Title: The fuzzy-IAVOA energy-aware routing algorithm for SDN-based IoT networks

Authors: Amin Nazari; Reza Mohammadi; Nadia Niknami; Seyedeh Shabnam Jazaeri; Jie Wu

Addresses: Bu-Ali Sina University, Hamadan, Iran ' Bu-Ali Sina University, Hamadan, Iran ' Center for Networked Computing, Temple University, USA ' Islamic Azad University, North Tehran Branch, Tehran, Iran ' Center for Networked Computing, Temple University, USA

Abstract: The internet of things (IoT) has rapidly grown in the past decade. Due to the heterogeneity and energy limitations of IoT devices, adopting efficient management practices for developing IoT applications is a challenging task. Software defined networking (SDN) is a novel approach that decouples the control plane from the data plane, enabling network administrators to manage their networks more efficiently. This paper proposes an energy-aware routing mechanism by leveraging the capabilities of SDN. Firstly, the SDN controller establishes several optimal clusters using fuzzy logic and the improved African vulture optimisation algorithm (IAVOA). Then, the controller computes optimal routes by combining the fuzzy logic system. Applying this mechanism enables data packets to be routed through IoT devices with sufficient energy, leading to prolonged network lifetime and improved quality of service (QoS). Simulation results confirm that the proposed solution significantly improves energy efficiency and QoS in terms of packet delivery ratio.

Keywords: African vultures optimisation algorithm; AVOA; energy-aware routing; internet of things; IoT; quality of service; QoS; routing; software-defined networks.

DOI: 10.1504/IJSNET.2023.132543

International Journal of Sensor Networks, 2023 Vol.42 No.3, pp.156 - 169

Received: 19 Apr 2023
Accepted: 21 Apr 2023
Published online: 27 Jul 2023 *

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