Paper id 26201472

International Journal of Research in Advent Technology, Vol.2, No.6, June 2014 E-ISSN: 2321-9637

Wireless Sensor Network Optimization using Different Design Parameters and Routing Techniques Priyanka1, Yogesh Juneja2 Electronics and communication1, 2, PDM college of Engg1, 2 Email: pbhardwaj45@gmail.com1 , yogeshjunejaer@gmail.com2

Abstract- Wireless Sensor Networks (WSNs), with growing applications in the environment addressed tremendously in the recent past. Many routing algorithms proposed to optimized working of network, mainly focusing energy efficiency, network lifetime, clustering processes. Considering homogeneity of network, we proposed Energy Efficient Sleep Awake Aware (EESAA) intelligent routing protocol for WSNs. In EESAA unstable region starts very later as compare to other protocols. Results show that in EESAA nodes die at a constant rate. In our proposed technique we evaluate and enhance certain issues like network stability, network lifetime and cluster head selection process. In EESAA nodes also switches between sleep and active modes in order to minimize energy consumption.

Index Terms- EESAA, WSN, ADC 1.

1. INTRODUCTION Developments in wireless, mobile communications combined with advancements in electronics have contributed to the emergence of a new class of networks: Wireless ad-hoc sensor networks. Tiny, smart, network-enabled sensing nodes can be deployed to construct sensor fields that form the infrastructure for various self-adaptive and autonomic applications. The main problem in wireless communication networks is the field nodes (mobile or stationary) are battery resource constrained. Consider a situation of multi-hop wireless communication in a sensor network in which the information from a node is transferred to the base station using ad hoc multi hop network. That is, the sensed information from a field sensor node is forwarded by multiple intermediate nodes until information reaches the base station. Sensor networks are also inherent in the concepts of smart dust [1] and ubiquitous computing [2]. Smart dust technology concerns the design and implementation of networks consisting of tiny, invisible sensing grains that aim to be untraceable in practice. Currently, smart dust motes scale down to 1mm2. On the other hand, ubiquitous computing concerns the building of intelligent environments. By placing a processor behind virtually every object, the computers are drawn out of their racks to be seamlessly integrated with the physical environment and form a ubiquitous infrastructure that will monitor and/or support every human activity from the simplest to the most complex one.

Network lifetime: Network lifetime is duration from start till last node is alive.

2. Instability period: It is duration of network operation from first node dies till the least node dies.

3. Number of Cluster-heads:It indicates the number of clusters generated per round.

4. Packet to BS: It is rate of successful data delivery to BS from CHs. There are four basic components that can be found in all sensor nodes. These components are: a power unit, a processing unit, a sensing unit and a transceiver.

Some sensor nodes also contain optional components such as a location finding system, a mobilizer or a power generator. Fig. 1 shows the basic components.

The power unit is very important in a sensor node. It is responsible for providing all of the other units with energy so that the node can perform its functions. A power generator or power scavenging unit can support the power unit. Solar cells could be used as power scavenging units.

2. WIRELESS SYSTEM Design Performance Parameters For analyzing the performance of EESAA protocol we consider the following metrics as given Stability period: It is duration of network operation from start till first node dies.

Fig. 1 The basic components of a sensor node.

The power unit is very important in a sensor node. It is responsible for providing all of the other units with energy so that the node can perform its functions. A

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International Journal of Research in Advent Technology, Vol.2, No.6, June 2014 E-ISSN: 2321-9637 power generator or power scavenging unit can support the power unit. Solar cells could be used as power scavenging units. Clustering algorithms like LEACH, and DEEC [3,4] for sensor networks have achieved reasonable goals regarding better performance of networks.

The processing unit consists of a processor and some storage or memory. This unit is responsible for managing the tasks of the sensor unit. The sensing unit generally consists of a sensor and an analogue to digital converter (ADC). The ADC converts the analogue data from the sensor to digital data that can be processed by the processor. The transceiver connects the sensor node to the network [6]. The transceiver can use either radio frequency (RF) or optical communications, such as infrared, to wirelessly connect to the network.

Routing Protocol with 4000 rounds and 100 nodes.

Fig. 2 shows the Advance Network Coupling Model with 4000 rounds. Fig. 3 demonstrates the Dead Nodes for 100݉ × 100݉ Network with 100 nodes with 4000 rounds. Fig 4 depicts the Alive Nodes for 100݉ × 100݉ Network with 100 nodes with 4000 rounds. Fig. 5 shows the Packet to BS Nodes for 100݉ × 100݉ Network with 100 nodes with 4000 round. Fig. 6 depicts the Count of Cluster Head per round for 100݉ × 100݉ Network with 100 nodes with 4000 round.

3. SIMULATION RESULTS The Energy Efficient Sleep Awake Aware (EESAA) Routing Protocol is present. Simulation is presented using Matlab for analyzing the performance of EESAA protocol.

Fig. 2 Advance Network Coupling Model with 4000 rounds

Displayed equations should be numbered consecutively, with the number set flush right and enclosed in parentheses. The equation numbers should be consecutive within the contribution.

The analysis of the Energy Efficient Sleep Awake Aware (EESAA) Routing Protocol is shown below: Table 1- Different design parameters

Design Parameters

Chosen Values

Network size

100m * 100m

Initial Energy

.5 J

ܲ݀

.1 J

Data Aggregation Energy cost

50pj/bit j

Number of nodes

100

Packet size

4000 bit

Transmitter Electronics (EelectTx) Receiver Electronics (EelecRx) Transmit amplifier

50 nJ/bit

Fig. 3 Dead Nodes for 100݉ × 100݉ Network with 100 nodes with 4000 rounds

50 nJ/bit 100 pJ/bit/m2

(Eamp)

Fig. 4 Alive Nodes for 100݉ × 100݉ Network with 100 nodes with 4000 rounds

EESAA Routing Protocol analysis with 4000 rounds In this example, we analysis the performance of Energy Efficient Sleep Awake Aware (EESAA)

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International Journal of Research in Advent Technology, Vol.2, No.6, June 2014 E-ISSN: 2321-9637

Fig. 5 Packet to BS Nodes for 100݉ × 100݉ Network with 100 nodes with 4000 round

Fig. 8 Dead Nodes for 100݉ × 100݉ Network with 100 nodes with 5000 rounds

Fig. 6 Count of Cluster Head per round for 100݉ × 100݉ Network with 100 nodes with 4000 round

EESAA Routing Protocol analysis with 5000 rounds In this example, we analysis the performance of Energy Efficient Sleep Awake Aware (EESAA) Routing Protocol with 3000 rounds and 100 nodes.

Fig. 7 shows the Advance Network Coupling Model with 5000 rounds. Fig. 8 demonstrates the Dead Nodes for 100݉ × 100݉ Network with 100 nodes with 5000 rounds. Fig. 9 depicts the Alive Nodes for 100݉ × 100݉ Network with 100 nodes with 5000 rounds. Fig. 10 shows the Packet to BS Nodes for 100݉ × 100݉ Network with 100 nodes with 3000 round. Fig. 11 depicts the Count of Cluster Head per round for 100݉ × 100݉ Network with 100 nodes with 5000 round.

Fig. 7 Advance Network Coupling Model with 5000 rounds

Fig. 9 Alive Nodes for 100݉ × 100݉ Network with 100 nodes with 5000 rounds

Fig. 10 Packet to BS Nodes for 100݉ × 100݉ Network with 100 nodes with 4000 round

Fig. 11 Count of Cluster Head per round for 100݉ × 100݉ Network with 100 nodes with 5000 round

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International Journal of Research in Advent Technology, Vol.2, No.6, June 2014 E-ISSN: 2321-9637 4. CONCLUSION This paper is concerned with Energy Efficient Intelligent Sensor Network Routing Protocol.

Here, we evaluate the performance of clustering algorithms on the basis of stability period, network life time and throughput for WSNs. We enhance the above mentioned parameters. Information from sensor nodes is forwarded to cluster heads (CHs) and these CHs are responsible to transmit this information to base station (BS) which is placed far away from the field. This observation depicts that in EESAA (Energy Efficient Sleep Awake Aware) energy dissipation is properly distributed among all the nodes in the network which in result increases network lifetime.

EESAA efficient CHs selection algorithm helps it in better and constant data rate transmission to BS. Although EESAA has sleep-awake policy for nodes and less number of data is transmitted to BS. Other main reason of higher data rate achievement is longer network life time of EESAA. Main focus was to enhance cluster-head selection process. In EESAA, CHs ale selected on the basis of remaining energy. In EESAA nodes also switches between sleep and active modes in order to minimize energy consumption. In our proposed strategy, stability period of network and life time has been optimized. Simulation results shows that the number of alive nodes varies as network evolves and first node dies around 1800 round. Result also shows that in EESAA instable region starts very later as compare to other protocols. Results show that in EESAA nodes die at a constant rate.

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[4] L. Pomante: Wireless Sensor Networks, Seminar in Wireless Communications -University of L’Aquila, March 2007.

[5] Shah, T. ; Javaid, N. ; Qureshi, T.N., "Energy Efficient Sleep Awake Aware (EESAA)intelligent Sensor Network routing prot ocol”International Multitopic Conference (INMIC), , Page(s): 317 – 322, 2012.

[6] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficient routing protocols for wireless micro sensor networks,” in Proc.

33rdHawaii Int. Conf. System Sciences(HICSS), Maui, HI,Jan. 2000.

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