A ROUTING OPTIMIZATION AND DATA AGGREGATION SCHEME BASED ON RF TARANG MODULE IN WSN

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1 A ROUTING OPTIMIZATION AND DATA AGGREGATION SCHEME BASED ON RF TARANG MODULE IN WSN Saranya.N 1, Sharmila.S 2, Jeevanantham.C 3 1,2,3 Assistant Professor, Department of ECE, SNS College of Engineering Coimbatore, (India) ABSTRACT A huge number of Wireless Sensor Network applications involved in a set of isolated urban area covered by sensor nodes monitor the environmental parameters like pressure, heart signal monitoring, temperature etc. The key challenge in the proposal of WSN is being the power consumption of the entire network thereby extending the network lifetime. In Heterogeneous WSN, the use of single and multi-hop energy efficient clustering protocols(s- EECP & M-EECP) are aims to be provide good network lifetime and it is more energy efficient protocols. On comparing these protocols, the Multi-hop energy efficient clustering protocol only suits for long distance communication because it shares the energy with intermediate nodes it has a high packet delivery ratio with some extent of energy consumption. The proposed concept multi-hop energy efficient clustering protocol (M-EECP) aims to increase the packet delivery ratio and for the application of Healthcare Monitoring in terms of temperature by controlling the packet loss based on alternate path selection. Keywords-Wireless Sensor Network (WSN), protocol, healthcare monitoring, energy, sensor node. I.INTRODUCTION WSN is becoming very important aspect in the human s life. Wireless Sensor Networks have been an active research area over the past few years because it is an important part of medical application. In medical healthcare system, it can be used as patient monitoring system. For medical monitoring system it requires some kind of hardware resources such as Sensors, Tarang module, microcontroller, power supply, computer and also network will be formed of sensor and hardware for solving the problems in Healthcare system.wsn consist of sensor node, Battery, ADC, Transceiver, Power Supply and Controller. It is a self-organization wireless network system constituted by number of micro sensors with limited energy. They are deployed to monitor the sensing field and collect information from physical or environmental conditions. These sensors co-operatively pass the collected data through the network to a main location. Due to the limited location energy and communication limitation of sensor 62 P a g e

2 nodes, it seems especially important to design an energy efficient routing protocol for WSN. Energy consumption is an important factor in the architecture design of WSN s. In WSN scheduling place an dominant role in reducing sensor energy consumption. Most of the existing scheduling schemes do not optimize energy consumption. Higher the energy consumed by the sensors, higher will be the depletion of its battery. This drastically reduces the network lifetime of WSN. The energy constraint is a major factor affecting the QoS of the system. Most of the energy is spent during transfer of data packets from sensor to destination. In order to reduce the energy consumption mobile sinks have been adopted. II. ARCHITECTURE OF WSN Sensor nodes consist of small or large number of nodes in the sensor network. These nodes have different types of modules such as sensor module, processing module, wireless communication module and power supply module. To make the sensor operation in wireless sensor network, these modules work together in such environment. Sensor module includes signal sampling A/D conversion and signal modulation. Based on the observed phenomena, sensors produce the analog signals which are converted into digital signal by A/D. Processing module include the controlling the sensor, communication between protocols and processing the data or information. The digital signals from the sensor module are fed into the processing module that carries sensing tasks. Fig. 1. Architecture of WSN In wireless communication module, a transceiver generates the radio waves and also connects the nodes to the network. The power supply modules consist of power unit (battery) which is supported by power scavenging unit such as solar cells. 63 P a g e

3 III. EXISTING SYSTEM When considering a general sensor network which may be deployed over a dense region, the energy spend in the power amplifier connected to distance may dominate to such a degree that using multi-hop mode may be more efficient than single hop mode. The heterogeneous network consists of three types of sensor nodes deployed uniformly in a region, that is, normal, super and advanced node. For single hop communication the cluster head (CH) tend to deplete the battery energy faster than other nodes. Here the packets are directly transmitted to the base station without any relay, does the nodes located far away from the base station (BS) have higher energy burden because of long range transmission and these nodes may die out first. It adopts single hop transmission intra cluster and inter cluster communication. The existing system is mainly based on the way of communication in which to attain the high packet delivery ratio with the consumption of low energy. The evaluation is based on clustering-based protocols which are single-hop energy efficient protocol. Fig. 2. Single Hop Approach In S-EECP, the cluster heads (CHs) are elected by a weighted probability based on the ratio between average energy of the network and the residual energy of each node. The nodes having more initial energy and residual energy will have more chances to be elected have CHs than nodes with lower energy. In M-EECP, the elected CH communicates the data packets to the base station via multi-hop communication approach. To analyze the network lifetime three types of sensor nodes equipped with different battery energy are assumed. Fig. 3. Multi-hop approach 64 P a g e

4 IV. PROPOSED SYSTEM The proposed system has three sections. A. Transmitter section B. Repeater section C. Receiver section A.Transmitter Section The transmitter section consists of atmega16, LM 35, RF TARANG module, crystals, and voltage regulator. In LM 35, the output voltage is linearly proportional to the Celsius (centigrade) temperature. The temperature senses the temperature up to 150 C. The initial voltage is 10V. The voltage regulator in the transmitter is use to convert the initial voltage into 5V. Atmega16 contains 16 Kbytes and Atmega16 AVR is supported with the suite of program and system development tools. In order to reduce power consumption, the clocks to modules not being used can be halted by using different sleep modes. The signals sensed from sensor are transmitted to the repeater section. B. Repeater section The repeater section consists of RF TARANG module, which is used to send the received signals from the transmitter section to the receiver section. C. Receiver section The receiver section consists of atmega16, Trimpot, voltage regulator, crystals, and LCD display. The RF TARANG module receives the signals from the repeater section and the temperature is displayed in LCD display. The command register stores the command instructions to the LCD. Fig. 4. Block Diagram of Proposed System Sensor nodes are randomly deployed in the environment. When the data transmission starts a cluster is formed with cluster members and cluster head. The cluster head is chosen based on the threshold energy per round of transmission by using multiple intermediate nodes, than the data will be transferred to base station efficiently. 65 P a g e

5 V. RESULTS AND DISCUSSION A. Software Results 1).Energy Consumption The energy model represents the energy level of nodes in the networks. The energy model define in a node has a initial value that is the level of energy the node has at the beginning of the simulation. Fig. 5.Overall Energy Consumption Fig. 6. Residual energy for each node This energy is termed as initial energy. In simulation, the variable energy represents the energy level in a node at any specified time. The value of initial energy is passed as an input argument. A node loss an particular amount of energy per every packet transmitted and received. As a result, the value of initial energy in a node gets decreased. If an energy level of a node reaches zero, it cannot receive or transmit anymore packets. 66 P a g e

6 2). Residual energy The energy models represent the energy level of the node in the networks. The value of initial energy in a node gets decreased. The current value of energy in node after receiving or transmitting routing packets is the residual energy. Data transmission is established between nodes using UDP agent and CBR traffic. Residual energy of the node is evaluated by accessing inbuilt energy in find energy procedure at different times. Fig. 7. Overall Residual Energy Fig. 8.Residual energy for each node 3). Packet Delivery Ratio (PDR) PDR is defined as the ratio between the received packets by the destination and the generated packets at the source. PDR is calculated using awk script which processes the trace file and produces the result. It is the ratio of number of deliver packet to the destination. 67 P a g e

7 Fig. 9. Packet Delivery Ratio B. Hardware Results The sensor senses the temperature and transmits to the given address (repeater section). The repeater section transmits the received signals to the receiver. Fig. 10. Transmission of signals using TARANG module In receiver, LCD displays the temperature which receives the signal from the repeater section. VI. CONCLUSION AND FUTURE WORK The present system can support with real time, low power, long distance and dual mode monitoring. The use of RF Tarang module is the communication processor of building blocks of the monitoring system as the benefits of intelligence, compact size and reliability. By the aid of these modules, external components and wirings are kept to a minimum. The PDR is 66.28%.The proposed system can be enhanced by including the security attacks to reduce packet loss. 68 P a g e

8 REFERENCES [1]. Abbasi A.A. and Younis M.(2007) A Survey on clustering algorithms for wireless sensor networks, Elsevier comput. Commun., Vol.30,pp [2]. Al-Karaki J.N. and Kamal A.E.(2004) Routing techniques in wireless sensor networks: a survey on wireless communication,ieee 11(6):pp [3]. Ashfaq Ahmad, Nadeem Javaid-Member IEEE, Zahoor Ali Khan Member IEEE Umer Qasim and Turki Ali Alghamdi.(2014) Routing scheme to maximize lifetime and throughput of wireless sensor networks. [4]. Aslam M., Javaid N.,Rahim A.,Nazir U., Bibi A. and Khan Z(2002) Survey of external Leach-based clustering routing protocol for WSN, In Proc.9 th IEEE INT. Conf. Embedded softw.syst.,proc.14 th Int. Conf. High Perform. Comput. Commun. (HPCC-ICESS),pp [5]. Charalampos Konstkntopoulos, Grammati Pantziou,Damianos Gabales, Aristides Mpitzioupoulos and Basilis Mamalis, A Rendezbous- Based Approach enabling energy efficient sensor data collection with mobile scheme, Vol.23, no.5, May [6]. Haifeng Zheng.Feneng Yang.Xiaohua Tian.Member. IEEE.Xiaoyang Gan,Xinbing Wang,Senior member,ieee and Shiling Xiao, Member IEEE, Data Gathering with Compressive Sensing in Wireless Sensor Networks:A Random Walk Based Approach,IEEE Transactions on parallel and distributed systems,vol.26,no.1,jan [7]. Hairong Zhao,Wuenung, Zhou,Yan Gao.(2012) Energy efficient and clustering based routing protocol for WSN IEEE international conference on Computational intelligence and security,pp [8]. Moumita Pramanick,Chandreyee Chwdhury, Paramita Basik, Md. Abdullah Al- mamum and Sarmistha Neogy, An Energy Efficient Routing Protocol for WSN,2015 AIMoC. 69 P a g e

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