TOPOLOGY CONTROL IN WIRELESS NETWORKS BASED ON CLUSTERING SCHEME

Similar documents
Figure 1. Clustering in MANET.

An Adaptive and Optimal Distributed Clustering for Wireless Sensor

IMPROVING WIRELESS SENSOR NETWORK LIFESPAN THROUGH ENERGY EFFICIENT ALGORITHMS

6367(Print), ISSN (Online) Volume 4, Issue 2, March April (2013), IAEME & TECHNOLOGY (IJCET)

PERFORMANCE EVALUATION OF TOPOLOGY CONTROL ALGORITHMS FOR WIRELESS SENSOR NETWORKS

Performance Evaluation of Various Routing Protocols in MANET

Performance Evaluation of Mesh - Based Multicast Routing Protocols in MANET s

Novel Cluster Based Routing Protocol in Wireless Sensor Networks

Proclivity of Mobility and Energy based Clustering schemes towards Load-balancing schemes in Wireless Ad-hoc Networks

The Impact of Clustering on the Average Path Length in Wireless Sensor Networks

An Efficient Data-Centric Routing Approach for Wireless Sensor Networks using Edrina

Journal of Wireless Sensor Networks. Topology control in Heterogeneous Wireless Sensor Network

Analysis of Cluster based Routing Algorithms in Wireless Sensor Networks using NS2 simulator

CROSS LAYER PROTOCOL (APTEEN) USING WSN FOR REAL TIME APPLICATION

A Study on Issues Associated with Mobile Network

AN ENERGY EFFICIENT AND RELIABLE TWO TIER ROUTING PROTOCOL FOR TOPOLOGY CONTROL IN WIRELESS SENSOR NETWORKS

Using Hybrid Algorithm in Wireless Ad-Hoc Networks: Reducing the Number of Transmissions

Survey on Secure & Efficient Data Transmission in Cluster Based Wireless Sensor Network

Ad hoc and Sensor Networks Topology control

EEEM: An Energy-Efficient Emulsion Mechanism for Wireless Sensor Networks

MPBCA: Mobility Prediction Based Clustering Algorithm for MANET

International Journal of Scientific & Engineering Research, Volume 6, Issue 3, March ISSN

GSM Based Comparative Investigation of Hybrid Routing Protocols in MANETS

IJREAT International Journal of Research in Engineering & Advanced Technology, Volume 1, Issue 2, April-May, 2013 ISSN:

SECURE AND ROBUST ENERGY-EFFICIENT AND RELIABLE ROUTING FOR MULTI HOP NETWORKS USING WIRELESS SENSOR NETWORKS

A Literature survey on Improving AODV protocol through cross layer design in MANET

CLUSTER BASED ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORKS

Reliable Routing In VANET Using Cross Layer Approach

A Comparative Analysis of Energy Preservation Performance Metric for ERAODV, RAODV, AODV and DSDV Routing Protocols in MANET

PRIVACY AND TRUST-AWARE FRAMEWORK FOR SECURE ROUTING IN WIRELESS MESH NETWORKS

(INTERFERENCE AND CONGESTION AWARE ROUTING PROTOCOL)

Energy Consumption for Cluster Based Wireless Routing Protocols in Sensor Networks

COMPARATIVE PERFORMANCE ANALYSIS OF TEEN SEP LEACH ERP EAMMH AND PEGASIS ROUTING PROTOCOLS

Mitigating Hot Spot Problems in Wireless Sensor Networks Using Tier-Based Quantification Algorithm

Mitigating Superfluous Flooding of Control Packets MANET

Clustering Based Topology Control Protocol for Data Delivery in Wireless Sensor Networks

A Survey On: Cluster Based Routing Protocols in Wireless Sensor Network

Time Synchronization in Wireless Sensor Networks: CCTS

A3: A Topology Construction Algorithm for Wireless Sensor Networks

Anil Saini Ph.D. Research Scholar Department of Comp. Sci. & Applns, India. Keywords AODV, CBR, DSDV, DSR, MANETs, PDF, Pause Time, Speed, Throughput.

International Journal of Research in Advent Technology Available Online at:

Performance Analysis and Enhancement of Routing Protocol in Manet

DISTANCE BASED CLUSTER FORMATION FOR ENHANCING THE NETWORK LIFE TIME IN MANETS

Improving Performance in Ad hoc Networks through Location based Multi Hop Forwarding

A Survey - Energy Efficient Routing Protocols in MANET

WSN Routing Protocols

Accepted 10 May 2014, Available online 01 June 2014, Vol.4, No.3 (June 2014)

Simulation and Performance Analysis of Throughput and Delay on Varying Time and Number of Nodes in MANET

Integrated Routing and Query Processing in Wireless Sensor Networks

NEW! Updates from previous draft Based on group mailing list discussions Added definition of optimal scalability with examples (captures idea of suffi

Simulation and Analysis of AODV and DSDV Routing Protocols in Vehicular Adhoc Networks using Random Waypoint Mobility Model

Battery Power Management Routing Considering Participation Duration for Mobile Ad Hoc Networks

Enhancement of Routing in Urban Scenario using Link State Routing Protocol and Firefly Optimization

Fig. 2: Architecture of sensor node

Efficient Broadcast Algorithms To Reduce number of transmission Based on Probability Scheme

Keywords Mobile Ad hoc Networks, Multi-hop Routing, Infrastructure less, Multicast Routing, Routing.

Subject: Adhoc Networks

Efficient Cluster Based Data Collection Using Mobile Data Collector for Wireless Sensor Network

A Survey on Path Weight Based routing Over Wireless Mesh Networks

End-To-End Delay Optimization in Wireless Sensor Network (WSN)

DYNAMIC SEARCH TECHNIQUE USED FOR IMPROVING PASSIVE SOURCE ROUTING PROTOCOL IN MANET

Study on Techniques for Cluster Head Formation over Mobile Ad Hoc Networks

Mobile Ad Hoc Backbones for Multi-Radio Networks

Performance Analysis of MANET Using Efficient Power Aware Routing Protocol (EPAR)

Vaibhav Jain 2, Pawan kumar 3 2,3 Assistant Professor, ECE Deptt. Vaish College of Engineering, Rohtak, India. Rohtak, India

Analysis of Cluster-Based Energy-Dynamic Routing Protocols in WSN

A Protocol for Reducing Routing Overhead in Mobile Ad Hoc Networks

Efficient Hybrid Multicast Routing Protocol for Ad-Hoc Wireless Networks

Proficient ID Allocation for MANETs

Analysis of GPS and Zone Based Vehicular Routing on Urban City Roads

A Topology Based Routing Protocols Comparative Analysis for MANETs Girish Paliwal, Swapnesh Taterh

CONCLUSIONS AND SCOPE FOR FUTURE WORK

Intra and Inter Cluster Synchronization Scheme for Cluster Based Sensor Network

AN OPTIMIZED CLUSTER BASED APPROACH FOR MULTI- SOURCE MULTICAST ROUTING PROTOCOL IN MOBILE AD HOC NETWORKS USING OWCA

CLUSTER HEAD SELECTION USING QOS STRATEGY IN WSN

Computation of Multiple Node Disjoint Paths

STUDY AND COMPARISION OF PROACTIVE AND REACTIVE ROUTING PROTOCOL FOR MULTICHANNEL WIRELESS AD-HOC NETWORK

Maximum Coverage Range based Sensor Node Selection Approach to Optimize in WSN

Regression Based Cluster Formation for Enhancement of Lifetime of WSN

An Energy-efficient Distributed Self-organized Clustering Based Splitting and Merging in Wireless Sensor Networks

Connected Point Coverage in Wireless Sensor Networks using Robust Spanning Trees

Mobile Agent Driven Time Synchronized Energy Efficient WSN

International Journal of Advance Engineering and Research Development. Improved OLSR Protocol for VANET

AN ANTENNA SELECTION FOR MANET NODES AND CLUSTER HEAD GATEWAY IN INTEGRATED MOBILE ADHOC NETWORK

Efficient Routing Algorithm for MANET using Grid FSR

E-MEECP- DEVELOPING A DEPENDABLE ROUTING PROTOCOLS FOR HETEROGENEOUS WIRELESS NETWORKS

An Energy Efficiency Routing Algorithm of Wireless Sensor Network Based on Round Model. Zhang Ying-Hui

AN EFFICIENT MAC PROTOCOL FOR SUPPORTING QOS IN WIRELESS SENSOR NETWORKS

GROUP MANAGEMENT IN MOBILE ADHOC NETWORKS

Energy Conservation through Sleep Scheduling in Wireless Sensor Network 1. Sneha M. Patil, Archana B. Kanwade 2

Dynamic Deferred Acknowledgment Mechanism for Improving the Performance of TCP in Multi-Hop Wireless Networks

Nearest Neighbor Query in Location- Aware Mobile Ad-Hoc Network

Chapter 5 To T pology C o C ntrol

Hierarchical Low Power Consumption Technique with Location Information for Sensor Networks

Geographical Grid Based Clustering for WSN

Ad hoc and Sensor Networks Chapter 10: Topology control

Performance Analysis of Power -aware Node-disjoint Multipath Source Routing in Mobile Ad Hoc Networks

Behaviour of Routing Protocols of Mobile Adhoc Netwok with Increasing Number of Groups using Group Mobility Model

On the Scalability of Hierarchical Ad Hoc Wireless Networks

Estimation of Network Partition Problem in Mobile Ad hoc Network

Transcription:

International Journal of Wireless Communications and Networking 3(1), 2011, pp. 89-93 TOPOLOGY CONTROL IN WIRELESS NETWORKS BASED ON CLUSTERING SCHEME A. Wims Magdalene Mary 1 and S. Smys 2 1 PG Scholar, ECE Dept, Karunya University, Coimbatore, India, E-mail: vimsy.87@gmail.com 2 Assistant Professor, ECE Dept, Karunya University, Coimbatore, India, E-mail: smys@karunya.edu Abstract: The objective of the paper is to implement topology control using cluster based approach. Topology control is a well known technique in wireless networks to improve the life time of the network. In the proposed work topology control is achieved in two phases. In the first phase the initial topology is reduced where each nodes are sub grouped to form clusters and cluster head is elected for each cluster. Both intra cluster as well as inter cluster Topology control mechanisms are analyzed by increasing the number of nodes in the network is reduced and network life time is improved. In the second phase the reduced topology is maintained by introducing backbone between the clusters. The results are witnessed by simulation. Keywords: topology control, topology maintenance, clustering. I. INTRODUCTION Topology control is a technique used in wireless ad hoc and sensor networks in order to reduce the initial topology of the network to save energy and extend the lifetime of the network. It is the art of coordinating nodes decisions regarding their transmitting ranges, in order to generate a network with the desired properties while reducing node energy consumption and/or increasing network capacity is defined in [1]. Topology control is divided into two phases. First phase is topology construction, which includes the process of reducing the initial topology The second phase is topology maintenance which is in charge of maintaining the reduced topology while preserving important network properties such as connectivity and coverage. The major goals of topology are connectivity with energy efficiency, high throughput and robustness to mobility etc. There are various existing methods available for topology construction and maintenance such as changing the transmission range of the nodes, turning the unnecessary nodes to off, partitioning the nodes to clusters. Our method is based on connected dominated sets (CDS) and clustering approach with backbone in between the clusters. CDS based approach is used in many papers Most CDS-based mechanisms work in two phases: In phase one they create a preliminary version of the CDS, and in phase two they add or remove nodes from it to obtain a better approximation to the optimal CDS. Clustering algorithms, organize the network into a set of clusters, which are used to ease the task of routing messages between nodes and/or to better balance the energy consumption in the network. Clustering techniques are more often used in the context of wireless networks since these networks are composed of a very large number of nodes and a hierarchical organization of the network units might prove extremely useful. A backbone node consists of high capacity nodes and remains connected even when the nodes are mobile and when nodes are failed is analyzed in [2]. Routing messages are exchanged between the backbone nodes instead of being broadcasted to all the nodes therefore it can adapt quickly when the network topology changes. In our method VB are used to maintain the reduced topology when it changes. The rest of the paper is organised as follows section 2 about the related works, section 3 analyzes the network model, section 4 consists of proposed Topology control algorithms, section 5 analyzes the inter cluster topology control and maintenance, section 6 shows results and simulation. Finally section 7 ends this paper with conclusion and future work.

90 International Journal of Wireless Communications and Networking II. RELATED WORKS In [3] topology control is achieved using A3 a topology construction protocol that addresses the problem of finding a reduced topology. A3 finds a sub-optimal Connected Dominating Set (CDS) to turn unnecessary nodes off while keeping the network connected and covered. The algorithm is based on a growing-tree technique and uses a selection metric based on the remaining energy on the nodes and distance among them. This paper [4] analyzes various topology maintenance techniques and present different strategies that can be used to switch the network topologies. Static and dynamic global topology maintenance techniques using topology construction algorithms and energy based triggering criteria are implemented and their performances are compared in dense and sparse networks. In [5] analyzes topology control based on power control technology where transmission range of each node is reduced and it also analyzes how the power affects the MAC layer, network topology, routing and energy efficiency with energy aware mechanisms in order to increase the energy efficiency and improve the life time of the network. In [6] presents three congestion aware topology control (CATC) algorithms. CATC-CP(CATC- Common power), CATC-IP (CATC- Independent power) and CATC-MS (CATC- master/slave). The proposed schemes use purely local state to make topology control decisions, but vary in degree of coordination between nodes once the decision are taken. In this paper the proposed CATC schemes shows better performance than that of static topology control schemes using constant transmission power. In [8] cluster based topology control is proposed for a hybrid approach to control topology using transmission power adjustments and it is done in three phases. It provides scalability, less interference and energy consumption. This paper [9] addresses the issue of energy conservation and interference reduction in wireless multi hop networks. In any topology the node affected by the communication between any other node should be few. Here two algorithms are proposed the interference-aware local minimum spanning tree (MST) based algorithm (IALMST) and the interference-bounded energy-conserving algorithm (IBEC) to reduce the interference and efficiently conserve energy to improve the network life time in wireless multi hop networks. In this paper we propose to control the wireless network topology using clustering backbone approach, where the initially reduced topology is partitioned into cluster. Cluster head is elected for each cluster based on node energy.. The existing methods on topology control stops with topology construction itself but in the proposed work the reduced topology is maintained by introducing backbone between the clusters. III. NETWORK MODEL A wireless networks consists of set of nodes distributed in a random fashion. A graph G = (V, E) where V is the set of vertices and E represents set of links. N is the nodes of nodes in the networks. All the nodes are partitioned to form clusters and cluster head is elected based on the node energy. The node with the highest energy is chosen as the cluster head and the other nodes are cluster members. IV. PROPOSED TOPOLOGY CONTROL Topology control is done in two phase. The first phase is intra cluster topology control. Intra cluster is done under static condition. It consists of two steps Step 1: Cluster heads and cluster members are connected via one hop distance. Step 2: A set of active nodes are selected in the cluster, the remaining nodes are in power saving process. Active nodes involves in the process of data transmission from the source to destination. Figure 1: Intra Cluster Topology

Topology Control in Wireless Networks based on Clustering Scheme 91 By selecting the nodes in the cluster to be in active and inactive states, the energy is saved and the transmitted power is reduced which in turn increases the life time of the network. The throughput, delay and packet delivery ratio is analyzed by increasing the number of clusters. Algorithm 1: Intra cluster topology control Step 1: Initialization. For i ---- 1,n in clusters Say u be the node with maximum energy If energy = max, then elect node as cluster head else normal node Step 2: Intra Cluster topology control Define a topology control set with clusters S(u) (u), Normal node set N(V) (v). S(u), N(v) is a subset of clusters, where u, v are one hop neighbors. //u 1, u 2 u n are clusters, v 1,v 2. v n are cluster members connected to the cluster head //. Step 3: Topology control-phase reduced topology Initially when power is max Set a threshold time Each node calculate individual energy If energy > threshold value Nodes set to ctive state. Else Nodes set to sleep state. S (u, v) update a,a,..a.// active nodes n1 n2 nn S(v) update s n1,s,..s.// sleeping nodes n2 nn V. INTER CLUSTER TOPOLOGY CONTROL AND MAINTENANCE The mobility feature of mobile ad hoc networks causes frequent and unpredictable changes of the network topology. These changes require the maintenance of the backbone. To ensure fast update, and efficient use of resources, the maintenance should be localized to adapt quickly to a node movement, and to minimize the communication overhead[2]. Topology maintenance is the process that restores, rotates, or recreates the network topology when the current reduced one is no longer optimal. Topology maintenance can be exercised in different ways depending on when the topologies are built, their scope, and the type of triggering event or metric [2].The triggering criteria, which may have important implications in terms of energy savings as well as coverage, reliability, and other important metrics, may be based on one of the following choices such as time based, Failure based and Density based. The second phase in cluster based topology control is inter cluster topology control. This is analyzed under dynamic conditions. Wireless networks are collection of mobile nodes. The topology of the network changes with time due to the mobility of nodes. Nodes may enter or leave the network In the proposed work topology maintenance can be done by using inter cluster conditions under different criteria s. When a single node moves out of cluster. When two or three nodes moves out of cluster. When the cluster head moves. When a node from a cluster moves out, the nodes which come first from any cluster will be considered as backbone nodes. Backbone nodes will maintain edge connectivity and extend the lifetime of the network. VI. SIMULATION RESULTS For our simulation, we use the network simulator NS 2.30 with fifty nodes. Nine nodes per cluster, in each cluster topology control is achieved by setting the nodes to active and sleep states and Packet delivery ratio, throughput and delay are calculated and the performance evaluation is done by comparing with the existing method DEMAC- Figure 2: Cluster based TC Scenario

92 International Journal of Wireless Communications and Networking Degree Energy mobility aware clustering scheme to reduce the topology[10]. A. Throughput Throughput is defined as the average number of data packets received at destinations during simulation time. Fig 4 shows the results of measured throughput for DEMAC and the proposed work. It can be seen that the proposed algorithm outperforms the existing DEMAC cluster based topology control mechanism. B. End to End Delay End-to-End delay is the average time required for a packet to reach the destination from source. Fig 3 shows the results of measured end to end delay for existing DEMAC and the proposed intra cluster topology control. C. Normalized Routing Overhead Normalized routing overhead is the number of routing packets transmitted per data packet sent to the destination. Fig. 5 shows that the proposed work outperforms the existing DEMAC scheme. Figure 5: Packets Arrived/S Vs Normalized Routing Overhead VII. CONCLUSION AND FUTURE WORK In this paper topology control problem is addressed thro intra cluster conditions and topology maintenance is carried out using backbones. Topology control is a very changeling issue in dynamic networks where the mobility of the nodes are unpredictable. Various topology control algorithms have been proposed are analyzed in the literature. Existing works on cluster based topology control are based on protocols such as LEACH, PEGASIS and DEMAC. In the proposed work both the cluster and backbone approach are used to reduce the topology and increase the life time of the network. In this paper intra cluster topology control is analyzed and the performance is evaluated in terms of throughput, packet delivery ratio delay and normalized routing overhead. These parameters are compared with the existing cluster based topology control DEMAC. The future work is to analyze the topology control under dynamic inter cluster conditions and topology maintenance. Figure 3: Figure 4: Packets Arrived/S Vs Delay Packets Arrived/S Vs Throughput REFERENCES [1] P. Santi. Topology Control in Wireless Ad Hoc and Sensor Networks. John Wiley & Sons, September 2005. [2] Efficient and Resilient Backbones for Multihop Wireless Networks Seungjoon Lee, Bobby Bhattacharjee, Aravind Srinivasan, Senior Member, IEEE, and Samir Khuller. IEEE Transactions on Mobile Computing, Vol. 7, No. 11, 2008. [3] P. M. Wightman and M. A. Labrador. A3: a topology construction algorithm for wireless sensor networks. Proc. of IEEE Globecom 2008. [4] P. M. Wightman and M. A. Labrador. Topology maintenance: Extending the lifetime of wireless sensor networks. Proc. of WWASN 2009 (submitted), 2009.

Topology Control in Wireless Networks based on Clustering Scheme 93 [5] R. Ramanathan, R. R. Hain, Topology control of multihop wireless networks using transmit power adjustment, in: Pt: Proceedings of IEEE INFOCOM, March 2000, pp. 404 413. [6] Congestion aware topology controls for wireless multi-hop networks.elsevier seung-jong park, Raghupathy sivakumar May 2009. [7] Simple and Efficient Backbone Algorithm for Calculating Connected Dominating Set in Wireless Adhoc Networks, World Academy of Science, Engineering and Technology 33 2007. [8] CLTC: A Cluster-Based Topology Control Framework for Ad Hoc Networks. IEEE Transactions on Mobile Computing, Vol. 3, No. 1, 2004. [9] Localized Interference-aware and Energyconserving Topology Control Algorithms Yao Shen Yunze Cai Xiaoming Xu, Wireless Pers Commun (2008), 45: 103 120. [10] DEMAC: A Cluster-Based Topology Control for Ad Hoc Networks Abhishek Majumder, Nityananda Sarma IJCSI International Journal of Computer Science Issues, Vol. 7, Issue 5, 2010. [11] Energy efficient clustering algorithm for maximizing life time of wireless sensor networks Xiang Mina,b,, ShiWei- rena, JiangChang-jianga, ZhangYinga, Int. J. Electron. Commun. (AEÜ) 64 (2010), 289 298. [12] EEHC: Energy efficient heterogeneous clustered scheme wireless sensor networks Dilip Kumar a,*, Trilok C. Aseri b, R. B. Patel c,computer Communications 32, (2009), 662 667. [13] Energy-efficient distributed clustering in wireless sensor networks, N. Dimokasa, D. Katsaros b,_, Y. Manolopoulosa, Parallel Distrib. Comput. 70 (2010) 371_383. [14] Power Control and Clustering in Ad Hoc Networks Vikas Kawadia and P. R. Kumar, IEEE INFOCOM 2003.