INCREASING ENERGY EFFICIENCY AMONG HOMOGENEOUS SENSOR NODES USING HYBRID ROUTING PROTOCOL IN A DENSELY DEPLOYED WSNS

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1 Volume 115 No , ISSN: (printed version); ISSN: (on-line version) url: ijpam.eu INCREASING ENERGY EFFICIENCY AMONG HOMOGENEOUS SENSOR NODES USING HYBRID ROUTING PROTOCOL IN A DENSELY DEPLOYED WSNS Pradeepa.R 1, Rajkumar.K 2, Dharshana.P 3 1 M.Tech-CSE, School of Computing, SASTRA University, Thanjavur ,India 1 pradeeparpt@gmail.com 2 Assistant Professor, 3 B.Tech-CSE, School of Computing, SASTRA University, Thanjavur ,India Abstract: The most critical complication in Wireless Sensor Network (WSN) is the energy consumption of nodes. Some techniques were introduced to saving battery power of nodes in WSNs. Modern researches have shown that clustering is a well organized technique for cognizing a network and that it stabilizes the traffic of the sensor nodes. Clustering is the foremost scheme for maintaining energy efficiency among nodes in WSNs. The various types of clustering includes Event-to-Sink directed clustering, Load Balanced clustering, K-means clustering, Adaptive clustering, Hierarchical clustering, Hybrid clustering and Weight based clustering. Energy efficient routing is a major task in the area of Wireless sensor networks. There are various routing protocols for WSN such as flat, clustering and hierarchal routing protocol. We have offered three techniques in this paper. Initially we have proposed the formation of clusters, finding active nodes, finding active route for communication from source to destination. The exploratory reviews are directed through network simulator ns-2.34 Keywords: Energy efficiency, Routing, Wireless sensor network, Clustering 1. Introduction 1.1 Wireless sensor networks The ultimate focus of this is to detect and also announce incidents happening in the world. The sensor nodes can sense, compute and communicate the events in an environment. The environment is the physical world, information technology frameworks and biological systems. A sensor networks includes the following components; a get together of disseminated sensor, an interconnecting system, a main issue of data grouping, an arrangement of figuring assets at the essential issue to handle information, connection, status questioning and information mining. WSN holds massive amount of sensor nodes which can be organised to make a well organized network. 1.2 Clustering Clustering is an efficient technique to increase energy efficiency among nodes. Every clustering technique forms a cluster based on minimum distance from base station and elects cluster head (CH). The CHs are responsible for overall working of nodes within the cluster. Its main role is to avoid data redundancy and to collect the events happening in an environment and to finally present it to the Base Station (BS). 2. Literature Survey Routing protocols can be categorized based on structure of network, operations of protocol and formation of path. The Routing path can be constructed in three ways proactive, reactive and hybrid. Proactive routing computes entire routes and stores these routes in a routing table. Reactive routing protocols determine routes only when they are required. In large networks, proactive routing is not suitable. Hybrid routing protocol is the combination of proactive and reactive which was proposed by Rajashree V.Biradar et al [1]. There are two major categories of WSN: Homogeneous and Heterogeneous sensor networks. Homogeneous consists of similar characteristics of nodes. Heterogeneous consists of similar characteristics of nodes with extra capabilities. The connectivity of nodes includes single hop and multi hop connectivity. In order to save energy of nodes in WSNs, it uses LEACH in single hop cluster sensor network and M- LEACH in Multi hop cluster sensor network. This was proposed by Vivek mahatre et al [2]. They also proposed that M-LEACH is more energy efficient than LEACH. The important trait of PEGASIS is followed as, 1) All nodes have universal knowledge about network. 2) Chain creation starts from the nodes that are afar from the sink. LEACH and PEGASIS is not suitable to event based applications. In the case of TEEN protocol, it is applicable for event based applications. To bear periodic information APTEEN has been proposed by Sanjolly Jain and Amit Grover [3]. To shun data redundancy sent throughout the network is done by SPIN protocol. SPIN checks the 83

2 current level of energy among sensor nodes and also saves battery power among nodes. SPIN does not have any cluster head (CH) so it uses less energy. By the comparison among LEACH and SPIN, LEACH consumes more energy, as proposed by Geetu et al and Sonia suneja [4].Energy Efficient Tree Based data protocol, proposed by Jin et al [5], is used to enhance nodes energy by using flooding avoidance and cascading timing schemes. EEDCP-TB protocol not only increases the energy efficiency of nodes but also enhances the lifetime of Wireless Sensor Networks. Balanced Aggregation Tree Routing (BATR) protocol is used for stabilizing the energy consumption across all nodes using optimal or near optimal minimum spanning tree. In order to avoid data redundancy, overheads of messages are controlled. It helps in long distance communication. BATR was proposed by Kim and Han [6].Chain Routing with Even Energy Consumption is used to expand the equity distribution of energy at every sensor nodes in the network. CREEC protocol is used for setup strength, redundancy of data and patching overheads because of extension of chain size. This was proposed by shin and sun [7].Greedy based routing (GBR) protocol used to utilize the power and enhance the life time of WSNs. GBR has the admirable routing performance in terms of balanced power efficiency and routing path distribution for routing path security [8]. 3. Proposed Methodology and approach The taxonomy of routing protocol [10] is categorized based on originator of communication, formation of path, composition of network, performance of protocol and following hop selection. The communication is source and destination based. The path formation is based on proactive or reactive or hybrid (Hybrid routing protocols combines the metrics of proactive and reactive routing). Network structure follows flat, hierarchical or location based. The operation of protocol is based on multipath, query, negotiation and QoS based. The next hop connectivity is broadcast, location, probabilistic and content based. Here hierarchical clustering is followed and the operation is based on multipath based routing algorithms. It is used to label inter and intra cluster routing issues in densely deployed WSNs [11]. The whole working rule is segregated in to three segments are as follows. 1. Cluster formation (CF) 2. Sensing of Active nodes (SAN) 3. Routing among Active nodes (RAN) 3.1 Cluster formation of nodes (CF) Initially, create a densely connected network by deploying numerous nodes based on regular deployment (Fig 1). After that, form clusters in which nodes can to communicate with all other nodes and elect one node as centralized Base station. This node initiates communication among other nodes by sending Hello packets. The cluster formation algorithm (Fig.2) is done by calculating the node s Euclidean distance from the centralized node as BS. The nodes having minimum distance from BS and the nodes receiving hello packets can form a cluster after electing a cluster head. The node in the cluster that has the highest connectivity and has more residual energy is elected as Cluster head. Cluster formation algorithm is mainly responsible to scatter data traffic and loads equally in the network by presenting different form of clusters in the system. Deploying nodes Figure1. Deployment of nodes-densely deployed network Figure 2. Formation of cluster using CF 3.2 Sensing of Active nodes (SAN) The main trait of sensing active node algorithm is to prevent overlapping of data. During communication between each cluster of nodes, the node having more residual energy is activated as active node (Fig.3) and the remaining nodes are in a sleep state. In order to save the energy among nodes, active nodes are involved in communication. In case of any sudden failures in active nodes, the backend active nodes (Fig.4) are awakened during communication. It gathers information and finally sends it to centralized node (BS). Active nodes are elected based on residual energy calculation of nodes. After receiving approximate packets from source to destination, active nodes changes stage by stage and senses the events. The main focus of selection of 84

3 active node is reducing redundancy of data and also save the cost of huge energy consumption by reducingthe transportation distance. To avert collision of data packet, every leader node is answerable for electing its nodes as active performing, in observing a distinctive TDMA approach by persuading that two nodes possess the identical time frame. If the nodes possess identical active node selection value, then the preference is given to the node which has minimal space from CH. To share the tasks and spreading load uniformly in the network, In every round the active node revolves in time to time and new active node is Figure 5. Routing of active nodes using RAN established. 4. Network model First, they offers cluster formation algorithm labeled as CFA.The objective of CFA is to scatter data traffic and load equally in the system by offering different form of clusters in the network. Second, they present sensing mechanism called Sensing Active Node Algorithm (SAN) to avert overlapping of data and repetition of data. Third, they suggests Routing Active Node Algorithm (RAN) to label tedious inter and intra cluster Figure 3. Sensing of active nodes using SAN routing problems. The proposed network model follows three stages of mechanisms including clustering mechanism, sensing mechanism and routing mechanism. In clustering mechanism, we have done the cluster formation, in sensing mechanism we have done sensing of active nodes based on active node sensing value. At last, in routing mechanism, we choose a minimimun distance route among active nodes. Here (Fig 6) firstly create a densely deployed network by deploying various sensor nodes. Each and every node involved in communication by broadcasting messages Figure 4. Sensing of Backend active nodes among themselves and formation of cluster based on CFA and then finding the active node based on SAN 3.3 Routing among Active Nodes (RAN) and finally form a active node routing based on RAN. To avoid network traffic we are proposing a node routing The whole network model is schematically represented algorithm. It segregates the whole network in to two in Fig.6. segments, from observing region to CH and CH to the final destination node. Routes can be found using the method of minimum spanning tree. In MST technique, the node having minimum transmission distance from source to destination is chosen and this route is selected for communication among nodes. The main objective of this routing method is to provide robust routing and minimizing the delay in WSNs. Another important objective of this technique is minimizing the cost of communication and energy consumption in WSNs.To split the whole network, data service workload and to scatter load are uniformly split in the network. If two or more nodes have same transmission distance from source to destination then the preference is given based on the source node that sends a message to 5. Performance analysis and simulation results destination node and the node that first sends the acknowledgement message back to source node is selected In this framework we analyze the various performance as a best route. (Fig.5) representing active node routing measures in the upcoming graphs; based 85

4 5.1 Consumption of energy In most of the case, consumption of energy among nodes is noticed that network s strength is straightly propositional to energy consumption of network. The sensor nodes with minimal level of consumption of energy are considered as well constructed network. Our innovative studies observed that the energy consumption of network in all routing strategy is straightly accompanied with the entire rounds and time(s) of nodes involved in the system. Compared to other routing techniques, the staging of hybrid routing protocol (HRP) has witnessed extraordinary results in the period of attaining a minimal consumption of energy (Fig.7). In our proposed scheme, we initially set the energy of node as 5 and our simulation results proves that all the nodes involved in communication, that is each and every node will not depleting their energy below 4.85 by attaining a minimum level of consumption of energy using HRP and using Adhoc on demand routing. Throughput=Received data*8/data transmission period (or) packet size *recv *8.0 Fig.8 shows the relationship between the delay with respect to packet id and in Fig.9 throughput is related with time. Figure 8. Average end-to-end delay Figure 9. Throughput 6. Conclusion Figure 7. Energy consumption of nodes 5.2 Delay and Throughput Delay is the one more circumstance that affects the whole performance of network and it can be calculated are as follows Delay=end time Start time End -to-end delay=n-to-n delay delay[i] Average End-to-End delay=n-to-n delay*1000 ms In our proposed scheme, we deploy 61 nodes and after finishing the above mentioned three mechanisms and done all the calculations. In comparison with other routing schemas Hybrid routing protocols plays a remarkable role in terms of achieving a minimum delay(fig 8) and maximizing the throughput(fig 9) and the life of network. The throughput can be evaluated are as follows In this Proposed system, it report different clustering and routing technique is used to manipulate issues of clustering, sensing and routing in densely deployed WSNs and also some performance measures. Here we proposed Hybrid routing protocols and their ultimate design to improve the network lifetime and increasing the energy efficiency among sensor nodes. In future, the researchers proposes some other efficient algorithm for increasing energy efficiency of nodes in WSNs and to investigate the rendering criteria together including lifetime of WSN, ratio of packet delivery, redundancy of data in more complicated homogeneous and heterogeneous scenario. References [1] Biradar, Rajashree V., V. C. Patil, S. R. Sawant, and R. R. Mudholkar. "Classification and comparison of routing protocols in wireless sensor networks." Special Issue on Ubiquitous Computing Security Systems 4, no , [2] Mhatre Vivek and Catherine Rosenberg. "Homogeneous vs heterogeneous clustered sensor 86

5 networks: a comparative study." In Communications, 2004 IEEE International Conference on, vol. 6, pp , [3] Al-Karaki, Jamal N., and Ahmed E. Kamal. "Routing techniques in wireless sensor networks: a survey." IEEE wireless communications 11, no. 6, 6-28, [4] Engg, H. C. E. "Performance Analysis of SPIN and LEACH Routing Protocol in WSN." [5] Jin, Yong-xian, Feng-zhen Chen, Gao-feng Che, and Wei Hu. "Energy-efficient data collection protocol for wireless sensor network based on tree." In Wearable Computing Systems (APWCS), Asia-Pacific Conference on 2010, pp , [6] Kim, Hyun-sook, and Ki-jun Han. "A power efficient routing protocol based on balanced tree in wireless sensor networks." In Distributed Frameworks for Multimedia Applications, DFMA'05. First International Conference on IEEE, pp , [7] Shin, Jisoo, and Changjin Suh. "CREEC: Chain routing with even energy consumption." Journal of Communications and Networks 13, no.1, 17-2, [8] Yang, Wenjing, Xinyu Yang, Shusen Yang, and Dongxu Yang. "A greedy-based stable multi-path routing protocol in mobile ad hoc networks." Ad Hoc Networks 9, no.4, ,2011 [9]Akkaya, Kemal, and Mohamed Younis. "A survey on routing protocols for wireless sensor networks." Ad hoc networks 3, no.3, , [10] Acs, Gergely, and Levente Buttyán. "A taxonomy of routing protocols for wireless sensor networks." BUTE Telecommunication department, [11] Faheem, Muhammad, Muhammad Zahid Abbas, Gurkan Tuna, and Vehbi Cagri Gungor. "EDHRP: Energy efficient event driven hybrid routing protocol for densely deployed wireless sensor networks." Journal of Network and Computer Applications 58, , [12] V.Pradeep Kumar, Multi Critical Event Monitoring in WSN using Sleep Scheduling, International Innovative Research Journal of Engineering and Technology, 27-29,

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