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A NOVEL CLUSTER FORMATION ALGORITHM FOR AD

HOC NETWORK

Ghaidaa Muttasher Abdulsaheb1, Associated Prof. Dr. Norrozila Sulaiman

2 ,

Osama Ibrahem Khalaf3

PHD Candidate at Faculty of Computer Systems & Software Engineering, Univer

sity Malaysia Pahang, 26300,Kuantan, works at university of Technology,Iraq 1

Faculty of Computer Systems and Software Engineering,University Malaysia

Pahang,26300,Kuantan2

PHD Candidate at Faculty of Computer Systems & Software Engineering, Univer

sity MalaysiaPahang, 26300,Kuantan, works at AlNahrain university, Iraq 3

Abstract: The mobile ad-hoc network has become one of the most important

networks because of its easy construction, which does not require any pre-fixed

infrastructure. However, clustering is difficult to apply in this type of network

because of the dynamic network topology, which complicates cluster formation,

maintenance, and route discovery. Therefore, the current study suggests a new

cluster-based formation routing algorithm, which is used in a new proposed

routing protocol namely, the new cluster routing protocol (NCRP), which is

proposed a new algorithm for cluster formation, it also uses a new, modified

algorithm to calculate the scale of nodes. This scale selects a cluster head

according to many parameters, such as the storage capacity, load distribution,

accumulative time, available power, number of neighboring nodes, the movement

of each node, and the distance among nodes. Results confirm that the proposed

algorithm can reduce end-to-end delay, the number of dropped packets, and

normalized control overhead. Furthermore, the throughput and the packet delivery

ratio are increased, as reflected significantly in the routing protocol.

Keywords: clustering, ad hoc, routing algorithms, cluster-based routing protocols,

K-algorithm. 1. INTRODUCTION The mobile ad-hoc network consists of a number of wireless mobile nodes that are

self-organized and do not require a constant structure. The movement of the nodes

enables them to generate multiple routes [1]. Thus, accurate routes must be

determined for these nodes. A new algorithm must therefore be developed to

design a routing protocol that adapts to network topology changes. The ad-hoc

network contains many kinds of routing protocols, namely, reactive (on demand),

proactive (table driven), and hybrid routing protocols. In the reactive routing

protocol (AODV), a route is created only as needed. In the proactive routing

protocol (DSDV), the route is prepared in advance, and the details are listed in a

specific table [2]. The hybrid routing protocol combines the two previous types of

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routing protocols. This type of routing protocol is used in clustering. A cluster

uses the DSDV to locate internal paths, whereas the AODV is employed to

determine routes to other clusters [3].

2. RELATED WORK

Many studies have been conducted to increase the performance of the routing

protocol. Kun-Won et al. [4] suggested a new and secure routing protocol for

sensor networks that combines the traditional routing protocols with security

routing protocols through encryption and decryption methods in the design

process. The results of this study suggest that the new protocol is more effective

and it is recommended over previous routing protocols than previous routing

protocols.

Rezaee et al. [5] established a new cluster-based routing protocol for use in the

ad-hoc network. It depends on the cluster formation to increase the packet

delivery ratio (PDR) and to minimize end-to-end delay. The cluster head (CH) can

be modified if the original node is damaged in the suggested method. The new

node is used to send data, thus minimizing the probability of error.

Jason et al. [6] proposed a new cluster routing protocol (CBRP) for a mobile ad-

hoc network. It applies a specific algorithm to select the gateway node and limits

this selection according to the weight and energy of the nodes. The simulation

results of this study indicate that node selection significantly reduces energy

consumption and improves the quality of the routing protocols.

Rashed et al. [7] presented a new two-layer hierarchical routing protocol that is

the modified form of the low energy adaptive clustering hierarchy (LEACH)

protocol. The main concept behind this design is the use of the number of CHs

and the number of sensors to aggregate the cluster information obtained from the

receiving node. The simulation results of this study show that the new routing

protocol consumes reduced amounts of energy and limits the time delay in data

transfer.

Pandi et al. [8] proposed a new cluster ad-hoc routing protocol that depends on

multiple sources and multicast features to enhance the performance of the

proposed protocol. The original weighted cluster algorithm was simply modified

for this purpose. The simulation results suggest that the new routing protocol

generates a high PDR; however, the maximum number of the normalized control

overhead is excessive.

Dongfeng et al. [9] designed an efficient cluster-based routing protocol for sensor

networks. The main principle behind this approach is reflected in CH selection;

each node can elect itself as a CH. The simulation results confirm that this new

routing protocol is better than the LEACH and CROSS routing protocols in terms

of energy consumption and end-to-end delay.

3.CLUSTERING Clustering is one of the most familiar mechanisms. It gathers numerous nodes into

many sets called clusters to reduce loads in connections and to eliminate power

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consumption in large networks. In the clustering structure, each cluster has one

node that is regarded as the CH. This node manages the selection of an

appropriate path for any node in a particular cluster. In addition, this node

possesses complete information about all of the nodes in the cluster. This

information is stored in a member table. The other node that is used to connect

clusters is known as the gateway. The remaining nodes in the network are labelled

as ordinary nodes [10], as shown in Figure. 1.

Figure.1. Clustering structure

4. THE POROPOSED CLUSTERE FORMATION ALGORITHM The main concept of the proposed algorithm involves modifying the k-hop

algorithm to enhance its performance. The k-hop algorithm calculates the weight

of each node without considering scalability, network stability, storage space,

processing power, and node distribution in the available area [load distribution

(LD)]. By contrast, the proposed algorithm takes all of these factors into account

and calculates the scale based on them. As shown in Fig.2. The main steps in

cluster construction are as follows:

Step 1: Each node sends a “hello” message to all other nodes to inform them of its

existence.

Step 2: The CH is selected by determining the node with the highest scale, this

step is applicable only to the node that has not been selected previously as a CH.

The scale is calculated according to the following parameters:

1- The storage capacity (SC) of the node is calculated.

2- The LD of each node is computed using the following formula:

LD =│ Ni - CS│.

Given that Ni is the number of neighbor nodes and CS is the cluster size,

the LD value helps assess the number of nodes that can be treated.

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3- Accumulated time T is calculated to reflect the summation of the period spent

by the node in the cluster. If this value is high, then the node is more fixed

than the others. This node enhances the stability of the entire cluster.

4- With respect to the number of the closest node F, a new node can be added to

the list of closest nodes under a condition. Each node should not include the

new node in its neighbor list unless it confirms that the energy of the most

recent message received from this specific node is higher than that of the first

message received from the same node. This validation ensures that the node is

close to the ones on the list. Consequently, the cluster area is reduced.

Moreover, this process helps shorten the time required for CH selection given

that the area is limited.

5- The distance between a particular node and all closest nodes listed in the

aforementioned list must be determined using the following formula:

DIS = DIS(n,n1) + DIS(n, n2) + DIS(n,n3) +………….+ DIS(n,nn) . 6- The available power of each node, which is referred to as APOW, is

calculated.

7- The movement of each node, which is denoted as MOV, is computed with the

following formula:

Mov = 1

𝐷(√(𝑚2 − 𝑚1) + (𝑛2 − 𝑛1)

given that D = D2 - D1,

where m1, n1 and m2, n2 are the coordinates of each node at times D2 and D1.

8- The scale of each node is calculated based on the aforementioned

parameters using the following formula:

S = a1SC+ a2 LD + a3 T+ a 4 F - a 5 DIS+ a 6 APOW- a7 MOV.

a1, a2, a3, a4, a5, a6, and a7 are the coefficients used in scale calculation. The

summation of these coefficients is equal to 1, and the important factors are

assigned high values. For example, available power is considered to be more

important than LD. Thus, its coefficient is higher than that of the LD.

Step 3: The node with greatest scale is selected as the CH. This node sends a

message to all other nodes to inform them that it has been selected as a CH node.

Step 4: Each node periodically sends a message to all other nodes in the cluster.

This message contains the following: node ID, request type, scale, and working

period.

Given that:

- Request type: “CH” indicates that the sender is the CH, “WCH” suggests

that the sender aims to be the CH, and “E” implies that the sender is the CH but

that it aims to cease its operation because it has identified a new node whose scale

is greater than its own.

- Scale: the weight of the node.

- Working period: It denotes the period of time for which the CH operates

as such. If it has a high value, then it must be replaced with a new one because its

scale is reduced by time.

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Thus, the sender of WCH waits for a specific period of time. If it receives a

response from the CH that contains the CH scale and the working period, then the

sender node behaves as an ordinary node. The same is true if its scale remains

greater than that of the sender and its working period is short. Then, the sender of

WCH repeats the request after a specific period of time. But if its scale is greater

than the current CH and if the working time of the current CH is long, then it

declares itself as a CH. The new CH sends a message that contains the following:

node ID, CH, scale, and 0. This exchange of CHs helps reduce the overhead of the

entire network and distributes the burden among all available nodes. This

distribution is reflected positively in routing protocol performance.

Step 4: If two nodes are of the same scale, then one of them is chosen as the CH.

The other one is utilized as a gateway to connect to external clusters.

5. SIMULATION PARAMETERS AND SETTING This study measured the effect of using the new formation method which is used

in NCRP, the NCPR is compared with Cluster Based Routing Protocol(CBRP)

which is used the old method of formation .The new method was analyzed based

on QoS parameters, such as the average throughput, PDR, average end-to-end

delay, and number of dropped packets. The simulation results were obtained

through a network Simulator 2 (i.e., NS2). The source and destination nodes in the

proposed network had a random movement. The mobility model had a square area

of 1500 m × 1500 m; the simulation time was 150s.

6. PERFORMANCE METRICS 1) Average throughput: This parameter is determined by calculating the ratio of

the received data to the simulation time, or the ratio of the received video to the

number of data packets, which is generated to correct the error and to obtain

the best throughput. Each error in the network must be corrected without need

for retransmission. The average throughput is always measured in bit/second or

data packets/time slot.

2) PDR: This parameter is determined by dividing the total number of received

data packets by the total number of the sent data packets. This ratio is

employed to reflect the scale of the delivered data to the destination node .

PDR = ∑ Total number of delivered packets

∑Total number of sent packets

3) End-to-end delay: This parameter is a very significant parameter,

particularly in real-time data transmission. It is determined by calculating the time

spent by the sent packets to reach the receiver nodes and by summing up all the

differences between the time spent for sending the data and that for receiving the

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data. If the value of the end-to-end delay is small, then the network status is good,

and vice versa.

End-to-End Delay = ∑ (Ds1 − Dr1) + (Ds2 − Dr2) + ∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙ + (Dsn − Drn)

where:

- Ds is the time spent for sending the packet data

- Dr is the time spent for receiving the packet data.

4) Number of dropped packets: When a packet reaches a network layer, it is

sent to the destination node if a correct route is identified. Otherwise, the packet is

buffered until the appropriate route by which to reach the destination node is

discovered. If the buffer is full, then the packet is dropped [11].

7. RESULTS AND DISCUSSION

1) Average Throughput:As depicted in Figure .2, the throughputs of the

two routing protocols decrease as node mobility increases. The main reason for

this decrement is that the increment in speed increases the distance between the

nodes. Thus, the number of the packets received in the destination node is

minimized. Throughput value is maximized when NCRP is utilized, followed by

the use of CBRP, the improvement in throughput which is resulted from using

NCRP is between (60 to80 Kbps), The main reason for the high throughput value

of NCRP is because of its resulted in increasing the number of packets per time

slot, which is considered a good indication for its performance.

Figure 2: Throughput for NCRP and CBRP versus speed

2) PDR: As shown in Figure .3, and NCRP performs well in this respect; its

PDR is more than (96%) in all cases of node speeds, and the PDR ratio is

increased as the speed of nodes decreased, this ratio reaches to more than 97% as

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mobility less than 8 m/second, as depicted in Fig. 3. The difference between PDR

of NCRP and that of CBRP is between (4 to 7 %), which is means that the

proposed formation method can increased the number of the corrected received

packets with respect to the number of sent packets.

Figure 3: PDR for NCRP and CBRP versus speed

3) End-to-end delay: As shown in Figure .4, end-to-end delay increased

linearly as the mobility (speed) of the nodes increased in both routing protocols.

The main reason for this increment is the reconstruction time of the cluster. When

the nodes move quickly, they require additional time to join with another cluster.

The NCRP has shown minimum delay than CBRP, and the differences between

the NCRP and CBRP are between (47 to 65 msec). The main reason behind these

improvements is proved the success of the proposed cluster formation algorithm

and selection the CH algorithm.

Figure 4: End-to-end delay for NCRP and CBRP versus speed

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4) Number of dropped packets : As indicated in Figure.5, the number of

dropped packets increases with node speed in NRCP and CBRP routing protocols.

This number is minimal in NCRP and increases slightly with node speed. The

difference between the number of dropped packets in the NCRP and those in

CBRP routing protocols ranges between (2 to 5) packets. This range is considered

very large in this respect, and it can significantly affect the performance of the

routing protocol.

Figure 5: Number of dropped packets for NCRP and CBRP versus speed

8. CONCLUSIONS This study suggests a new developed formation algorithm which is used in

new cluster based routing protocol which is called NCRP, this study has

calculated the quality parameters and compared it with CBRP which is considered

the highest performance cluster based routing protocol, the proposed NCRP

follows a special criteria with respect to CH selection, this criteria used different

factors to find the scale of the each node and use this node as the CH which is

responsible for all the management and communication processes, this criteria is

proposed in order to enhance the stability of the cluster and the life time of the

entire network and that reduce power consumption. The simulation results show

that this proposed algorithm can be increased the throughput by increasing the

number of the received packets in a specific time slot, and it also improve the

PDR value which means that the proposed protocol enhances the stability of the

cluster. So that, all the cluster members is remained in a stable state for as long as

possible. This occurrence increases the ratio of the received packets with respect

to the sent packets.

The simulation results also show that this new protocol can significantly

minimizing the end-to-end delay , this minimizing is produced as a result of its

criteria in transitioning between a number of CHs, which is resulted in

minimizing the congestions and link failures problem.

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The number of dropped packets by using this proposed algorithm is also

decreased, the main reason behind this reducing is that the new criteria is based on

the select the node with high memory capacity as the CH, which is minimized the

number dropped packets, because the existence of the enough memory, so there is

no need to buffer the packets until the next transaction.

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