VORONOI LEACH FOR ENERGY EFFICIENT COMMUNICATION IN WIRELESS SENSOR NETWORKS

VORONOI LEACH FOR ENERGY EFFICIENT COMMUNICATION IN WIRELESS SENSOR NETWORKS D. Satyanarayana Department of Electrical and Computer Engineering University of Buraimi Al Buraimi, Sultanate of Oman Sathyashree. S Department of Information Technology College of Applied Sciences Sohar Sohar, Sultanate of Oman Abdullah Said Al Kalbani Department of Electrical and Computer Engineering University of Buraimi Al Buraimi, Sultanate of Oman Abstract Energy efficient communication is significantly important for Wireless Sensor Networks as the energy is a scarce and constrained resource. In this paper, we have proposed a different version of LEACH (Low Energy Adaptive Clustering Hierarchy) protocol called Voronoi LEACH, where the clusters in LEACH are replaced with Voronoi regions. The proposed protocol has better properties for energy efficient communication than LEACH protocol. The simulation results show that the Voronoi LEACH consumes less energy compared to the LEACH protocol. Keywords Wireless sensor networks, energy efficiency, clusters, Voronoi diagrams. Introduction Wireless Sensor Networks have gained its popularity day by day because of its wide range of applications. In wireless sensor networks, the energy is one of the important component as the sensor node will be considered dead when the energy in the node is depleted. Hence, there is significant importance in designing the energy efficient communication methodologies for wireless sensor networks. The protocol LEACH proposed by Heinzelman et al. [4] was one of the popular energy efficient communication protocol used in wireless sensor networks. The LEACH protocol has two phases. In the phase I the protocol forms the clusters and in phase II, the sensor nodes send the information to their cluster heads which inturn send the aggregated information to the basestation. In phase I, it is very important to consider the formation of clusters in which a huge number of communication actions are taken place between the sensor nodes and the cluster heads. In the literature, many variations of the LEACH protocol were proposed. However, most of the algorithms focused on the criteria for selecting cluster heads based on many factors, such as energy levels in the node, to increase the network lifetime and the stability. In wireless communication systems, the energy consumption is directly proportional to the distance travelled by the frames [8][9]. In otherwords, the energy consumption, where d is the distance between the transmitter and receiver and is the path loss component [8][9]. If the distance between the transmitter and receiver is less, the energy consumption becomes low. In this paper, we have focused on designing a new type of clusters for the LEACH protocol such that the distance between a sensor node and the cluster head is minimum. However, due to the random distribution of sensor nodes, in the traditional approach, the cluster formations may have overlapping areas and this distribution of sensor nodes can be look alike as shown in Figure 1. In this figure, we can observe there are some sensor nodes in the overlapping cluster areas. These nodes sometimes have more distance to its cluster head than the other cluster heads. For example, consider the Figure 2, where two clusters have cluster heads H 1 and H 2 respectively. The sensor node a belongs to the cluster C1 always needs to transfer its data to the H 1 only. Similarly, in cluster C2, the sensor node b needs to transfer the data the cluster head H 2 only. The distances and are higher compared to the distances and, respectively. Please note that the notation indicates the Euclidean distance between the two nodes x and y. Hence there is higher energy consumption in the system. We consider this as a problem in the paper and we design a solution for this problem using Voronoi diagrams [7]. In this paper, we use the Voronoi diagrams for forming clusters. With this kind of clusters, the protocol 216

provides optimum energy consumption between sensor nodes and the cluster heads. The paper has been organized with the following sections. The next section provides the related work and the Section III describes the proposed protocol. The Section IV gives the simulation work whereas the Section V concludes the paper. Related Work In this section, we give the information related to the paper. The paper mainly focuses on saving the energy in communication system. There were many protocols proposed for energy efficient communication [10][11][12][13]. During this period, the protocol LEACH has been proposed for energy efficient communication for wireless sensor networks [4]. A wireless sensor network is a wireless network which collects the environment information through sensors and transmits to a destined place through the communication system [14]. In general, the sensor nodes contain energy constrained resources [15]. Hence, there is a need for the study of energy efficient communication systems for wireless sensor networks. The complete process of LEACH protocol is broadly divided into two phases [4]. The phase 1 is responsible for forming the clusters. The formula for making the sensor node as the cluster head is based on the threshold formula given below. (1) ( ) { ( ) P=probability of becoming the cluster head r= the current node G= the set of nodes that have not been cluster-heads } The node n selects a random number between 0 and 1 and having the value less than the threshold T(n) then the node becomes the cluster head for the current round. In the phase 2 of the LEACH protocol the sensor node transmits its data to the cluster head which intern aggregates and transmits the data to the basestation. There are few improvements done on LEACH to increase the life time of the network and providing reliable communication. The author Takkar et al. [1] proposed a sequential LEACH(S-LEACH) protocol, which makes sure that the required number of cluster heads is maintained in each round until the first node consumes the entire energy. The E-LEACH protocol [16] selects the cluster heads as a function of the remaining energy levels in the sensor nodes. The node having highest energy will be selected as cluster head, hence the network lifetime increased in the network. The K-LEACH [15] protocol uses K-medoids algorithm in selecting the cluster heads. This algorithm increases the network lifetime and balancing the load of the network. The author Hou et al. [2] proposed a protocol called D-LEACH where each cluster head observes the data coming from the sensor nodes and it assigns the probability components to each data frame to be transmitted. The Hierarchical LEACH protocol [17] has defined three levels of nodes, where the level 1 nodes gather the information from the environment, the level 2 nodes exist outside the radius of the basestation where as the level 3 nodes exists inside a predefined radius to the basestation. The author Hady et al. [3] proposed CS-LEACH which uses an approach called Intelligent sleeping mechanism(ism) to make a certain percentage of nodes to go to the sleep mode in order to save the energy. In this paper, the proposed protocol uses Voronoi diagrams [7] in the cluster formation. A Voronoi diagram is a computational geometry structure which provides distance relation among the points. The formal algorithm for constructing Voronoi diagram is given in [7]. However, this algorithm is very expensive to use in wireless networks as it needs global information. The 217

localized algorithm for constructing Voronoi diagram, especially used for wireless networks is given in [7]. In the next section, the use of Voronoi diagrams in wireless sensor network to save energy consumption of sensor nodes has been described. The Proposed Protocol The energy efficient methodologies in wireless sensor networks have got significant importance as the sensor nodes die as and when the battery energy is depleted. In the literature several methods have been proposed for WSN to consume less energy and increase the network lifetime. Among them, one of the best approaches to save the energy consumption is LEACH by Heinzelman et al. [4]. This proposal has three categories of nodes in the network: sensor nodes, cluster heads, and the basestations. The sensor node collects the information from the environment, where as the cluster heads and the basestations are responsible to transfer the information to the desired location. The actions in the LEACH protocol works in two phases. The phase I choose a cluster head from the specific set of sensor nodes and create the cluster. In phase II, the data from the sensor node will be transmitted to cluster head in TDMA fashion and the cluster head inturn aggregates the data and retransmits to the basestation. In this algorithm, there are two levels of energy savings due to the communication. In level 1, the sensor nodes switch off their communication device, where the receiver power consumption can be saved even though the transmitter is not used. In the level 2, the data to be transmitted from cluster head to the basestation will be huge. As the data is collected from different nodes within the same cluster, there is more possibility of data aggregation. Hence, there is a reduction in the data size to be transmitted which leads to the energy saving. However, the LEACH has some drawbacks in forming the clusters due to the random distribution of sensor nodes. For example, when the clusters are formed, there could be some sensor nodes in the overlapping area of the clusters, see the Figure 1. In some scenarios, the sensor nodes in the overlapped area will transfer the data to its cluster head which is far away than the other cluster head. For example, in Figure 2, the sensor node a belongs to the cluster C1, whereas the sensor node b belongs to the cluster C2. The information from sensor node a has to be transferred to the cluster head H 1 and similarly from the sensor node b to the cluster head H 2. From the figure, we can clearly observe that the Euclidean distance between a and H 1 is more than the distance between a and H 2. In otherwords, it is energy efficient if the sensor node a transfers the data to cluster H 2 rather than H 1 as the energy consumption is directly proportional to the distance travelled by the frame [8][9]. The possibility of occurring such cases is more in WSN due to the random distribution of nodes. Hence considering these types of cases saves significant energy in the communication system. To solve this problem, we have used Voronoi diagrams to create the clusters and we named it as Voronoi LEACH. The Voronoi diagrams are computational geometry structures which provide distance relationship among the given nodes [7]. The construction of Voronoi diagram with the given set of nodes using the local information is given in [5][6]. C3 C1 C10 C7 Fig. 1. Sensor nodes, Cluster heads and Clusters. C4 C9 C6 C2 C5 C8 218

C1 a C2 H1 b H2 Fig. 2. Overlapping area of clusters. In this paper, we have considered a dynamic approach for constructing the Voronoi clusters, as the cluster heads need to be changed at every certain period to avoid depleting the energy, which causes the node dead. The following algorithm creates the Voronoi LEACH architecture. Algorithm 1 1. Choose the cluster heads based on the equation 1. 2. Broadcast cluster head ID and position information in two hops. 3. With only cluster heads, create Voronoi clusters using the algorithm given in [5][6]. 4. At every time period, each sensor node transmits the environmental information to its cluster head. 5. At every time period, the cluster head aggregates the data and retransmits to the basestation. 6. At every time period, goto step 1. Fig. 3. The Voronoi clusters. The proposed approach consumes less energy than the LEACH. In the algorithm, first all the sensor nodes select the cluster head using the threshold equation 1. These cluster heads form the Voronoi clusters, using a localized algorithm for constructing the Voronoi regions [5][6]. These Voronoi clusters are dynamic as they change at every time period. When the Voronoi clusters are formed, all the sensor nodes within the Voronoi cluster will communicate to only the Voronoi cluster head. In general, all the points within the Voronoi region are closure to the Voronoi vertex than any other Voronoi vertex in the Voronio diagram [7]. After constructing the Voronoi clusters, all the sensor nodes within the Voronoi cluster are closure to the Voronoi cluster head of the same cluster, see the Figure 3. In otherwords, all the sensor nodes within the overlapped area in LEACH will communicate to only the less distanced cluster heads in Voronoi LEACH. This assures the communication between sensor node and cluster head will further reduce the energy consumption. The Voronoi cluster heads need to be changed as the battery life of the sensor node will be exhausted soon if it is continuously or heavily used. To avoid this kind of problem, the cluster node needs to be changed for every time interval. In otherwords, the Voronoi clusters needed be constructed for every time interval. This process is taken care in the step 6 of the Algorithm. The proposed approach has the major advantage of saving communication energy of sensor nodes, precisely, the sensor nodes in the overlapped area of the 219

Total Energy consumption (kilo joules) Distance (meters) clusters in LEACH. The energy saving is significant. In the next section we describe the simulation work of the proposed approach. 9000 8000 LEACH VLEACH Simulation ` In this paper, we have performed simulation work using ns2. We have compared our proposal Voronoi LEACH (V-LEACH) with the LEACH given in [4]. In the simulation, we have taken sensor nodes in different sets in the grid size of 1000 x 1000 m 2. We consider that each node has the capability to adjust its transmitter radio range with the maximum transmission range of 200m. The sensor nodes transmit the data to the cluster head with the defined distance. We have carried out the experiments to calculate the number of sensor nodes in the overlapped area of the clusters by taking the different of node sets of 50, 100, 150, 200, 250, 300. We have calculated the total distance between overlapped sensor nodes and the cluster heads. From the Figure 4, we can observe that the distance used for communication between sensor node and the cluster heads is high in the case of LEACH protocol, whereas the proposed Voronoi LEACH has less distance between the sensor node and cluster head. This could happen because the Voronoi clusters in V-LEACH protocol optimize the distance between sensor nodes and the cluster heads. The other experiment that we have done is to calculate the energy consumed during the entire simulation time. The following graph shows the energy consumption for the two protocols LEACH and V- LEACH. The energy consumption in V-LEACH is less compared to the energy consumption in LAECH, see the Figure 5. This could happen because the V-LEACH uses Voronoi clusters which optimize the distance between sensor nodes and cluster heads. In otherwords, the distance between sensor nodes and cluster heads in V-LEACH is less than or equal to the distance between the sensor nodes and the cluster heads in LEACH. This leads to the less energy consumption as the energy consumption is directly proportional to the distance. 7000 6000 5000 4000 3000 2000 1000 0 50 100 150 200 250 300 Number of sensor nodes Fig. 4. The overlapped sensor nodes 40 LEACH VLEACH 35 30 25 20 15 10 5 0 50 100 150 200 250 300 Number of sensor nodes Fig. 5. Energy consumption 220

Conclusion The LEACH protocol is used for saving the energy consumption and increase the network lifetime for wireless sensor networks. However, the protocol has some drawbacks on the energy consumption of sensor nodes in the overlapped area of the clusters. The proposed protocol Voronoi LEACH solves this problem and saves the energy consumption better than the LEACH protocol. To consider our claim, we have done the simulation work and it has shown that the energy saving in V-LEACH is better than LEACH. References [1] A. Thakkar and K. Kotecha, S-leach: A sequential selection approach to elect cluster heads for leach protocol, International journal of Electronics and Communication Engineering and Technology (IJECET), 5(1), pp. 148 157, 2014. [2] G. Hou, K. W. Tang, and E. M. Noel, Implementation and improvement of leach protocol for wireless sensor networks, International Journal of Research in Wireless Systems (IJRWS), pp.94-106, October 2013. [3] A. A. Hady, S. A. El-kader, and H. S. Eissa, Intelligent sleeping mechanism for wireless sensor networks, Egyptian Informatics Journal, pp. 109-115, July 2013. [4] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, Energy efficient communication protocol for wireless microsensor networks, Proceedings of 33 rd annual Hawaii International Conference on System Sciences, Maui, Hawaii, USA, Pp. 3005-3014, 2000. [5] D. Satyanarayana and J. M. Elmirghani, A voronoi based energy efficient architecture for wireless networks., NGMAST 09 Proceedings of the 2009 Third International Conference on Next Generation Mobile Applications, Services and Technologies., pp. 377 382, Cardiff, UK. 2009. [6] D. Satyanarayana and J. M. Elmirghani, An energy efficient network architecture for infrastructured wireless networks., Global Communication, GLOBECOM 10, pp. 1 6, Miami, USA, 2010. [7] F. P. Preparata and M. I. Shamos, Computational geometry: An Introduction. New York, USA: Springer-Verlag, 1985. [8] T. S. Rappaport, Wireless Communications: Priciples and Practices. Prentice Hall PTR, 2001. [9] P. M. Shankar, Introduction to Wireless Systems. JOHN WILLEY and SONS, INC. 2002. [10] J. Kuruvila, A. Nayak, and I. Stojmenovic, Progress and Location based localized power aware routing for ad hoc and sensor wireless networks., IJDSN, vol. 2, no. 2, pp. 147 159, 2006. [11] I. Stojmenovic and S. Datta, Power and cost aware localized routing with guaranteed delivery in wireless networks, Computers and Communications, IEEE Symposium on, vol. 0, p. 31, 2002. [12] I. Stojmenovic and X. Lin, Power-aware localized routing in wireless networks, IEEE Trans Parallel Distrib. Syst., vol. 12, no. 11, pp. 1122 1133, 2001. [13] S. Singh, M. Woo, and C. S. Raghavendra, Power-aware routing in mobile ad hoc networks, in MobiCom 98: Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking, (New York, NY,USA), pp. 181 190, ACM, 1998. [14] G. Hou, W. Tang, and E. Noel., Implementation and improvement of leach protocol for wireless sensor networks,. International Journal of Reaearch in Wirless Systems (IJRWS), Vol. 2, No. 3, pp. 94-106, October 2013. [15] P. Bakaraniya and S. Mehta, K-leach: An improved leach protocol for lifetime improvement in WSN, International Journal of Engineering Treands and Technology (IJETT), May 2013. [16] F. Xiangning and S. Yulin, Improvement on leach protocol of wireless sensor network, In proceeding of : Sensor Technologies and Applications, SensorComm, International Conference on, pp.260-264, October 2007. [17] H. Taneja and P. Bhalla, An improved version of leach: Three levels hierarchical clustering leach protocol (tlhclp) for homogeneous WSN. International Journal of Advanced Research in Computer and Communication Engineering Vol 2, Issue 9, September 2013. [18] D. Dembla and S. H. Mehta, Energy efficient leach protocol for wireless sensor network (ee-leach), IJSRDV119073, p. 165169, July- December 2013. 221