Energy efficient software defined networking algorithm for wireless sensor networks

Mohsin Masood, Mohamed Mostafa Fouad, Saleh Seyedzadeh, Ivan Glesk

Research output: Contribution to journalConference Contribution

Abstract

The real-time properties and operational constraints of Wireless Sensor Networks (WSNs) have emerged the need for designing energy efficient routing protocols. Recently, software defined network based WSN (SDN-WSN) emerging technology has offered a significant development by untying control logic plane from the low power sensor nodes. This centralized programmable control still suffers from several configuration challenges in distributed sensors environment. Meta-heuristic based SDN approaches had been proposed for the efficient path selection in WSN but they still suffer from both, exploration and exploitation problems. Therefore, this paper addresses these shortcomings by proposing a meta-heuristic based dolphin echolocation algorithm (DEA) for optimizing route selection in WSNs. Objective function of the DEA algorithm is to consider the residual energy of the nodes for selecting energy efficient routes. The proposed algorithm performance is compared with several meta-heuristic algorithms in terms of energy-consumption, and network throughput parameters.

Fingerprint

networking
Wireless sensor networks
energy
heuristics
Heuristic algorithms
Routing protocols
Sensor nodes
Energy utilization
Throughput
energy consumption
software
Software defined networking
exploitation
Sensors
performance

Keywords

  • software defined networks
  • energy efficient routing
  • wireless sensor networks
  • optimization techniques
  • adaptive dolphin echolocation algorithm

Cite this

@article{f20cad8b8f594e16b3bacc8139ce7baf,
title = "Energy efficient software defined networking algorithm for wireless sensor networks",
abstract = "The real-time properties and operational constraints of Wireless Sensor Networks (WSNs) have emerged the need for designing energy efficient routing protocols. Recently, software defined network based WSN (SDN-WSN) emerging technology has offered a significant development by untying control logic plane from the low power sensor nodes. This centralized programmable control still suffers from several configuration challenges in distributed sensors environment. Meta-heuristic based SDN approaches had been proposed for the efficient path selection in WSN but they still suffer from both, exploration and exploitation problems. Therefore, this paper addresses these shortcomings by proposing a meta-heuristic based dolphin echolocation algorithm (DEA) for optimizing route selection in WSNs. Objective function of the DEA algorithm is to consider the residual energy of the nodes for selecting energy efficient routes. The proposed algorithm performance is compared with several meta-heuristic algorithms in terms of energy-consumption, and network throughput parameters.",
keywords = "software defined networks, energy efficient routing, wireless sensor networks, optimization techniques, adaptive dolphin echolocation algorithm",
author = "Mohsin Masood and Fouad, {Mohamed Mostafa} and Saleh Seyedzadeh and Ivan Glesk",
year = "2019",
month = "7",
day = "30",
doi = "10.1016/j.trpro.2019.07.205",
language = "English",
volume = "40",
pages = "1481--1488",
journal = "Transportation Research Procedia",
issn = "2352-1465",

}

Energy efficient software defined networking algorithm for wireless sensor networks. / Masood, Mohsin; Fouad, Mohamed Mostafa; Seyedzadeh, Saleh; Glesk, Ivan.

In: Transportation Research Procedia, Vol. 40, 30.07.2019, p. 1481-1488.

Research output: Contribution to journalConference Contribution

TY - JOUR

T1 - Energy efficient software defined networking algorithm for wireless sensor networks

AU - Masood, Mohsin

AU - Fouad, Mohamed Mostafa

AU - Seyedzadeh, Saleh

AU - Glesk, Ivan

PY - 2019/7/30

Y1 - 2019/7/30

N2 - The real-time properties and operational constraints of Wireless Sensor Networks (WSNs) have emerged the need for designing energy efficient routing protocols. Recently, software defined network based WSN (SDN-WSN) emerging technology has offered a significant development by untying control logic plane from the low power sensor nodes. This centralized programmable control still suffers from several configuration challenges in distributed sensors environment. Meta-heuristic based SDN approaches had been proposed for the efficient path selection in WSN but they still suffer from both, exploration and exploitation problems. Therefore, this paper addresses these shortcomings by proposing a meta-heuristic based dolphin echolocation algorithm (DEA) for optimizing route selection in WSNs. Objective function of the DEA algorithm is to consider the residual energy of the nodes for selecting energy efficient routes. The proposed algorithm performance is compared with several meta-heuristic algorithms in terms of energy-consumption, and network throughput parameters.

AB - The real-time properties and operational constraints of Wireless Sensor Networks (WSNs) have emerged the need for designing energy efficient routing protocols. Recently, software defined network based WSN (SDN-WSN) emerging technology has offered a significant development by untying control logic plane from the low power sensor nodes. This centralized programmable control still suffers from several configuration challenges in distributed sensors environment. Meta-heuristic based SDN approaches had been proposed for the efficient path selection in WSN but they still suffer from both, exploration and exploitation problems. Therefore, this paper addresses these shortcomings by proposing a meta-heuristic based dolphin echolocation algorithm (DEA) for optimizing route selection in WSNs. Objective function of the DEA algorithm is to consider the residual energy of the nodes for selecting energy efficient routes. The proposed algorithm performance is compared with several meta-heuristic algorithms in terms of energy-consumption, and network throughput parameters.

KW - software defined networks

KW - energy efficient routing

KW - wireless sensor networks

KW - optimization techniques

KW - adaptive dolphin echolocation algorithm

U2 - 10.1016/j.trpro.2019.07.205

DO - 10.1016/j.trpro.2019.07.205

M3 - Conference Contribution

VL - 40

SP - 1481

EP - 1488

JO - Transportation Research Procedia

T2 - Transportation Research Procedia

JF - Transportation Research Procedia

SN - 2352-1465

ER -