimal traffic

tunneling.

Fig. 1 simplifies the Vm load balancer cluster integration model

with the remote cloud backend. From the figure, a load balancer

controller 𝐿𝑚 ensures uniform traffic distribution. Equation (1.1)



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gives the simplified model description. The first term shows the

VPN user computing activities from remote locations to the

MPLS virtual instances core. The second term captures the

computing activities from LSRs virtual instances to the virtual

load balancer service while the third term and fourth term show

the load balance controller and virtual instances for remote VPN

sites in the CBMV respectively.

𝐶𝐵𝑀𝑉𝑖=𝑘=∑ (𝑉𝑈𝑘+1)𝑘

𝑖=0 + ∑ (𝐿𝑆𝑅𝑣𝑚𝑛+1)𝑛+1

𝑖=0 + ∑ (𝐿𝑣𝑚𝑛+1)𝑛+1

𝑖=0 + ∑ (𝑉𝑅𝑚𝑛+1)𝑛+1

𝑖=0 (1.1)

Where ∑ (𝑉𝑈𝑘+1) = ⟨𝑉𝑈1

+ 𝑉𝑈2+ 𝑉𝑈3

⋯ ⋯ + 𝑉𝑈𝑛+1⟩𝑘

𝑖=0 (VPN user computing activities)

∑ (𝐿𝑆𝑅𝑣𝑚𝑛+1) = ⟨𝐿𝑆𝑅𝑣𝑚1

+ 𝐿𝑆𝑅𝑣𝑚2+ 𝐿𝑆𝑅𝑣𝑚3

⋯ + 𝐿𝑆𝑅𝑣𝑚𝑛+1⟩𝑛+1

𝑖=0 (LSR computing activities)

∑ (𝐿𝑣𝑚𝑛+1) = ⟨𝐿𝑣𝑚1

+ 𝐿𝑣𝑚2+ 𝐿𝑣𝑚3

⋯ ⋯ ⋯ + 𝐿𝑣𝑚𝑛+1⟩𝑛+1

𝑖=0 (Load Balance Controller activities)

∑ (𝑉𝑅𝑛+1) = ⟨𝑉𝑅𝑚1

+ 𝑉𝑅𝑚2+ 𝑉𝑅𝑚3

⋯ + 𝑉𝑅𝑚𝑛+1⟩𝑛+1

𝑖=0 (Remote VPN user computing activities)

From Equ. 1.1, traffic job rates 𝑡𝑟 was represented as accessing remote sites traffic and its other resources, from the virtualized load

manager 𝐿𝑣𝑚 in the CBMV domain. A VPN user was connected to the computing resources of the CBMV from the distributed load

managers/controllers shown in fig.1.

CBMV-Logical

Load Balancer

Vm

Vm

Vm

Vm

Vm

Vm

Vmi1

Vmim+1

Vmi2

Vmi3

Vmim+1

Vmim+1

Vmi4

Vmim+1

Vmi5

VmiK

Vmim+1

Vmim+1

Traffic

Engineering

VLAN

LVM

LVM

LVM

LVM

LVM

LVM

Fig.1: Developed CBMV Load Balancing Model with VLAN TE

A Virtual Local Area Network (VLAN) traffic engineering was

configured and introduced to reduce the network density. This

was done with configuration. For the traffic workload expected

to run in the system, the maximum VM instantiations were

created to be 1005. This is the maximum traffic workload a VPN

user can send to load balance controller. The load manager 𝐿𝑣𝑚



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(load balance controller) with traffic arrival rates 𝑅𝑗 was

connected to the remote VPN sites. Each 𝑉𝑚instance only

executes jobs allocated to it and never dispatches again to

another 𝑉𝑚instance. In this case, each 𝑉𝑚instance maintains a

queue that holds the jobs to be executed based on First-In-First-

Out (FIFO) pattern. This work will now derive the job allocation

to CBMV load balancer depicted in Equation (1.2).

ɸ𝐽𝑎=∑ (𝐿𝑚α𝑈𝑗

)𝑛𝑖=1 = ⟨𝐿𝑉𝑚α𝑈1

+ 𝐿𝑣𝑚α𝑈2+ 𝐿𝑣𝑚α𝑈3

+ ⋯ +

𝐿𝑣𝑚α𝑈𝑛+1⟩ (1.2)

where

𝐿𝑣𝑚α𝑈𝑛+1 represents the traffic workload that a VPN user Ki

sends to load balance controller 𝐿𝑣𝑚. For the model to be

effective, the average traffic arrival rate 𝑅𝑗 of the 𝐿𝑣𝑚 must be

less than the total average processing rate of the remote VPN

sites. Hence, the traffic arrival rate is given by Equ 1.3 as

𝑅𝐿𝑣𝑚=∑ (𝐿𝑣𝑚α𝑈𝑛+1

𝑢𝑖=1 ) ∗ 𝐾𝑟 < 𝑃𝐿𝑣𝑚

(1.3)

But 𝐿𝑣𝑚α𝑈𝑛+1 must be constrained such that Equ 1.4 holds

0 ≤ (𝐿𝑣𝑚α𝑈𝑛+1≤ 1(1.4)

Such that Equ. 1.5 validates this scenario

∑ ⟨𝐿𝑣𝑚α𝑈𝑛+1⟩𝑢

𝑖=1 = 𝑃𝑣𝐿𝑣𝑚 / 𝐾𝑟 (1.5)

Where 𝐾𝑟= Traffic generation rate of VPN user Ki

𝑃𝐿𝑣𝑚 = Processing capability of virtualized load balancer

𝐿𝑣𝑚 instance.

In the model, the load balancer logically connects all the devices.

This offers a very scalable integration for the load balancers in

CBMV. Since from fig.1,LVm defines all the physical load

balancers in the entire MPLS-VPN. The objective function was

to optimize the QoS performance and improved bandwidth

utilization while maintaining fault tolerance generally. Based on

this case,let m represents the upper bound of traffic flow in arc

(i;j) while n gives the lower bound to give the following Linear

Programming formulation as shown below.

Max∑ (𝐿𝑣𝑚(𝑖, 𝑗)) 0≤ ɸ ≥ m 0<ɸ>𝑛

(1.6)

Subject to

R𝑣𝑚> 1

where R𝑣𝑚 ( VM resource constraints) were the CPU, memory,

I/Os, etc.

The dynamic load balancing/scheduling algorithm needed for

bandwidth optimization obtained with the equations were shown

in fig.2. The VM load balancer was set to be greater than n (the

lower bound of traffic flow). The model estimated the total

traffic workload coming out from sites to headquarter while

dynamically adjusting the Vm allocation. The total traffic

workload was checked in the simulation compilation platform.

This check was done in order to know if it has exceeded the

threshold. The set threshold is the maximum traffic workload of

1005 a VPN user can send to the load balancer controller in

respect to bandwidth usage. When the threshold was greater,

another VM load balancer was set up. Otherwise VM was

automated by increasing it. Once the VM was incremented, the

VLAN TE for proper logical isolation of the traffic matrix was

also set. This was done in order to map the VM traffic matrix

efficiently. VLAN Traffic Engineering integrated all traffic from

headquarter to remote ends.Again, the model checked if the

resources in respect to bandwidth were equated to the total traffic

task. Assuming the check was negative, the model will carry out

a dynamic transformation of virtual machines. Hence or

otherwise the system assigned tasks to different nodes thereby

balancing the resources and traffic efficiently. The system

initialized the VM load balancer such that it offered supports for

n resources to traffic flow on the egress route. Once the resources

assignment is equated with traffic task, bandwidth is uniformly

distributed for traffic flow.

4.1 Logical Mapping of IP address in LSR Load Balancer

From fig.1, traffic engineering with VLAN and virtualization

were introduced to strengthen the usefulness of the load balancer

model in LSR shown in the figure. In this section, Software

Defined Networking (SDN) with VLAN IP mapping was

introduced to address the issues of large scale network density.

Figure 2 illustrates the logical mapping of IP addresses in LSR

Load Balancer of the VPN sites running to ensure maximum

throughput, lower delay and achieve VLAN security services.

This mapping was done at the LSR load balancer of different

VPN sites with configuration. This was done in order to avoid

any VM instance fail over and to create redundancy for the

different sites. The configuration was done properly so that there

will not be any impact that affect the network stability and

availability. Recall that the virtual load balancers have VLAN



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traffic engineering which offers VPN flexibility, security, traffic

regulation and congestion control across the CBMV.

.

Fig.2: Illustration of Logical Mapping of IP address in LSR Load Balancer

This algorithm has two sections. The first section checks

whether LSRs, virtual load balancer and remote VPN sites are

well established and functioning at optimal capacity based on the

pre-set parameters. After its verification of the above

components, logical connection was established while

accommodating established traffic from the VPN sites.

Secondly, the VLAN interconnects all the LSR services once an

instance is created. Each LSR in the subnet cluster was

connected with a characteristic IP address for traffic routing in

the modeling. With this SDN-VLAN mapping scheme, a logical

isolation of the VPN-sites cluster subnets in the CBMV

architecture was achieved in fig. 2. The addressing scheme was

developed for the CBMV leverages on Classless Inter-domain

Routing (CIDR) in order to achieve scalability, route

aggregation, dynamic updating. This was done in IP attribute

palate in the RIVERBED modeler. Considering fig.2 with four

nodes, LSR nodes were considered for easy configurations and

for simplicity purposes per site as shown in the figure. After

developing the host IP mapping, two options are feasible: Static

and dynamic IP mapping. For exactness of this simulation setup,

manual static approach was adopted. Hence, in the baseline

testbed used in this work, a scalable inter-domain routing

addressing scheme was developed.

5 SIMULATION APPROACH

v

𝑉2

𝑉3

𝑉4

𝑉𝑛

𝑉1LSR-

𝑉2

𝑉3

𝑉4

𝑉𝑛

vLSR-

𝑉2

𝑉3

𝑉4

𝑉𝑛

VPN-

Site 3

vLSR-

𝑉2

𝑉3

𝑉4

𝑉𝑛

VPN-

Site 4

VPN-

Site2

VPN-

Site1

S-VLAN1

S-VLAN2

S-VLAN3

S-VLAN4

S-VLANn

Load Balancer Load Balancer

Load Balancer

Load

Balancer



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So far, under heavy VPN traffic tunneling, the presence of

Resource Allocation and Scheduling (RAS) and VLAN Traffic

Engineering in the Load Balance model, an efficient servicing of

VPN traffic flow in terms of QoS bandwidth utilization were

explored. To show the necessity of this a simulation was done at

two different interface ports of cloud MPLS network. Traffic

were transmitted from headquarter to the VPN branch office 1

and 2 and results were analyzed.

Fig. 3 Network Simulation Topology with the Interface Ports for Load Balancing Model Analysis

6 RESULTS ANALYSIS

The analysis of data collected from the simulation with its effect on the network bandwidth utilization at different time was presented

in this section. A 1000 packets were sent from the source to the destination router, the requested packet were then transmitted back to

the source router. Bandwidth utilization and packet flowing from each interface were monitored through Simple Network Message

Protocol (SNMP). Two different interface ports connected to the source router were used during the analysis. The interface include fast

Ethernet fa0/0 and fa0/1. The figure 4 depicted the data collected when data traffic were transmitted from the branch VPN to headquarter

through enabled MPLS backbone.

6.1 Performance Influence on Bandwidth Utilization Traffic over MPLS-VPN without Load Balancing

This subsection presents the analysis of the data that were collected from simulation at the egress and ingress routers. The effects of the

results on the network bandwidth utilization at different time were explored. Firstly the bandwidth utilization of the traffic that were

transmitted from source to destination on fast Ethernet interface 0/0 without load balancing were shown.

Fig. 4: Bandwidth Utilization of Egress and Ingress Traffic on Interface 0/0 without Load Balancer



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Result Analysis of Traffic on Interface 0/0 without Load Balancing

The fig. 4 shows the statistic of different bandwidth at Fast Ethernet 0/0 interface with the time of monitoring. The average of these data

were monitored and collected at intervals of five minutes. It was observed that bandwidth utilization traffic at egress and ingress routers

were

76.81% and 23.19% respectively. The results depicted in fig. 6 shows that incoming traffic were under-utilized while outgoing traffic

was over-utilized. There were chances of high probability loss of packet on the network because bandwidth usage were not efficiently

used at both ends.

The bandwidth usage of the outgoing and incoming traffic to the destination router through interface 0/1 were presented.

0

2

4

6

8

10

12

11:30am 11:35am 11:40am 11:45am 11:50am 11:55am 12:00pm

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dw

idth

(K

byt

es)

Bandwidth Utilization on Interface 0/0 without Load Balancer

Egress Router Ingress Router



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Fig. 5: Bandwidth Utilization of Egress and Ingress Traffic on Interface 0/1 without Load balancer

The traffic load at the interface were still under-utilized, thus there were wastage of bandwidth. These links at Fast Ethernet 0/0 and 0/1

were getting over loaded and under loaded of the bandwidth because there is no load balancing of the network traffic.

6.2 Performance Influence on Bandwidth Utilization Traffic over MPLS-VPN with Load Balancing

In this particular section, the influence on bandwidth utilization traffic over MPLS-VPN with the implementation of load balancing

were explored. Master and slave servers were created and this was done in order to check redundancy in the network especially when

there is link or node failure. Several packet were sent from source to destination and successful results were collected. The results of

bandwidth usage at both egress and ingress routers were depictedfor interfaces 0/0 and 0/1 respectively.

0

2

4

6

8

10

11:30am 11:35am 11:40am 11:45am 11:50am 11:55am 12:00pm

Bandwidth Utilization on Interface 0/1 without Load Balancer



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Fig. 6: Bandwidth Utilization of Egress and Ingress Traffic on Interface 0/0 with Load Balancer

Observed that the bandwidth utilization of the data traffic from figs. 6 and 7 were approximately equal at both egress and ingress routers

because of the presence of load balancer whose function is to uniformly distribute traffic among nodes at different sites.

0

1

2

3

4

5

6

11:30am 11:35am 11:40am 11:45am 11:50am 11:55am 12:00pm

Ban

dw

idth

(K

byt

es)

Time (sec)

Bandwidth Utilization on Interface 0/0 with Load Balancer


0

1

2

3

4

5

11:30am 11:35am 11:40am 11:45am 11:50am 11:55am 12:00pm

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byt

e)

Time (sec)

Bandwidth Utilization on Interface 0/1 with Load Balancer




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Fig. 7: Bandwidth Utilization of Egress and Ingress Traffic at Interface 0/1 with Load balancer

Hence, there is minimal loss of packet. This shows that the number of packets that are distributed at each interface and resources shared

among intermediary devices are roughly equal to the number at the other end, therefore bandwidth are properly utilized.

Figs. 8 and 9 show the comparison of the bandwidth utilization of the traffic of the two scenarios with or without load balancing

mechanism.

6.3 Comparative Analysis of Bandwidth usage at Egress and Ingress Routers

An average bandwidth utilizations of egress traffic for the two different interface ports with and without Load Balancer were computed

in this subsection.

The result in fig. 8 shows that roughly 3Kbytes of bandwidth of egress traffic for both 0/0 and 0/1 interfaces were equally utilized.

Fig. 8: Average Bandwidth Utilizations of Egress Traffic without and with Load Balancer

Similarly the computation of an average bandwidth utilizations of ingress traffic for the two different interface ports with and without

Load Balancer were carried out. Results are presented in fig. 9.

0

1

2

3

4

5

6

7

0/0 interface 0/1 interface

Ban

dw

idth

(Kb

yte

)

Average Bandwidth Utilizations of Egress Traffic

Without LB With LB



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Fig. 9: Average Bandwidth Utilizations of Ingress Traffic without and with Load Balancer

It was observed that with load balancing technique the

bandwidth utilization are approximately 3.0Kbytes in all

interface ports on both egress and ingress router. The orange

color from the chart represents the average utilization when

traffic loads are balanced during data transition at egress end,

while blue depicted the situation of MPLS network without load

balancer. The percentage evaluation of the simulation with and

without Load Balancing mechanism were 42.36% and 57.64%

respectively.

CONCLUSIONS

This paper shows how Load Balancing scheme helped in

achieving an effective bandwidth utilizations in an MPLS

network. The result shows that there were lower drainage of

utilization in terms of resources and bandwidth with Load

balancing scheme Hence, there were an optimal usage of

bandwidth by the operators and VPN users when there is load

balancing model in the cloud of the network whereas much

bandwidth were wasted when the traffic loads were not

balanced. With the presence of load balancing model in an

MPLS-VPN, bandwidth of the network devices were expanded,

throughput increased, network data processing capability and

flexibility were well enhanced.

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Aliyu, A. (2016, July 26). Speech on IEEE Nigeria section.

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http://sites.ieee.org/nigeria/2016/07/26/speech-by-

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http://sites.ieee.org/nigeria/2016/07/26/speech-by-engr-abdullateef-aliyu-yp-chair-at-the-programmers-club-seminar-ntn-university-boot-camp-23th-july-2016/






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p –ISSN 0920-5691

Impact factor: 3.57




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