Abstract
In this paper, three energy efficient routing strategies for a design of a Particle Swarm Optimization based Wireless Sensor Network (WSN) routing algorithm are presented. The first strategy maximizes the energy of the node with the lowest energy (the worst performing node) in the WSN, the second strategy maximizes the overall WSN energy and the third strategy maximizes the energy of the worst performing node while improving network latency. The best of these strategies is further tested in a WSN with energy harvesting nodes. The results are compared with a benchmark variant of the Low energy adaptive clustering hierarchy (LEACH) protocol, called the LEACH-Centralized Sleeping (CS). The results show that the strategy that maximizes the overall network energy can improve the network lifetime better. The results further show that the energy harvesting aware routing protocol can extend the lifetime of a WSN more than a protocol that is not energy harvesting aware.
| Original language | English |
|---|---|
| Title of host publication | 2019 Conference on Information Communications Technology and Society, ICTAS 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781538673652 |
| DOIs | |
| Publication status | Published - 30 Apr 2019 |
| Externally published | Yes |
| Event | 3rd Conference on Information Communications Technology and Society, ICTAS 2019 - Durban, South Africa Duration: 6 Mar 2019 → 8 Mar 2019 |
Publication series
| Name | 2019 Conference on Information Communications Technology and Society, ICTAS 2019 |
|---|
Conference
| Conference | 3rd Conference on Information Communications Technology and Society, ICTAS 2019 |
|---|---|
| Country/Territory | South Africa |
| City | Durban |
| Period | 6/03/19 → 8/03/19 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Energy harvesting
- LEACH-CS
- PSO
- Two-tier Clustering
- Wireless Sensor Networks
ASJC Scopus subject areas
- Computer Science Applications
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Information Systems and Management
- Education
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