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  5. Ant Colony Optimization Based Quality of Service Aware Energy Balancing Secure Routing Algorithm for Wireless Sensor Networks

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Article
English
2019

Ant Colony Optimization Based Quality of Service Aware Energy Balancing Secure Routing Algorithm for Wireless Sensor Networks

0 Datasets

0 Files

English
2019
IEEE Transactions on Engineering Management
Vol 68 (1)
DOI: 10.1109/tem.2019.2953889

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Amir Gandomi
Amir Gandomi

University of Techology Sdyney

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Manisha Rathee
Sushil Kumar
Amir Gandomi
+3 more

Abstract

Existing routing protocols for wireless sensor networks (WSNs) focus primarily either on energy efficiency, quality of service (QoS), or security issues. However, a more holistic view of WSNs is needed, as many applications require both QoS and security guarantees along with the requirement of prolonging the lifetime of the network. The limited energy capacity of sensor nodes forces a tradeoff to be made between network lifetime, QoS, and security. To address these issues, an ant colony optimization based QoS aware energy balancing secure routing (QEBSR) algorithm for WSNs is proposed in this article. Improved heuristics for calculating the end-to-end delay of transmission and the trust factor of the nodes on the routing path are proposed. The proposed algorithm is compared with two existing algorithms: distributed energy balanced routing and energy efficient routing with node compromised resistance. Simulation results show that the proposed QEBSR algorithm performed comparatively better than the other two algorithms.

How to cite this publication

Manisha Rathee, Sushil Kumar, Amir Gandomi, Kumar Dilip, Balamurugan Balusamy, Rizwan Patan (2019). Ant Colony Optimization Based Quality of Service Aware Energy Balancing Secure Routing Algorithm for Wireless Sensor Networks. IEEE Transactions on Engineering Management, 68(1), pp. 170-182, DOI: 10.1109/tem.2019.2953889.

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Publication Details

Type

Article

Year

2019

Authors

6

Datasets

0

Total Files

0

Language

English

Journal

IEEE Transactions on Engineering Management

DOI

10.1109/tem.2019.2953889

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