Clustering based performance improvement strategies for mobile ad hoc netwo
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Clustering based performance improvement strategies for mobile ad hoc netwo Clustering based performance improvement strategies for mobile ad hoc netwo Document Transcript

  • 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: Journal Impact Factor (2013): 6.1302 (Calculated by GISI) IJCET © I A E M E
  • 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:
  • 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.
  • 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
  • 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
  • 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.
  • 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.