International Journal of Computer Engineering and Applications, Volume XII, Issue III, March 18, ISSN

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1 IMPROVED ENERGY CONSUMPTION FOR HYBRID (PSO/GADA-LEACH) APPROACH IN WIRELESS SENSOR NETWORKS Bandani Kumari 1, Shaveta Kalsi 2 1 Research Scholar, Department of Computer Engineering 2 Assistant Professor, Department of Computer Engineering, DAV Institute of Engineering & Technology Punjab, India ABSTRACT: A wireless Sensor Networks is a combination of sensor nodes which are set up in large network and able to operate in an unattended environment. Wireless Sensor Networks is one of the emerging technologies in Nowadays. Sensor nodes having limited power, limited processor, limited memory unit and onboard sensors. WSNs having numerous applications such as environment monitoring, area monitoring and pollution monitoring. In WSNs the sensor nodes having limited power and our area of research is to save power of sensor node and increase the network lifetime. This paper deals with efficiently consumption of energy in wireless sensor network. The proposed scheme called Hybrid approach (PSO/GADA-LEACH) improves the energy efficiency in the network, number of packet transferred. The simulation results shows that proposed algorithm is efficient in term of energy consumption and packet transferred. Keywords: PSO (Particle Swarm Optimization), WSNs (Wireless Sensor Network), LEACH (Low Energy Adaptive Clustering Hierarchy), GADA-LEACH (Genetic Algorithm Distance aware- LEACH),BS (base station),ch (cluster head) [1] INTRODUCTION Wireless Sensor Networks (WSN) is an aggregation of sensor nodes which are remotely deployed in large network operate autonomously in an unattended environment. Sensor nodes sense the event according to particular application. WSN include numerous applications such as Bandani Kumari And Shaveta Kalsi 155

2 IMPROVED ENERGY CONSUMPTION FOR HYBRID (PSO/GADA-LEACH) APPROACH IN WIRELESS SENSOR NETWORKS monitoring physical and environmental conditions. Some of its applications include area monitoring, air pollution monitoring, industrial monitoring etc. Sensor nodes having limited power and they need to operate in an unattended environment. WSN consists of thousands of small nodes having numerous capabilities such as sensing, computation and processing capabilities. The energy required for transmission of data is more as compared to sensing and capturing of data. The main our research is to save power, energy consumption and increase lifetime of network. Main components of WSN are as following: 1. Sensor: It is device which converts any physical phenomena such as motion, light, heat into signals. 2. Sensor node: It consists of onboard sensor, memory, power supply etc. 3. Sensor Network: It consists of large number of sensor nodes. There are various types of routing protocols for WSNs such as flat, hierarchical and location based protocols. Hierarchal based or cluster based routing protocols are one of the efficient due to network scalability, energy efficiency. One of the design issues is the formation of clusters and selection of cluster head to reduce the energy consumption in the network. The one of the challenging issue in design of routing protocol is to minimize energy dissipation and maximize the network lifetime. LEACH one of the hierarchical routing protocols though uses cluster based routing to maximizing network lifetime and minimizes energy dissipation. This paper is organized as follows: Section 2discuss related work. Section 3 discuss network model and problem formulation. Section 4 gives an overview of Genetic Algorithm. Section 5 discusses the proposed algorithm.section6 presents the simulation environment and experimental result of Hybrid (GADA-LEACH) approach. Section7 concludes the paper. [2] RELATED WORK The main goal of cluster based routing protocol is to efficiently maintain the energy consumption of sensor nodes. There are several hierarchal routing protocols proposed in the literature for WSNs that supporting longer network lifetime. The energy consumption of the sensor nodes is mainly effected by data transmission and reception of data. Therefore, routing protocols for WSNs should focus on energy efficient routing for extending the lifetime of various sensor nodes and network. Heinzelman et al. [14] proposed LEACH that is one the most popular distributed cluster based routing protocol in wireless sensor network. The process of generating clusters where one node acts as cluster head. Every round is divided into two phases: 1. Cluster building phase: In cluster building phase, one of the node is selected as cluster head which is selected on the basis of cluster head selection. 2. Stable data communication: In this phase, communication process occurs between cluster head and non-cluster nodes. Kumar et al. [3] proposed a protocol EEHC (energy efficient heterogeneous clustered scheme) which aims to increase network lifetime in presence of heterogeneous nodes. In this we divide the nodes into three categories: normal nodes, advance nodes and super nodes. In this the network lifetime and performance of network is improved by using weighted probability of election of cluster head. T. Bhatia et al. [1] proposed a protocol GADA-LEACH, makes use of evolutionary genetic algorithm for improving CH selection in legacy LEACH routing protocol in sensor networks. The concept of relay node is introduced which acts as an intermediary between CH and base station (BS) to ease the communication between the CH and BS. In [6], Particle Swarm Optimization Routing protocol is proposed. The PSOR does routing by considering the energy as a fitness value. In this fitness value of the nodes is calculated and this protocol finds a new path to route the packets. It then selects the route that consumes less energy or select only optimized path to choose an alternate path in case of node failure is quite difficult. Bandani Kumari And Shaveta Kalsi 156

3 [3] NETWORK MODEL AND PROBLEM DESCRIPTION Network model consists of nodes which are setup randomly. Every node consist of some energy (E), probability (P) and sensor position etc. The sink node is located at specific position in the network and numbers of source nodes are also variable. The nodes in the network send data to the cluster head and it further send data to base station. Though various protocols has been proposed so far to improve the energy efficiency further but still much improvement can be done. The work focused on making use of evolutionary genetic algorithm for improving CH selection in LEACH routing protocol in sensor networks. Concept of relay node is also introduced in this which acts as an intermediary between CH and base station (BS) to make the communication between the CH and BS effective and efficient. GADA-LEACH has shown quite significant results in the case of network lifetime. The proposed technique has the ability to overcome the limitations of the GADA-LEACH routing protocol by using the clustering and particle swarm based optimized path selection. The genetics based technique doesn t promise to find a global optimum path. It happens often once the populations have plenty of subjects. [4] EXISTING SYSTEM Genetic Algorithm is an revolutionary algorithm used to generate solutions to optimization and search problems. Such techniques used in genetic algorithm are selection, crossover and mutation. The existing technique is based on genetic algorithm and distance aware routing. In existing algorithm we calculate the fitness of nodes by considering various parameters such as energy of nodes, energy of cluster head etc. The results of GADA-LEACH indicate that the approach significantly improves the lifetime, energy consumption and data delivery to CH and BS. Disadvantages of existing algorithm: 1. Existing algorithm doesn t consider the total energy consumption in the network. 2.It ignores the number of packets delivered and number of dead nodes in the network. 3. The last node becomes dead too early so poor network lifetime occur. [5] PROPOSED TECHNIQUE The various steps required to successfully accomplish the objectives of the paper. The algorithm steps for proposed Algorithm are as following: Step 1: Start:- Process is initialized. Step 2: Deploy WSNs:- After initialization, the Wireless sensor networks are deployed. Step 3: Apply threshold function to get cluster heads: Every node produces random number between 0 and 1.The node announces itself as CH if this number is less than some threshold value, say T(n). Step 4: Associate member nodes with CHs:-The member nodes which are associated with the cluster head get evaluated in Step 3. Step 5: Introduce and evaluate the position of Relay node: Relay nodes are chosen from the normal nodes. Step 6: Apply Hybrid (GADA/PSO) based routing:-pso (Particles Swarm Optimization) and GA are used to find the shortest path between the cluster heads to the sink node for optimal and power aware communication. The PSO algorithm provides the opinion or idea about the global solution among the various particles. Step 7: Transmit data:- Then the transmission of the data get occur. Bandani Kumari And Shaveta Kalsi 157

4 IMPROVED ENERGY CONSUMPTION FOR HYBRID (PSO/GADA-LEACH) APPROACH IN WIRELESS SENSOR NETWORKS Step 8: Evaluate Energy dissipation:- After transmission of the data, dissipation of the energy is evaluated. Step 9: To find node dead:-then it is found that whether the node is dead or not. If the node is dead, then goto step 9, otherwise goto step 3. Step 10: Count dead:- If the nodes are dead in step 10, then the dead nodes are counted. Step 11: To find dead equal to n: - In this, it is found that whether the nodes are equal to n or not. If they are equal, then goto step 12, otherwise goto step 3. Step 12: Network lifetime:- Now the network lifetime is evaluated. Step 13: End. These are the steps which are followed to implement the hybrid (PSO/GADA-LEACH) approach in wireless sensor networks. Flowchart of Hybrid (PSO/GADA-LEACH) Approach: (1) Start Deploy WSNs Apply threshold function to evaluate CHs Associate member nodes with CHs Introduce and evaluate the positon of relay node Apply Hybrid (GADA/PSO) based Routing Transmit data Evaluate energy dissipation No Is any node dead? Count Dead No Is dead==n Yes Network lifetime End Fig.1: Flowchart of Proposed Hybrid (PSO/GADA-LEACH) Approach Bandani Kumari And Shaveta Kalsi 158

5 Fig.1 shows the flowchart of proposed hybrid (PSO/GADA-LEACH) approach. This approach will able to provide better results as compared to existing LEACH, and GADA-LEACH. [6] EXPERIMENTAL RESULTS A MATLAB simulation is done to evaluate the performance. In this section we have evaluated the performance of proposed Hybrid approach and compare it with the existing GADA-LEACH and LEACH on the basis of total energy consumed, number of dead nodes and number of packets delivered. The 100 nodes are randomly distributed in the area of 100*100m².We can use the relay node so the energy consumption of cluster head get decreased and the lifetime of network will increase. There is comparison between energy consumption by LEACH,GADA- LEACH, Hybrid (PSO/GADA-LEACH) approach. [6.1] Simulation Parameters: NETWORK PARAMETERS Network Size VALUES 100*100m² Number of nodes 100 Packet size Routing Protocol 2000,3000,4000 bits LEACH,GADA LEACH,Hybrid(PSO/GADA-LEACH) Initial energy of node (Eo ) 0.1,0.2,0.3, 0.4, 0.5 J/node Energy to run transmitter and receiver (Eelec ) Data aggregation energy (Eda) 50 nj/bit 50 nj/bit Amplification Energy to transmit at shorter distance (Efs ) 10 pj/bit/m² Maximum number of iterations 600 Primary population 100 Crossover rate 0.4 Table 1: Simulation Parameters Table1 represents the simulation parameters which we used to implement LEACH, GADA- LEACH,Hybrid (PSO/GADA-LEACH) approach. The results have been implemented in simulated environment. In GADA-LEACH, the position of base station is outside the network and we introduce the relay node in the centre of the network. Relay node used to decrease the energy degradation of CH.The energy of relay node is higher than CH and less then base station. Bandani Kumari And Shaveta Kalsi 159

6 IMPROVED ENERGY CONSUMPTION FOR HYBRID (PSO/GADA-LEACH) APPROACH IN WIRELESS SENSOR NETWORKS Implementation of LEACH: Cluster Head Selection: Fig.2: Cluster Head Selection In Fig.2, the cluster head selection is random number without considering parameters like location and residual energy of the node. Every node will produce a random number between 0 and 1 and the node will be cluster head if this number is less than some threshold value we can say it as T(n).One node is consider as cluster node and other nodes are non-cluster head node. Energy Dissipation From Sink Node: Fig.3: Energy Dissipation from Sink Node In Fig.3 the energy dissipation from sink node to all other sensor node is dissipated.the energy of each node get vary from iteration to iteration. After completion of iterations, all nodes will get dead. When energy of all the nodes in the network is equal to zero then all node will get dead. Bandani Kumari And Shaveta Kalsi 160

7 Total Packet Transferred: Fig.4: Pictorial Representation of Total Packet Transferred Fig.4 represents the total packet transferred in the network in case of LEACH protocol. X- axis represents number of rounds and Y axis represents the packet transferred. Number of Alive Nodes: Fig.5: Pictorial Representation of Number of Alive Nodes The number of alive nodes at the end of simulation has been plotted in Fig.5.Here in X-axis we have number of rounds and Y axis represents the number of nodes alive in each round. The blue line represents the alive nodes after completion of rounds. Bandani Kumari And Shaveta Kalsi 161

8 IMPROVED ENERGY CONSUMPTION FOR HYBRID (PSO/GADA-LEACH) APPROACH IN WIRELESS SENSOR NETWORKS Total Energy Consumed: Fig.6: Pictorial Representation of Total Energy Consumed The consumed energy of all sensors nodes at the end of simulation has been plotted in Fig.5.Here in X-axis we have number of rounds and Y axis represents the energy level. The initial energy level started from 0.1,0.2, 0.3,0.4, 0.5 J/node. Implementation of GADA-LEACH: Total Packet Transferred: Fig.7: Pictorial Representation of Total Packet Transferred Bandani Kumari And Shaveta Kalsi 162

9 Fig.7 represents the total packet transferred in the network in case of GADA-LEACH protocol. X-axis represents number of rounds and Y axis represents the packet transferred. The blue line represents the packet transferred in GADA-LEACH. Number of Alive Nodes: Fig.8: Pictorial Representation of number of Alive nodes The number of alive nodes at the end of simulation has been plotted in Fig.5.Here in X-axis we have number of rounds and Y axis represents the number of nodes alive in each round. Total Energy Consumed: Fig.9: Pictorial Representation of Total Energy Consumed The consumed energy of all sensors nodes at the end of simulation has been plotted in Fig.9.Here in X-axis we have number of rounds and Y axis represents the energy level. The initial energy level started from 0.1, 0.2, 0.3,0.4, 0.5 J/node. The plotted line shows the energy consumption in case of GADA-LEACH. Bandani Kumari And Shaveta Kalsi 163

10 IMPROVED ENERGY CONSUMPTION FOR HYBRID (PSO/GADA-LEACH) APPROACH IN WIRELESS SENSOR NETWORKS Implementation of Hybrid (PSO-GADA) Approach: Total Packet Transferred: Fig 10: Pictorial Representation of Total Packet Transferred Fig.10 represents the total packet transferred in the network in case of Hybrid (PSO/GADA- LEACH) protocol-axis represents number of rounds and Y axis represents the packet transferred. Number of Alive Nodes: Fig.11: Pictorial Representation of Number of Alive Nodes The number of alive nodes at the end of simulation has been plotted in Fig.11.Here in X-axis we have number of rounds and Y axis represents the number of nodes alive in each round. Bandani Kumari And Shaveta Kalsi 164

11 Total energy Consumed: Fig.12: Pictorial Representation of Total Energy Consumed The consumed energy of all sensors nodes at the end of simulation has been plotted in Fig.12.Here in X-axis we have number of rounds and Y axis represents the energy level. The initial energy level started from 0.1,0.2, 0.3,0.4, 0.5 J/node. The plotted line shows the energy consumption in case of hybrid (PSO/ GADA-LEACH) approach. Comparison on the basis of Average consumed energy in GADA-LEACH and Hybrid (PSO/GADA-LEACH) approach: Initial Energy GADA-LEACH Hybrid(PSO/GADA-LEACH) Table 2: Average Consumed Energy Analysis The average consumed energy of all sensors nodes at the end of simulation has been plotted in Fig.13. The graph shows that hybrid (PSO/GADA-LEACH) approach has better consumed energy over the entire network in a more balanced way. From Table 2, it has been clearly Bandani Kumari And Shaveta Kalsi 165

12 IMPROVED ENERGY CONSUMPTION FOR HYBRID (PSO/GADA-LEACH) APPROACH IN WIRELESS SENSOR NETWORKS shown that the hybrid (PSO/GADA-LEACH) approach performs better over the GADA- LEACH. Average consumed Energy Numbee of rounds Initial energy PSO/GADA-LEACH GADA-LEACH Fig.13 Graph shows average energy consumed in GADA-LEACH and PSO/GADA-LEACH approach [7] CONCLUSION In this study, we proposed an hybrid approach for selecting optimal path in the network that prolong network lifetime,packet transferred as well as energy consumption is improved in hybrid approach. Although numbers of clustering protocols in WSNs have been proposed in the literature, yet they need to consider various factors such as total packet delivered, number of dead nodes and total energy consumed. The proposed approach is efficient as it considers the total energy consumed by all nodes, number of dead nodes and packet transferred. The simulation results shows that hybrid approach is efficient are compared to GADA-LEACH in terms of average energy consumed. REFERENCES [1] T. Bhatia et al., A genetic algorithm based distance-aware routing protocol for wireless sensor networks, Computers and Electrical Engineering (2016): 11:10. [2] Vinesh Kumari et.al, Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey, International Journal of Computer Applications ( ) Volume 100 No.5, [3] Lee SL, Park J, Shon JG. A two-layer cluster head selection based on distance in wireless sensor networks In: Computer science and its applications. Springer Berlin [4] Miao H, Xiao X, Qi B, Wang K. Improvement and application of LEACH protocol based on genetic algorithm for WSN. In: computer aided modelling and design of communication links and networks (CAMAD), 2015 IEEE 20th international workshop on; p [5] Balamurugan A. An energy efficient fitness based routing protocol in wireless sensor networks. ICTACT J Commun Technol 2014;5(1). [6] Snehal Sarangi and Biju Thankchan, Particle Swarm Optimization based A Novel Routing Algorithm for Wireless Sensor Network, International Journal of Research in Engineering, Information Technology and Social Sciences, Vol. 2, No. 11, Bandani Kumari And Shaveta Kalsi 166

13 [7] Peiravi A, Mashhadi HR, Hamed Javadi S. An optimal energy-efficient clustering method in wireless sensor networks using multi-objective genetic algorithm. Int J Commun Syst 2013;26(1): [8] Nikolaos AP, Stefanos AN, Dimitrios DV Energy-efficient routing protocols in wireless sensor networks: a survey. IEEECommun Surv Tut 2013;15(2): [9] Haneef M, Deng Z. Design challenges and comparative analysis of cluster based routing protocols used in wireless sensor networks for improving network life time. Adv Inf Sci Serv Sci 2012; 4: [10] Karimi M, Naji HR, Golestani S. Optimizing cluster-head selection in wireless sensor networks using genetic algorithm and harmony search algorithm. In: electrical engineering (ICEE), th Iranian conference on. IEEE; p [11] Liu JL,Ravishankar CV. LEACH-GA: Genetic algorithm-based energy-efficient adaptive clustering protocol for wireless sensor networks.int J Mach Learn Comput 2011;1(1): [12] AbuBakr B, Lilien L. Extending wireless sensor network lifetime in the LEACH-SM protocol by spare selection. In: proceedings of the fifth international conference on innovative mobile and internet services in ubiquitous computing (IMIS 11). Washington, DC, USA: IEEE Computer Society; p [13] Gautam N, Jae-Young P. Distance aware intelligent clustering protocol for wireless sensor networks. J Commun Netw 2010;12(2): [14] Heinzelman WR, Chandrakasan A, Balakrishnan H. LEACH: energy efficient communication protocol for wireless microsensor networks. In: proceedings of Hawai International Conference on System sciences. Maui, Hawaii; p Jan. [15] Khedr AM, Osamy W, Agrawal DP. Perimeter discovery in wireless sensor networks. J Parallel Distrib Comput 2009;69 : [16] Gou H, Yoo Y, Zeng H. A partition-based LEACH algorithm for wireless sensor networks. In: computer and information technology. CIT 09. Ninth IEEE international conference on, 2. IEEE; p [17] Guo S, Yang O, Energy-aware multicasting in wireless ad hoc networks: a survey and discussion. In: Computer communications, 30(9). Elsevier; p [18] Al-Karaki JN, Kamal AE. Routing techniques in wireless sensor networks: a survey. IEEE Wireless Commun 2004; 11(6):6 28. [19] Akyildiz IF, Su W, Sankarasubramaniam Y,Cayirci E. A survey on sensor networks. IEEE Commun Mag 2002; 40 (8): [20] Whitley D. A genetic algorithm tutorial. Stat Computing 1994;4(2):65 8. Bandani Kumari And Shaveta Kalsi 167