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ToolsHameed, Ahmad Raza, Islam, Saif ul, Raza, Mohsin and Khattak, Hasan Ali (2020) Towards energy and performance aware geographic routing for IoT enabled sensor networks. Computers and Electrical Engineering, 85. ISSN 0045-7906
Full text not available from this repository. (Request a copy)Abstract
The Internet of Things (IoT) has been a pivotal technology enabler for realizing smart cities' vision through the provision of connectivity for everyday objects by means of wireless sensor networks (WSNs). Scalability, flexibility, route efficiency, mobility support and reduced overhead in routing protocols are desired characteristics in large-scale WSNs. Given the several geographic routing schemes proposed, mainly focusing on positioning, location error, and energy consumption, still exhibit higher routing overhead and unbalanced energy consumption of sensor nodes which significantly affect the performance and lifetime of the network. In this paper, an energy-efficient geographic (EEG) routing protocol has been proposed that focuses on network throughput and energy consumption of sensor nodes. The proposed protocol applies mean square error algorithm to resolve the sensor localization problem. Moreover, routing overhead has been reduced by restricting the nodes to maintain single neighbor information. The proposed protocol reduces the energy holes in the network by efficiently balancing the energy consumption among sensor nodes. The extensive simulations illustrate that the proposed scheme manages energy consumption and packet delivery ratio (PDR) more efficiently in comparison to a state-of-the-art geographic routing protocol.
| Item Type: | Article |
|---|---|
| Additional Information: | Publisher Copyright: © 2020 Elsevier Ltd |
| Uncontrolled Keywords: | energy holes,geographic routing,internet of things,load balancing,location error,void regions,wireless sensor networks,control and systems engineering,computer science(all),electrical and electronic engineering,sdg 11 - sustainable cities and communities ,/dk/atira/pure/subjectarea/asjc/2200/2207 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 16 Jun 2025 10:30 |
| Last Modified: | 27 Jun 2025 00:54 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/99515 |
| DOI: | 10.1016/j.compeleceng.2020.106643 |
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