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ACCENT JOURNAL OF ECONOMICS ECOLOGY & ENGINEERING

Peer Reviewed and Refereed Journal, ISSN NO. 2456-1037

Available Online: www.ajeee.co.in/index.php/AJEEE

Vol. 06, Issue 04, April 2021 IMPACT FACTOR: 7.98 (INTERNATIONAL JOURNAL) 25 A REVIEW ON ENERGY CONSUMPTION ANALYSIS IN WIRELESS SENSOR NETWORKS

Pragati Jain, (M.Tech Scholar)

Guide - Rajendra Arakh, (Assistant Professor) Deptt. - Computer Science Engineering

Global Engineering College, Jabalpur

Abstract - Wireless Sensor Network (WSN) has played a contributory role in modern wireless and communication system. With a wide range of applications exercised in environmental monitoring, process management, industrial monitoring, healthcare monitoring, WSN is one of the most attentive topic in research area. Along with various advantages associated with sensor, there are potential flaws in this topic. A sensor node is characterized by limited memory, limited energy, restricted computational capability. There are series of issues that are still left unsolved viz. routing, bandwidth, security, energy, quality of service and many more. A sensor operates on a principle of radio energy principle, which means that there is a closer relationship between energy dissipation and communication performance. With wide range of availability of routing protocols, only few hierarchical routing protocols are found to provide energy efficiency in wireless sensor network. An optimal routing performance will easily require higher power requirement during routing that significantly reduce the network lifetime of the wireless sensor network.

However, the closer investigation shows that energy is the root cause for all form of performance degradation.

Keywords: WSN, LEACH, DTN.

1 INTRODUCTION

There are places on earth where it is never possible for human to move and collect information therefore WSN is one such technology that assists to bridge this gap. Usually, a WSN is also termed as a set of specific sensors that are distributed widely over the area that requires remote surveillance [1, 2]. In order to understand the domain of WSN, it is essential to first understand fundamentals of a sensor node. It is a type of device, powered from electrical and electronic characteristics, that is responsible for sensing some of significant physical attributes such as smoke, moisture, thermal, pressure, motion, temperature, humidity etc. [3].

Sensor nodes are scattered on the area where the information is required to be gathered. Hence, normally, such sensor nodes are dropped from the aeroplane [4].

This form of distribution of sensor nodes on the monitoring area is called as random distribution, where the position of sensors is quite unknown or unpredictable for the user before deployment [5]. Random deployment of sensors is preferable only for a large geographical area, where it is not possible for human to go and plant sensors. A uniform distribution of sensors is just the opposite of random deployment, where the sensorlocation is well known to the

user. It is generally used in small area for surveillance. Referring to Figure 1, it can be seen that a sensor node is designed using various forms of internal components examples transceiver, microcontroller, external memory, Analogue-to-Digital Converter (ADC), and power source [6].

Figure 1 Hardware Components of Sensor Nodes

Various types of sensors are as follows:

• Pressure Sensor: These sensors are used for capturing data related to pressure for example vacuum, fiber optics etc.

• Temperature Sensor: These types of sensors are used for capturing thermal data e.g. temperature data of thermocouples, integrated circuits, thermistors etc.

• Level Sensor: It is used to capture

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ACCENT JOURNAL OF ECONOMICS ECOLOGY & ENGINEERING

Vol. 06, Issue 04, April 2021 IMPACT FACTOR: 7.98 (INTERNATIONAL JOURNAL) 26 the differential data when the

horizontal or vertical levels are subjected to any change.

• Proximity Sensor: It is a form of motion sensors which capture data related to any object coming closer to them.

• Biosensor: Such sensors are connected to body of living organism to capture vital stats.

• Miscellaneous Sensor: speed sensor, smoke sensor, humidity sensor etc.

1.1 Applications of WSN

The applications of the WSN are as follows:

• Environmental Monitoring:

Sensors can be used in the surrounding to capture the forest fire, data of rainfall, precipitation, pollution, landslide, natural calamities, level of pollution etc.

• Process Management: Various forms of process in factories or industries for example chemical plant, nuclear plant, roadways, airport etc. can be evaluated using sensor nodes.

• Industrial Monitoring: Sensors are also used for capturing the information about data logging, structural health monitoring, evaluating the health of complex machineries system.

• Healthcare Monitoring: Sensor nodes can also be used to capture vital statistics as well as certain clinical information to understand specific medical condition of a patient.

1.2 Essential Characteristics of WSN Some of essential characteristics of WSN are as follows:

• A sensor node is characterized by

less memory, minimal

computational capability

• The deployment of sensors happens only once and nodes are usually stationary. Few nodes have mobility but it is not consistent.

• The nature of WSN is quite centric to data which means that any queries to the sensor network will be processed by sensors without any feasibility of unique addressing as nodes lack global identifier.

• The deployment of sensor nodes are usually carried out by single owner as they are normally application specific.

• The rate of data transfer is quite minimal in WSN and is quite statistical in nature.

• In conventional theory, the quantities of sensor nodes are considered to be quite large and should have the capability of scaling up to higher degree of network.

1.3 Design Issues in WSN

The communication performance of sensor network solely depends on the quality of the wireless transmission mode.

Design issues in WSN are as follows:

• WSN has less supportability for multichip networking which results in minimization of transmission link range.

• Battery of sensor consistently dissipates energy thereby lowering the network lifetime and degrading the higher duty cycle operation.

• There is a less availability of routing protocol that supports energy efficiency and efficient data transmission during peak traffic condition.

• Inefficient clustering mechanism will lead to selection of imprecise cluster head leading to unnecessary energy depletion.

2 ENERGY PROBLEMS IN WSN

A WSN is a collection of various sensors that are small and inexpensive inter- connected in an Ad-hoc manner [7].

Sensors are electronic devices that can sense the physical attributes example motion, pressure, temperature, smoke, humidity, etc. Very often, such devices are represented as nodes.

Figure 2 Typical WSN Architecture

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ACCENT JOURNAL OF ECONOMICS ECOLOGY & ENGINEERING

Vol. 06, Issue 04, April 2021 IMPACT FACTOR: 7.98 (INTERNATIONAL JOURNAL) 27 Architecture of a sensor node includes

three basic components which are used for sensing various environmental attributes with respect to a process of sampling signals. Processing subsystem for aggregated data and storage components as well as a wireless communication unit for transmitting and receiving signals [9]. Each and every sensor node consists of a battery source with a limited power capacity. As sensor nodes are deployed over a hostile region, it will not be possible to recharge the batteries if batteries get exhausted [10].

Prolonging the life time of a sensor network has become more challenging now a day’s [11]. Figure 2 shows a typical WSN architecture which includes geographically distributed different sets of sensor nodes. Where each and every sensor node has the capability of running various Application Programming Interfaces (API) with the help of one operating system [12].Existing research trends highlight that sensor nodes placed in a particular deployment area form a cluster. The cluster head in a cluster which consists of more powerful and computationally efficient resources. Every cluster head maintains and collects aggregated data from its respective sensor nodes where a data acquisition process is performed for sampling of a received signal and resulting Analog sample values are converted into digital numeric values for the ease of computation and pre- processing. Sensor nodes sense various kinds of environmental attributes using its sensing unit and transmit the information to its corresponding cluster head [. The entire cluster heads gather the collected information and retransmit it to a sink node which is also an electronic device used for processing of huge amount of collected data and sending it to the monitor station via a gateway node. All sensor nodes use an Analog to digital converter for converting conditioned sensor signals to digital values.Energy consumption issues impose a great deal of challenges in the field of WSN as sensor nodes are deployed over a hostile region and there is no external wired source that can recharge sensor node batteries [17]. Scarcity of efficient power consumption has to be managed wisely in order to extend battery as well as network lifetime [18]. As the WSN

network architecture has been designed to be implemented in various military applications which consume more power for data communication between cluster heads which have verylimited power capacity.

It can be seen that there are two other factors which affect badly, quality of services for large networks and wireless link qualities respectively. A huge distance between two sensor nodes and a poor link quality between nodes increase the data transmission power consumption within a particular WSN. Link quality depends on different factors such as several physical barriers and climatic conditions. In order to maintain the link capacity for efficient data packet transmission several factors such as link quality and transmission power can be adjusted for data delivery success. Earlier literature highlights that while designing a sensor node the computation energy and data transmission power has to be considered, as transceiver plays a very significant role in the conservation of overall power.

Transceiver consumes battery power by different type of stages such as

• Signal Transmission

• Signal Receiving

• Idle/Inactive mode

• Sleeping Mode/ (Off)

The above mentioned different types of stages of transceiver dissipate different amount of power during data transmission [22]. Many of the existing work show that transmission consumes more energy than data acquisition of a particular node. The configuration of a transceiver can be developed in a way that the enable and disable mode of these four different stages can be adjusted as per requirements of routing because in most cases it happens like a transceiver is in an idle mode which means it is not sending or receiving signal and puts itself in a power saving mode. Figure 1.3 highlights an overview of power management and energy harvesting of sensor node architecture.

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Vol. 06, Issue 04, April 2021 IMPACT FACTOR: 7.98 (INTERNATIONAL JOURNAL) 28 Figure 3 Power Management of a

Sensor Node 3 CONCLUSION

Sensors being a very smaller and delicate electronic miniature device are highly restricted with lower memory ranges with minimal computational capabilities.

Accompanied by limited capabilities, these sensors carry out the cycle of data dissemination process. However, methods of data dissemination process till date are discussed with respect to routing protocols or critical operations of the data aggregation techniques with minimal consumption of energy. In the existing system, there are also various researchers who have also addressed the issues of energy consumption during the data dissemination process.

REFERENCES

1. Mohammad Abo-Zahhad et all, “An energy consumption model for wireless sensor networks”, IEEE international conference,

March 2015.

2. F. Ke, S. Feng, and H. Zhuang, “Relay selection and power allocation for cooperative network based on energy pricing,” IEEE Communications Letters, vol. 14, no. 5, pp.

396–398, 2010.

3. J. Abouei, K. N. Plataniotis, and S.

Pasupathy, “Green modulations in energy- constrained wireless sensor networks,” IET Communications, vol. 5, no. 2, pp. 240–251, 2011.

4. T. Zhao, T.-D. Guo, and W.-G. Yang, “Energy balancing routing model and its algorithm in wireless sensor networks,” Journal of Software, vol. 20, no. 11, pp. 3023–3033, 2009.

5. P.-F. Xu, Z.-G. Chen, and X.-H. Deng, “Power control algorithm for wireless sensor networks based on approximate Unit Delaunay triangulation,” Journal on Communication, vol. 34, no. 2, pp. 170–176, 2013.3

6. A. Karimi, S. M. Amini, “Reduction of energy consumption in WSN based on predictable routes for multi mobile sink”, The journal of supercomputing, issue: 11/2019.

7. Y. Bao et. all, IEEE international conference on communications, 2014, 3487-3492.

8. Najam ul Hasan. cooperative Spectrum sensing in cognitive radio networks, 2006- nust-ms PhD-ComE.

9. L. Giupponi, Ana I. Pérez-Neira. Fuzzy-based Spectrum Handoff in Cognitive radio network, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Universitat Politècnica de Catalunya (UPC).

10. Dong Li, Xianhua Dai, Han Zhang. Joint Adaptive Modulation and Power Control in Cognitive Radio Networks, School of Information and Scienc Technology, Sun Yat- Sen University Guangzhou 510275, P. R.

China.

11. Nouha Baccour, Anis Koubâa, Habib Youssef, Maissa Ben Jamaa1, Denis do Rosário, Mário Alves, and Leandro B.

Becker. F-LQE: A Fuzzy Link Quality Estimator for Wireless Sensor Networks.