Minimizing Interference in WMN

5/19/2018 Minimizing Interference in WMN

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Minimizing Interference in Wireless Mesh Networks using multi

channel and multi radio

Mohammad Siraj*

* PSATRI, College of Engineering, King Saud University,

P.O.Box 800, Riyadh-11421, Saudi Arabia,

E-mail: [email protected]

Abstract

Wireless Mesh network is a promising technology which has become popular with network

providers providing last mile broadband internet connectivity to the end users. This popularity is due to

the fact that it inter operates well with diverse wireless systems and provides robust fault tolerance with

a high degree of redundancy and reliability. During relaying, Even if some of the mesh nodes die, there

exist many other alternative nodes to serve the end users. In addition, multi-hop WMNs increases the

coverage area. A common problem in WMN is the performance degradation as the network size

increases. This is due to the interference arising from the neighbors and varying traffic load. This is a

critical issue in WMN, which is due to the co channel interference in WMN utilizing individual channel

and singular radio. One of the approaches to increase performance of WMNs is to use multiple channel

multiple radio (MCMR) in each node (mesh router). In this work, a critical issue of performance

degradation in WMN, by incorporating MCMR in WMNs is addressed. This performance has been

evaluated by simulating it in our protocol in OPNET Modeler 17.1 PL1. Simulation results show theeffectiveness of using MCMR.

Key Words: Wireless mesh network, MCMR, Throughput, Packet Delivery Ratio

1. Introduction

IEEE 802.11 Multi Hop Wireless mesh networks (WMNs) [1] are self-forming, self-

healing and self-organizing. Their easy configuration and deployment make them an

economical, reliable and simple solution that can be implemented anywhere at any time. The

end users can use WMN to access the internet by connecting to any of the routers. WMNs

have emerged as a fundamental technology for the next generation of Wireless Networking.

They are formed by mesh routers and mesh clients as shown in Figure 1. WMNs are being

investigated at this moment to support video-related applications such as video streaming,

multimedia messaging, teleconference, voice over IP, and video telemedicine due to its

superior characteristics compared with other wireless standards, including mobility, high

data rate, and low cost infrastructure. They are also being utilized in providing internet

connectivity to rural areas and in disaster management. With such infrastructure in place, a

number of critical medical problems can be addressed with the help of WMNs and the

INFORMATION

Volume 16, Number 10, pp.7611-7624 ISSN 1343-4500

2013 International Information Institute


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stability of the infrastructure backbone can be done. In a wireless mesh network, the capacity

is degraded by interference from concurrent wireless transmissions. The Maximum

theoretical capacity in such networks at each node is given by (1/ n)O whereas the

achievable capacity is (1/ log )O n n where n is the number of nodes in the network in

random ad-hoc network ideal situations [3]. Through experimentation, it is found that in

IEEE 802.11 [4], which uses a contention-based medium access control the throughput

degrades approximately to, of the raw channel bandwidth [5]. Equation for the achievable

capacity illustrates that throughput capacity of a single channel WMN degrades significantly

as the network size grows. One of the key factors for this rapid degradation is from co-

channel interference as the transmission in a single channel WMNs is a half-duplex radio per

node. To minimize co channel interference one of the effective means is to go for multiple

channels and multiple radios (MCMR) for each node. Scheduling approach for CR- WMN.

Figure 1 Wireless Mesh Architecture [2]

The remainder of this paper is organized as follows: In section 2, some recent research

related work in this area has been discussed. Section 3, describes the network model to be

considered for classic WMN. In section 4, Load Balancing Interference Aware Routing

Protocol implemented with the best route discovery algorithm is described. Section 5

presents performance evaluation followed by conclusion and future work.


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2 Related Work

Interference is a key factor in WMNs as the transmissions from one user interferes with

the transmissions and receptions of other users. Due to the interference, the capacity of WMN

is constrained [6]. Researchers have tried to investigate the impact of interference on WMNthrough practical scenarios such as test bed environment[7] where it was found that

interference not only degrades the performance for single path flow but also for multi path

flows. Due to interference, a high quality video streaming service could not be delivered as a

high percentage of packets were lost. Siraj and Bakar [8] demonstrated the impact of

Interference on Multi-hop Wireless Mesh Network. They showed how the performance is

degraded due to interference.

In [9] a MAC protocol was proposed for resolving channel assignments in connections

going through multiple wireless hops in WMNs by considering interference range issue and

hidden node problems. In [10] an algorithm was proposed, which assigned the same channel

to the two links that were within the vicinity of interference range of each other, which were

a source of co-channel interference resulting in a decrease in network throughput. This

algorithm was based on two-way interference-range edge coloring. In [11] performance

analysis of WMN was done by modeling the maximum throughput per cell and average

system delay of the backbone and the gateways in the WMN. This analysis was based on a

general network model with two key considerations, the random access mechanism in the

MAC and the equivalent queuing network of the backbone. Packet arrival distribution and the

packet departure distribution at the intermediate mesh routers and gateway nodes separately

were analyzed. Maximum throughput per cell and the average packet delivery delay for the

backbone of the WMN was evaluated. The performance study of the influence of the number

of forwarding intermediate and gateway nodes on the system delay at the gateway nodes was

based on this evaluation. In multi-hop networks to improve end to end throughput the per hop

throughput has to be increased which in which in turn depends critically on the number of

simultaneous transmissions that can be achieved in a given network area. This can be

achieved using multiple channels. Nevertheless, with only one radio per node, channel

switching is required. This switching delay grows with the number of channels. For example,

the switching delay for the present 802.11 hardware ranges from a few milliseconds to a few

hundred milliseconds [12]. Such frequent channel switching adversely affects the end-to-end

delay performance of the WMN [13]. Routing in MCMR networks is closely related to

channel assignment [14]. Researchers have studied the problem of routing and channel


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assignment in MCMR [15-20]. In [21] the delay and throughput performance of multi-

channel wireless infrastructure networks was evaluated with ring and grid topologies. Their

analysis is based on the transmission range, interference range and sensing range. In [22] the

capacity of a multi-channel multi-radio wireless networks using linear programming. The

work of [23] was extended to model the throughput gain of network coding in two way, star,

and general network topologies [24]. The authors of [25] examined the queuing delay of a

MCMR WMN under various channel fading conditions.

3. Network Model

An arbitrarily distributed wireless mesh network with nnodes can be defined by a directed

graph, G= (V

,E

):Where Vis the set of vertices representing nodes of WMN; Eis the set of directional edges

representing radio links between the nodes.

Let dijthe distance between nodes, iandj, where each node is equipped with radio, which

has: rttransmission range and riinterference range; with constraint ri> rt.

There exists a link {i,j} between nodejand kprovided.

djk ri and ij

Thus, the link between two neighbor nodesjand k of WMN is represented by the directed

edge.

{i,j} E

A nodej can successfully transmit to node kif the following two conditions are met.

a) dij rt (1)

b) dkj rikwhere nkis the neighbor node. (2)


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Figure 2. Nodes Constraint Diagram

Fig. 2 shows presence of six nodes in WMN. When node 2 is transmitting and if node 4

wants to transmit it cannot transmit due to (1) and (2). Similarly, nodes 1 and 2 cannot,

whereas node 5 and 6 can, transmit. Fig. 2 also shows that node 4 will cause interference if it

tries to connect. Based on the above approach, an interference graph Gican be constructed.

An interference graph can be represented by Gi= (Vi,Ei)

The vertex set is identical to the directed graph G representing nodes of WMN. There

exists a directed edge from nodejto node kif

a) a signal from nodejis strong enough to disturb node k but

b) it cannot be decoded correctly by k

So if there are two communication links {j,k} and {l,m} and if they are not able to transmit,

it indicates that there exists an edge between them. So an edge for the Interference graph G i

can be drawn between {j,k} and {l,m} based on the following conditions, i.e. djmrjor dlk

rl. With the help of Interference graph, Gi and vertex set Ei, an interference vector can bedefined between any given link say link {i,j} and all the links in E. If {k,l} {i,j} and there

is a link between link {i,j} and link {k,l} then I {i,j},{k,l} = 1 otherwise it is 0. Similarly,

Interference vector for all the links can be computed and an interference constraint matrix

|E||E| can be constructed. This constraint is shown by the Fig. 2.

4. Load balancing Interference Aware Routing Protocol (LBIARP)

LBIARP has been implemented with LBIARM [26] in AODV protocol. This protocol isbased on the best route discovery algorithm. It selects the route which has minimum


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interference, high throughput and low end to end delay. The algorithm is as follows:

Algorithm for best route discovery:

Source Node S Broadcasts to Gateway Node G

if (Intermediate Node I receives Route_Request) then

Calculate path load from S to I using the following equation:

i i i

i p i p

LBIARM (1 a) ETT a ETT * N

= +

Create a Reverse Route to S

If Route_Request is duplicate discard Route_Request Packet.

if (I is D)

unicast Route_Reply to S.else

rebroadcast Route_Request

endif

if (I receives Route_Reply) and (I is not S) then

I forward Route_Reply to S

else

S updates path load.

endif

if (S does not receive Route_Reply for a certain time period t) then

S broadcasts (Route_Request_Error)

endif

ifI receives Route_Request_Error and (I is not G)

forward Route_Request_Error.

elseG updates its links_table.

G sends Route_Request to D

endif


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5 Performance Evaluation

5.1 Simulation Environment

The performance evaluation of MCMR was done by simulating it with OPNET Modeler 17.1

PL1. MCMR was implemented in the LBIARP protocol and compared with the classic

WMN using Single Channel Single Radio (SCSR). The network topology as shown in Figure

3 was used for simulation. It consists of 16 static mesh routers uniformly randomly placed in

a 4 X 4 grid in a 1000 X 1000m2area. The average distance between each pair of two one

hop nodes is the same. The interference range is set to be approximately equal as all mesh

routers are with similar transmission powers. The source nodes send Constant Bit rate (CBR)

traffic with UDP as transport protocol, consisting of 512 byte packets with a sending rate of

20 packets/second. The center mesh router was selected as the Gateway node. The following

simulation parameters were used (Table 1)

Table 1: Simulation Parameters

Parameter Value

Network Scenario Campus Network

Network Grid 1000 X 1000

Number of Nodes 16

Number of radios 2

Number of Channels 4

Packet Size 512

Interference range 40 m

Traffic Model Constant Bit rate (CBR)

Path Loss Model Two ray

Transmission Power 10 mW

Queue size at Routers 50 Kbytes

Physical layer protocol PHY 802.11g

CBR senders rate 20 packets/sec

Transmission rate at

Physical layer

54 Mbits/sec


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Figure 3. Node placement with 16 nodes in 1000m x 1000m

5.2 Performance Metrics

For the evaluation following metrics were used.

Packet Delivery Ratio:This is the ratio between the number of data packets successfullyreceived by the destination node and the total number of data packets sent by the source node.

This metric reflects the degree of reliability of the routing protocol.

End-to-end delay of data packets: This is the delay between the time at which the data packet

originated from the source and the time it reaches the destination, and includes all possible

delays caused by queuing for transmission at the node, buffering the packet for a detour,

retransmission delay at the MAC layer, propagation delay and transmission delay. This

metric reflects the quality of routing protocol.

Throughput: This is defined as the amount of data that is transmitted through the network per


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unit time (i.e. data bytes delivered to their destinations per second).

5.3 Simulation Results and Analysis

5.3.1 Packet Delivery Ratio

Figure 4 shows the percentage of the packet delivery ratio between MCMR and SCSR in

presence of interfering traffic arising from the interfering nodes. From the below figures, it is

observed that when the traffic load is light (10 - 20 packets/s). Both the algorithms perform

almost similarly as there is less medium contention and usage. A single channel would have

been adequate for this case. When the traffic load is moderate to heavy (above 40 packets/s),

the MCMR advantage is clearly observed, which leads to MCMR outperforming with the

increase in traffic Load. For instance, under heavy load, 70 packets/s, the PDRs of MCMR

and SCSR are 82% and 35% respectively, a difference of 47%.

Figure 4. Packet Delivery Ratio vs. Traffic Load

5.3.2 End to End Delay

Figure 5 shows the end to end delay. It is observed MCMR performs better than SCSR. There

is a significant difference between them. This is due to the balancing act of MCMR, which

minimizes interference due to the selection of an optimum route. This route is based on less

interference taking into consideration varying traffic load. When the traffic load is increased,


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it increases the end to end delay. MCMR improved the end to end delay as it balances the

traffic flows and avoids congestion causing less delay.

Figure 5 End to End Delay vs. Traffic load

5.3.3 Throughput

Figure 6 shows throughput comparison between MCMR and SCSR in presence of interfering

traffic arising from the interfering nodes. The throughput in MCMR is greater because SCSR

creates congestion areas. At each hop, there is a delay of data packets. MCMR creates quality

links with fewer delays, which are less loaded. As the number of channels increases, the

throughput increases. The higher the number of channels, the less time spent contending for

the medium to create congestion areas. It is seen that MCMR performs better than SCSR


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Figure 6 Throughput (average) vs. Traffic Load

Conclusion and Future Work

A common problem in WMN is the performance degradation with multiple hops. This is due

to Interference of the neighbors and varying traffic load. This is a critical issue in WMN.Performance of WMN is degraded as the number of nodes increases. In this paper, to enhance

the performance of WMN, an attempt has been made to incorporate MCMR in WMNs.

Simulation results indicate that the results obtained by using MCMR enhances the

performance significantly. In the future, it will be interesting to see the performance after

implementing multicasting in MCMR WMNs

ACKNOWLEDGEMENTS

This research is supported by the Deanship of Scientific Research, College of Engineering,

King Saud University.

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*Corresponding author: Mohammad Siraj

PSATRI, College of Engineering,

King Saud University, P.O.Box 800, Riyadh-11421, Saudi Arabia,

Email: [email protected]

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Minimizing Interference in WMN