1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-
6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
308
CLUSTERING BASED PERFORMANCE IMPROVEMENT STRATEGIES
FOR MOBILE AD-HOC NETWORK
Mr. Rahul A Jichkar1
, Dr. M.B.Chandak2
1
M.Tech Scholar, CSE Department, SRCOEM, Nagpur, India
2
Associate Professor and Head, CSE Department, SRCOEM, Nagpur, India
ABSTRACT
Mobile Ad hoc Networks (MANETs) consist of a large number of relatively low-powered
mobile nodes communicating in a network using radio signals. Clustering is one of the techniques
used to manage data exchange amongst interacting nodes. Each group of nodes has one or more
elected Cluster head(s)(CH), where all Cluster heads are interconnected for forming a
communication backbone to transmit data. Moreover, Cluster heads should be capable of sustaining
communication with limited energy sources for longer period of time. Misbehaving nodes and cluster
heads can drain energy rapidly and reduce the total life span of the network. According to that, this
paper presents reviews of most clustering techniques that improves the power conservation in
mobile ad hoc network and increase the battery usage in ad hoc wireless network devices and
conserve the power energy consumption.
Keywords : Mobile ad-hoc networks, Clustering, clusterhead, gateway.
1. INTRODUCTION
In an ad hoc network, mobile nodes communicate with each other using multihop wireless
links. The infrastructure is completely is dynamic; for instance, there are no base stations. Each
node in the network also acts as a router, forwarding data packets for other nodes. A research
issue in the design of ad hoc networks is the development of dynamic routing protocols that can
efficiently find routes between two communicating nodes. The routing protocol must be able to
keep pace with the high degree of node mobility that often changes the network topology.Also,
nodes heterogeneity must be taken in to account, since nodes may have variety of available
resources, and this produces different level in their roles within the network. The Solution for
nodes heterogeneity is the Cluster-Based Routing which also limits the amount of routing
information that propagates inside the network. The concept behind clustering is to divide the
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING &
TECHNOLOGY (IJCET)
ISSN 0976 – 6367(Print)
ISSN 0976 – 6375(Online)
Volume 4, Issue 4, July-August (2013), pp. 308-314
© IAEME: www.iaeme.com/ijcet.asp
Journal Impact Factor (2013): 6.1302 (Calculated by GISI)
www.jifactor.com
IJCET
© I A E M E

2. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-
6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
309
network nodes into a number of overlapping clusters. This gives clustering the ability to make a
hierarchical routing in which paths are recorded between clusters instead of between nodes. The
remaining part of this paper shows briefing about the clustering concepts and in later sections it
shows some clustering algorithms that applied in MANETs.
2. CONCEPT OVERVIEW
Most of the researchers defined Mobile Ad Hoc Networks (MANETs) as a self-configuring
network platform of mobile computing devices connected by wireless links. Towards this, many
challenges appear to face this kind of network, such as route discovery and maintenance. Almost, all
devices in mobile ad hoc networks has same prosperities i.e. usage, batteries, power consumption
with respect to transmission range, type of application running on each device, location,etc, all make
power usage as standard factor that specify the device lifetime which indicate the overall
network lifetime. Since, MANET operates on either rechargeable or replaceable batteries. Even
though it must works with respect to the absence of infrastructure that come from the type of
applications which make the construction of this kind of network an important issue [1], [2]. Some
concept reduced the energy consumption level by providing routing Discovery process with
single path in MANET as mentioned on DSR (Dynamic Source Routing)[3] and AODV (Ad-hoc
On Demand Distance Vector Routing)[4], even though others focus on multi-path outing protocol as
modeled in AODVM [5]. On the contrary, clustering technique is one of the most important
techniques that used to provide resource management in MANET [6]. Also, it influences the usage
of energy in this kind of network.
3. CLUSTER HEAD SELECTION
The feasibility of a clustering method can be primarily determined by the complexity
of the cluster head selection. Optimizing the cluster head selection allows for the network to
be more efficient by minimizing the signaling overhead while ensuring that the network
connectivity is maintained despite topology changes. In this paper, we investigate the problems
of cluster head selection for large and dense MANETs. Two variants of the cluster head selection are
examined: (1) the distance-constrained selection where every node in the network must be
located within a certain distance to the nearest cluster head; and (2) the size-constrained
selection where each cluster is only allowed to have a limited number of members.
4. CLUSTERING TECHNIQUES IN MANET
The most popular method that developed to provide resource management over mobile ad
hoc networks is clustering. This technique based on partitioning the network in smaller and
manageable groups each group called cluster [6]. Clustering offers several benefits when it used
with MANETs listed as following:
1. Enhances routing process and mobility.
2. Stabilizes dynamic network topology
3. Helps to perform more efficient resource allocation
4. Provides hierarchical routing architecture.
This techniques dividing nodes of a self-organized network like MANET into a number of
disjointed or overlapped clusters[7],[8]. Thereby, cluster based network defines three types of
node in MANET as shown in Fig. 1 and defined as follows:

3. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-
6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
310
1) Cluster Head: can defined as a local coordinator for its cluster. It performs inter-cluster
routing, data forwarding and many other operations.
2) Gateway: is a node that can access neighboring cluster and forward information between
clusters.
3) Cluster Member or Ordinary Node: is the one neither a Cluster Head nor Gateway.
Fig. 1 Cluster heads, Gateways and ordinary nodes in MANET
Clustering techniques is designed by defining structural partitioning of nodes inside particular
network as shown in fig.1. This mean; for particular network, the nodes will grouped to define set of
clusters based on specific techniques to specify:
1. Cluster formation phase.
2. Cluster maintenance phase.
Regarding to clustering concepts in MANET, one node must be elected as a special node or
incharge node called Cluster Head (CH) which provides virtual infrastructure for particular cluster.
Hence, remaining nodes will be referred as Ordinary Nodes (CN) except Cluster Gateways (CG)
which are the nodes that act as shared nodes between more than one cluster. All of these agreed that
the clustering formation and maintenance phases are very important concepts in power consumption
enhancement for MANETs. Some of the techniques are briefly described in the following
subsections :
4.1 LOWEST-ID CLUSTERING
The Lowest-ID as shown in fig. 2 is considered as a simplest clustering scheme algorithm [9].
In this scheme unique identifier (ID) is assigned to each node. All nodes recognize its neighbors ID
and CH is chosen according to minimum ID. Thus, the nodes IDs of the neighbors of the CH will be
higher than that CH. The main drawback with this scheme is; there is no limitation to the number of
nodes attached to the same CH. Also, CHs are prone to power drainage due to serving as cluster
heads longer period of time.

4. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-
6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
311
Fig. 2 Lowest ID Clustering Technique
4.2 HIGHEST DEGREE CLUSTERING
In comparison with Lowest-ID scheme, the degree of nodes is computed based on its distance
from each other’s [10]. All nodes flood its connectivity value within their transmission range. Thus, a
node decides to become a CH or remain as CN by comparing the connectivity value of its neighbours
with its own value. Node with highest connectivity value in its vicinity will become CH as shown in
Fig. 3. Connectivity-based clustering follows the same circumstances of ID-based regarding to
cluster size and performance degradation.
Fig. 3 Highest Degree Clustering Technique
4.3 LEAST CLUSTERING CHANGE ALGORITHM (LLC)
LLC has an important improvement over Lowest-ID and Highest-Degree Clustering
Algorithms [11]. Since most of algorithms require performing procedure of clustering periodically to
satisfy specific characteristics of CHs, the cost of cluster maintenance must be taken into account. In

5. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-
6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
312
Highest-Degree Clustering, the algorithm is performed to check the local highest node degree
periodically as it specifies the aspect of CH election. Thus, current CH will force to hand over its
roles if it finds any member node with higher degree. Frequent re-clustering involved by this
mechanism. In contrast, LLC clustering algorithm is divided into two phases:
1. Cluster formation.
2. Cluster maintenance.
The first phase simply applied as Lowest-ID algorithm by choosing mobile nodes
with Lowest-ID in their neighborhoods as CHs. But, cluster maintenance is performed as event-
Driven and called only under two circumstances; first, when a node can’t access any CH. Thus, it
call cluster formation phase to rebuilds the cluster structure according to Lowest-ID techniques.
Second, when more than one node reaches the transmission range of each other, this
requires giving up CH roles except only one which become a CH. Hence, LLC significantly
enhances clustering and increase its stability in mobile ad hoc network by releasing the
requirement that a CH should reserve some special features and characteristics within its local
area.
4.4 TRUST-BASED CLUSTERING TECHNIQUE
In [12] a trust based approach for Cluster head (TA) selection algorithm. Each cluster is
nothing but a group of nodes which is headed by one or more node(s) known as Cluster
head(s)(TAs).In this proposal Cluster head is elected by the member nodes in order to make the TA
more stable depending upon some metrics. The Cluster head(s) selection is totally distributed and
secured. The challenges can be handled by formalizing a trust relationship between the participating
nodes within 1 hop distance away. To formalize the trust of a particular node, nodes monitor the
behavior of other nodes and collect information from its neighbors and then take the decision about
the node. We have used a quantitative trust evaluation algorithm at each node to evaluate the direct
trust of its neighbor nodes.
Fig. 4 Node-based Secured Interactions
The Node-based Trust Management(NTM) (fig.4)scheme is based on a Clustered mobile
sensor network with backbone; it introduces a trust of a node within local management strategy with
help from the mobile agents running on each node. That is, a node’s trust-based information is stored
as a history on the node itself and managed by the local mobile agent of the node. However, there are

6. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-
6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
313
a couple of limitations in this approach. The way the messages passed through may overload the
Cluster head, creating a bottleneck due to additional message exchanges. Another possible limitation
is the way that the message authentication between intermediate Cluster heads are treated, where
there can be a delay in identifying a malicious neighboring node(s).
4.5 CLUSTERING BASED ON OUTLIER DETECTION MECHANISM
In this clustering technique we first determine whether all the nodes participating in the
cluster formation are trusted or not.To determine the malacious or dishonest nodes, we use the outlier
detection technique used in data mining which is based on linear method of deviation detection
[13].The objective of this indirect trust computation is to determine the trustworthiness of an
unfamiliar servic requester from the set of recommendations that narrow the gap between the derived
recommendation and the actual trustworthiness of the target service.
A dishonest recommendation is defined as an outlier that appears to be inconsistent with other
recommendations and has a low probability that it originated from the same statistical distribution as
the other recommendation in the data set. The algorithm uses a smoothing factor which detects
malicious recommendations by evaluating the impact on the dissimilarity metric by removing a
subset of recommendation classes from the set of recommendations.The node which is evaluated as
the most trusted node is selected as the cluster head (CH).
5. CONCLUSION
We have reviewed various clustering techinques,most of them provide performance
enhancement in Mobile Adhoc Network (MANET), the central theme of any algorithm is the
selection of the Cluster Head (CH),which facilitates the intra as well asinternetwork communication.
Also, the selection of the cluster head is quite critical task ,for this many CH selection algorithms
have been developed of which trust based selection scheme is an new area of research.
With this survey we can also observe that a cluster-based MANET has many important
issues to examine, such as the cluster structure stability, the control overhead of cluster
construction and maintenance, the energy consumption of mobile nodes with different cluster-
related status, the traffic load distribution in clusters, and the fairness of serving as clusterheads for a
mobile node.
6. REFERENCES
[1] J.-E. Garcia, A. Kallel, K. Kyamakya, K. Jobmann, J.-C. Cano, and P. Manzoni, A novel
DSR-based energy-efficient routing algorithm for mobile ad-hoc networks, presented at the
IEEE Vehicular Technology Conference, Florida, USA, 2003.
[2] N. Ghanem, S. Boumerdassi, and E. Renault, New energy saving mechanisms for mobile ad-
hoc networks using OLSR, in PE-WASUN '05 Proceedings of the 2nd
ACM international
workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks,
Canada, Oct. 2005, pp. 273-274.
[3] D. Johnson, D. Maltz, T. Imielinksi, and H. Korth, Dynamic source routing in ad hoc
wireless networks, in Mobile Computing, Kluwe, 1996, pp. 153-181.
[4] C. Perkins and E. Royer, Ad-Hoc on-Demand Distance Vector Routing, in Proceedings
WMCSA'99. 2nd Annual IEEE Workshop on Mobile Computing Systems and Applications,
New Orleans, 1999, pp. 90-100.
[5] I. I. Er and W. K. G. Seah, Mobility-based d-Hop Clustering Algorithm for Mobile Ad Hoc
Networks, presented at the Proceedings of IEEE Wireless Communications and Networking
Conference, Atlanta, Georgia, USA, Mar. 2004.

7. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-
6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
314
[6] S. Sarkar, T. G. Basavaraju, and C. Puttamadappa, Ad Hoc Mobile Wireless Networks:
Principles, Protocols and Applications. New York: Auerbach Publications, 2007.
[7] Dr. Mohammad U. Bokhari , Hatem S. A. Hamatta and Shams Tabrez Siddigui, A Review of
Clustering Algorithms as Applied in MANETs , International Journal of Advanced Research
in Computer Science and Software Engineering, Volume 2, Issue 11, November 2012.
[8] Dr. Mahesh Motwani and Ratish Agarwal, Survey of clustering algorithms for MANET,
International Journal on Computer Science and Engineering Vol.1(2), 2009, 98-104
[9] M. Gerla and J. Tsai, Multicluster, mobile, multimedia radio network, ACM-Baltzer Journal
of Wireless Networks, vol. 1, pp. 255-265, 1995.
[10] A. Ephremides, J. E. Wieselthier, and D. J. Baker, A design concept for reliable mobile radio
networks with frequency hopping signaling, presented at the Proceedings of the IEEE, Jan.
1987.
[11] C.-c. Chiang, H.-K. Wu, W. Liu, and M. Gerla, Routing in Clustered Multihop, Mobile
Wireless Networks with Fading Channel, presented at the Proceeding IEEE Singapore
International Conference of Networks, SICON'97, Singapore, Apr. 1997.
[12] Raihana Ferdous, Vallipuram Muthukkumarasamy, Elankayer Sithirasenan, Trust-based
Cluster head Selection Algorithm for Mobile Ad hoc Networks, TRUSTCOM '11
Proceedings of the 2011IEEE 10th International Conference on Trust, Security and Privacy in
Computing and Communications Pages 589-596.
[13] Naima Iltaf, Abdul Ghafoor and Uzman Zia, A mechanism for detecting dishonest
recommendation in indirect trust computation, EURASIP Journal on Wireless
Communications and Networking 2013.
[14] Thaker Minesh, S B Sharma and Yogesh Kosta, “A Survey: Variants of Energy Constrained
Reactive Routing Protocols of Mobile Ad Hoc Networks”, International Journal of
Electronics and Communication Engineering & Technology (IJECET), Volume 3, Issue 2,
2012, pp. 248 - 257, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472.
[15] M. Ahmed, S. Yousef and Sattar J Aboud, “Bidirectional Search Routing Protocol for Mobile
Ad Hoc Networks”, International Journal of Computer Engineering & Technology (IJCET),
Volume 4, Issue 1, 2013, pp. 229 - 243, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.
[16] Shiva Prakash, J. P. Saini, S.C. Gupta and Sandip Vijay, “Design and Implementation of
Variable Range Energy Aware Dynamic Source Routing Protocol for Mobile Ad Hoc
Networks”, International Journal of Computer Engineering & Technology (IJCET),
Volume 4, Issue 1, 2013, pp. 105 - 123, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.