Energy-Efficient Unequal Chain Length Clustering for Wireless Sensor Networks in Smart Cities

Joint Authors

Baniata, Mohammad
Hong, Jiman

Source

Wireless Communications and Mobile Computing

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-09-07

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Information Technology and Computer Science

Abstract EN

The recent advances in sensing and communication technologies such as wireless sensor networks (WSN) have enabled low-priced distributed monitoring systems that are the foundation of smart cities.

These advances are also helping to monitor smart cities and making our living environments workable.

However, sensor nodes are constrained in energy supply if they have no constant power supply.

Moreover, communication links can be easily failed because of unequal node energy depletion.

The energy constraints and link failures affect the performance and quality of the sensor network.

Therefore, designing a routing protocol that minimizes energy consumption and maximizes the network lifetime should be considered in the design of the routing protocol for WSN.

In this paper, we propose an Energy-Efficient Unequal Chain Length Clustering (EEUCLC) protocol which has a suboptimal multihop routing algorithm to reduce the burden on the cluster head and a probability-based cluster head selection algorithm to prolong the network lifetime.

Simulation results show that the EEUCLC mechanism enhanced the energy balance and prolonged the network lifetime compared to other related protocols.

American Psychological Association (APA)

Baniata, Mohammad& Hong, Jiman. 2017. Energy-Efficient Unequal Chain Length Clustering for Wireless Sensor Networks in Smart Cities. Wireless Communications and Mobile Computing،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1206001

Modern Language Association (MLA)

Baniata, Mohammad& Hong, Jiman. Energy-Efficient Unequal Chain Length Clustering for Wireless Sensor Networks in Smart Cities. Wireless Communications and Mobile Computing No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1206001

American Medical Association (AMA)

Baniata, Mohammad& Hong, Jiman. Energy-Efficient Unequal Chain Length Clustering for Wireless Sensor Networks in Smart Cities. Wireless Communications and Mobile Computing. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1206001

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1206001