Efficient Scalable Clustering Scheme forPseudolinear Mobile Ad hoc Network

Mahfida AmjadInstitute of Information TechnologyUniversity of Dhaka, BangladeshEmail: mahfidaamjad@live.com

Ambreen ZamanInstitute of Information TechnologyUniversity of Dhaka, Bangladesh

Email: ambreen.zaman@yahoo.com

Kazi SakibInstitute of Information Technology

University of Dhaka, BangladeshEmail: sakib@univdhaka.edu

Abstract—One hop clustering scheme in MANET adopts thesimple shortest path for packet transmission mechanism bytrading off the cluster maintenance overhead. However, as themaintenance overhead increases the network scalability becomesvulnerable. Instead, a Two Hop clustering in Pseudolinear Mobilead hoc network (THPM) is proposed for providing betterscalability with minimum overhead. THPM also incorporates animportant parameter, mobility since mobile devices on the movehave a great impact on the network structure. Node mobilityhas been taken into account in terms of the average clusterheadlifetime of clustermembers. Here, the clusterheads are selectedbased on node stability, which has been calculated using doplervalue. Simulation result shows that the clusters created by THPMretain more uniform cluster size, clusterhead lifetime and morenodes in each cluster up to 45∼50% than the existing technique.

Index Terms—One hop clustering; Clusterhead; Clustermem-ber; Pseudolinear Mobile Ad hoc Network; Doppler value.

I. INTRODUCTION

It is obvious that the topology changes dynamically inMANET. If the network has a flat topology1, the size of therouting table is proportional to the number of nodes in theentire network. A flat structure encounters scalability problemswith increased network size, especially for the node mobility.As the network size increases, communication costs consumea large proportion of the bandwidth. If the rate of the networktopology changes increases, the exchange of routing tablesbetween neighboring nodes must be more frequent. Otherparameters such as node density and traffic load, can alsoimpair network scalability.

Hierarchical routing2 is an interesting solution for building ascalable network. One promising approach to build hierarchyamong the nodes is clustering. The number of hops of themobile nodes is an important issue in cluster based MANET.Most researches have focused on single hop clustering, whichallows simple local management within each cluster [2], [3],[4], [5], [6]. However, with the increased network size andnumber of mobile nodes, one hop clustering creates manysmall clusters. These clusters are likely to be broken whenmobile nodes move out of their cluster’s coverage. MOBIC [3]is a one hop clustering algorithm that minimizes the influenceof mobile nodes’ movement on cluster topology by tightening

1All nodes are treated equally [1]2Only selected nodes take the responsibility of routing [1]

the connection between mobile nodes residing in the sameclusters. It is effective for MANETs with group mobilitybehavior, but performance of this scheme may be degradedif mobile nodes move randomly.

There are some multi hop clustering schemes for MANET[7], [8], [9]. But there is no such remarkable clustering schemefor Pseudolinear Mobile Ad hoc Network [10]. The mobilenodes which move in a relatively linear path without frequentlychanging its direction and motion parameters, for example,aircraft, ships, trains, and cars on highways are called pseudolinear mobile entity, and the communication among the pseudolinear mobile entities is known as Pseudolinear Highly MobileAd hoc Network (PHMANET)[10]. It focuses on a clusteringtechnique for the nodes with slow changes of node’s movingdirection and speed. If mobile nodes change its mobility pat-tern frequently, the performance of this clustering scheme maydegrade. This clustering technique considers single hop, whichcauses frequently change of clusterheads and the diameter ofeach cluster is also small.

Compared to one hop [10], two hop clustering is morescalable for large scale PHMANET as it groups all nodes inthe network with a small number of clusterheads. To form astable cluster network this paper proposes a two hop clusteringscheme for PHMANET, named as THPM. Moveover, it isnot restricted on speed and direction. In THPM, nodes movetoward a random destination at their own random speed ofmovement. It uses stability metric, Doppler Value (DV) forclustering. DV is based on the relative velocity between nodesobtained from the Doppler shift of control packets exchangedbetween nodes during the clustering process. The smaller DVof a node means lower mobility and, hence, higher stabilitythan its neighbors and this node has the quality of being theclusterhead in THPM. Although there are many topology con-trol algorithms for MANET [11], THPM develops an efficientequation for calculating two hop neighbors for forming a twohop cluster in the network. It develops the equation based onEuclidean distance by ignoring direct link between two nodesand excluding the self node.

The result analysis shows that, in THPM, no matter whatthe node velocity is the average number of clusters are about45∼50% less than the existing technique. In case of averageclusterhead lifetime of holding nodes, it shows that whenthe number of nodes increases, the lifetime of each cluster

978-1-4244-6252-0/11/$26.00 ©2011 IEEE

also increases. Because, if the network becomes dense, thereis more possibility to stable as a clusterhead. The averagenumber of nodes in each cluster in THPM is almost twice thanPHMANET as it considers two hop and the existing methodconsiders one hop.

II. PROPOSED THPM METHOD

This section describes the proposed THPM method. Themechanism for calculating the two hop neighbor has beendescribed below-

Fig. 1. Two hop neighbor calculation

Let, each node in Fig. 1 knows its one hop neighborinformation (based on Euclidean distance). Then, the One HopNeighbor (OHN) lists of each node are –

OHN(A)={B,F,G};OHN(B)={A,C};OHN(C)={B,D,G};OHN(D)={E,C,G};OHN(E)={D,F,G};OHN(F)={E,A,G};OHN(G)={A,C,E,F,D};

Now, Two Hop Neighbor (THN) of node E will be –

THN(E) = [OHN(D) − OHN(E)] ∪ [OHN(F )−OHN(E)] ∪ [OHN(G) − OHN(E)] (1)

THN(E) = [OHN(D) − OHN(E)] ∪ [OHN(F )−OHN(E)] ∪ [OHN(G) − OHN(E)]= [{E,C,G} − {D,F,G}] ∪ [{E,A,G}−{D,F,G}] ∪ [{A,C,E, F,D} − {D,F,G}]= [{E,C} ∪ {E,A} ∪ {A,C,E,D}]= {A,C,E,D}

By excluding the self node and by ignoring thedirect link between the nodes, THN(E) = {A,C}In the same way, THN(A) = {C,E,D} . Let,Set of Nodes (U) = {U1, U2, ..., Un} , and list ofOHN(Un) = {V1, V2, ..., Vn} . Then, the general formof equ.(1) for calculating THN of a node is –

THN(Un) = [OHN(V1) − OHN(Un)] ∪ [OHN(V2)−OHN(Un)] ∪ ...[OHN(Vn)−OHN(Un)] (2)

Where, Un �= Vn and no direct link between Un and Vn.Finally, applying the above equation THPM has been devel-oped. It considers two phases, these are –

A. Initial Cluster Formation for Two Hop Neighbor

In [10], a one hop clustering scheme has been used for theinitial cluster formation. It is assumed that all participatingnodes in the network are initially in the NULL state whichmeans the role3 of the nodes yet to be defined. The DopplerValue (DV) of the Hello messages of each node is calculatedby first measuring the Doppler shift of the Hello messages. Therelative velocity of two mobile nodes related to the Dopplershift is as follows:

V = C[(F/F0) − 1] (3)

Where,V = Relative velocity between two communicating nodesC = Speed of lightF = Expected frequency of the signal/packet andF0 = Observed frequency of the signal/packet

DV is related to the relative velocity of two nodes whiletaking into account the effect of approaching and recedingnodes. DV has been calculated by the following equations –For approaching nodes,

if (F/F0) < 1; then DV = C|V | (4)

For receding nodes,

if (F/F0) > 1; then DV = 2C|V | (5)

For approaching nodes, the observed frequency turns out tobe smaller than the expected frequency. For receding nodes,however, the observed frequency is greater than the expectedfrequency. Receding nodes are considered half as stable asapproaching nodes, as nodes that are approaching generally bewithin communication range of each other for twice as long asnodes that are receding from each other. The DVs of all thereceived Hello messages are stored at each node. These arethen used to calculate the Sum of the DVs (DVS). The DVSreflects the relative stability of the node with respect to itsneighbors as it defines the relative mobility based on the DVof the nodes. A smaller DVS will result in lower mobility and,hence, higher stability of a node with respect to its neighbors.

1) The algorithm of THPM: The step 1 of Algorithm1, each node broadcasts a HELLO message to its THNsindicating its existence in the network. HELLO receivingnodes calculate the DVS and broadcasts to its THNs in step2. In step 3, the DVS receiving nodes compare R DVS withits O DVS and if its O DVS is less than R DVS, it broadcastsClusterHeadClaim (clusterID, O DVS) to its THNs. Contain-ing smallest O DVS node will be the ClusterHead and hereclusterID is equal to the nodeID of the clusterhead claimingnode. Upon reception of the clusterhead claim packet, a nodemay choose to join the cluster. Once a node wishes to join acluster, it sends a JoinRequest(clusterID, nodeID) message andthe clusterhead then sends a JoinAccept (clusterID, nodeID)message to the requesting nodes which are stated in step 4 andstep 5 of the algorithm. Finally in step 6, the accepted nodesby the clusterhead joins the cluster and periodically broadcasts

3The role of the nodes may be as clusterhead or clustermember.

Data:State: NULLNode Identifier: nodeIDOne Hop Neighbor: OHNTwo Hop Neighbor: THNSet of Nodes (U): U1, U2...Un

OHN (Un) list: V1, V2, ..Vn

Sum of Doppler Values: DVSOwn DVS: O DVSReceiving DVS: R DVSMessage Type (Packet): HELLO, DVS,ClusterHeadClaim, JoinRequest, JoinAccept,ClusterMember

Step 1: [Each Node]Broadcast HELLO (nodeID, NULL) to its THNs usingequ. (2)THN(Un) = OHN(V1) − OHN(Un) ∪ OHN(V2) −OHN(Un) ∪ OHN(Vn) − OHN(Un)Step2: [HELLOs Receiving Nodes]Calculate DVS of HELLOsBroadcast DVS (nodeID, DVS) to their THNsStep 3: [DVS Receiving Nodes]Compare R DVS with O DVSIf O DVS < R DVSBroadcast ClusterHeadClaim (clusterID, O DVS)to theirTHNsContaining smallest O DVS node will be the ClusterHeadStep 4: [ClusterHeadClaim Receiving Nodes]Can wishes to join the clusterSend JoinRequest (clusterID, nodeID)Step 5: [ClusterHead]Sends JoinAccept (clusterID, nodeID)Step 6: [Request Accepted Nodes]Join the cluster & periodically broadcastsClusterMember (clusterID, nodeID)

Algorithm 1: Initial Cluster Formation Algorithm (THPM)for Two Hop Neighbor

a ClusterMember (clusterID, nodeID) notifying its state, andits associated cluster of its presence.

B. Progressive Cluster Maintenance

The cluster maintenance is very important to keep a stablecluster structure. For this THPM has an effective mechanismfor node activation and deactivation.

1) Node Activation: The primary objective of node acti-vation is to detect an adjacent node and to join a cluster.Every mobile node in the network monitors its neighboringnode through Hello packets. When a non member node comesclose to its cluster or switches on its power inside the cluster,it becomes activated. On receiving Hello packets from a newneighboring node, the non member node tries to join within atwo hop range cluster using the Algorithm 1.

TABLE IA COMMON SET UP VALUES FOR SIMULATION

Property ValueMAC 802.11

Radio Propagation Model Free space modelRouting Protocol AODV

Traffic Pattern CBRMaximum Packet 50

Packet carrying bytes 1024

TABLE IIVELOCITY OF 10 NODES

Node Velocity0 192.681494025830891 346.763533468713772 396.746336667214683 155.538472419389764 125.631253992035655 461.258168779899456 242.550155028025677 262.387205968791258 419.525156225788019 375.11132558580084

2) Node Deactivation: When a node leaves from its clusteror switched off its power at that time deactivation occurs. Amember node that does not receive periodic broadcast from aclusterhead for a certain threshold value of the round trip timewill disassociate itself from that cluster, then the clusterheadremoves the member from its list of members. If a nodeis not part of any cluster, loses the path for connecting theoriginal clusterhead or the distance between the clusterhead isfar enough to join the cluster, it begins broadcasting periodicjoin request message to find a new cluster to join. In this case,the node selects a new clusterhead which is able to connectthe two hop cluster members.

III. SIMULATION AND PERFORMANCE ANALYSIS

To simulate THPM and to compare its performance withPHMANET, Network Simulator version 2.34 (NS2) has beenused. The network simulation carried out in flat grid topog-raphy for tracking the movement of mobile nodes within anarea of 1000X1000 meter and the number of nodes is between10 and 40. A Set up values for the simulation has been givenin Table I and the sample of each node’s random speed isgiven in Table II. The performance of THPM in compare toPHMANET has been described below.

Fig. 2 shows, as the number of nodes increases, the pos-sibility of forming clusters also increases in both cases. InTHPM, average number of cluster is about 45∼50% less thanthe existing technique, no matter what the node velocity is andfor that the possibility of forming the clusterhead decreases.This is because THPM selects the most unique node as aclusterhead, in terms of node ID, remaining battery, degreeand holding time of each node, where as PHMANET uses thenode ID and node degree.

Cluster stability is defined by the lifetime of the clusterhead,which stays in the head status without any interruption. Thecluster life time starts when the clusterhead is selected and

Fig. 2. The average number of clusters

ends when it is switched off or exited from its cluster.Fig. 3 shows that, when the number of nodes increases, thelifetime of each cluster also increases. Because, consideringclusterhead in THPM, holding time of each node is alsoconsidered as a parameter.

Fig. 3. The average clusterhead lifetime of holding nodes

Fig. 4 shows the average number of nodes in each clusterconsidering the number of nodes in the network. As thenumber of nodes increases, the degree of nodes also increases.In THPM the average number of nodes in each cluster isalmost twice than PHMANET.

Fig. 4. The average number of nodes in each cluster

IV. CONCLUSION

This paper proposes an efficient scalable two hop clusteringscheme THPM for pseudo linear mobile ad hoc network. The

TABLE IIIPERFORMANCE RESULTS AT A GLANCE

No.ofnodes

Avg. no. of clus-ters

Avg. clusterhead lifetime ofholding nodes

Avg. no. ofnodes in eachcluster

PHMANET THPM PHMANET THPM PHMANET THPM10 4 2 1.531475 2.2503 3 620 8 4 3.98 4.08 5 1130 13 7 4.68 5.38 8 1340 15 9 5.08 6.23 10 18

performance summary of THPM is given in Table III. Thediameter of cluster increases with the increase of hop count. InTHPM, two hop is considered to improve the performance ofcluster, which has longer clusterhead duration and less controloverhead, indicating that cluster stability and scalability areenhanced substantially. The result analysis states that THPMperforms more than 45∼50% better than the existing method.

THPM does not deal with k-hop clusters. Energy powerand the waiting time for receiving packets of each node hasnot been taken into account as parameters to improve theperformance of clusterhead. To get a more stable clusteringscheme, an enhancement to remove these limitations will becarried out.

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