Wireless Sensor Network Softwarization: Towards WSN Adaptive QoS

Ezdiani, Syarifah; Acharyya, Indrajit S.; Sivakumar, S.; Al-Anbuky, Adnan

doi:10.1109/jiot.2017.2740423

Cited by 37 publications

(13 citation statements)

References 24 publications

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“…In view of these factors, WSN designers ought to consider factors such as fault tolerance, operating environment, scalability, network topology, and energy efficiency. Recent studies such as [14], [28], and [40], consider OPNET, MATLAB, NS-2, and TOSSIM based simulations as well as real system implementations (testbeds) for the evaluation of new algorithms to improve the battery lifetime and QoS values under variable traffic load conditions.…”

Section: Quality Of Service For Iot Applicationsmentioning

confidence: 99%

“…In this section, modelling, and simulation works on WSNs' pure performance, availability/reliability and energy efficiency. Benchmarking studies similar to [14] come with important limitations such as the cost of the infrastructure, scale of the system to be considered as well as the difficulties usually encountered to extrapolate the results obtained for a specific scenario [6]. Therefore, simulation and analytical modelling studies are quite commonly utilised for studying WSNs.…”

Section: Related Workmentioning

confidence: 99%

“…The following table summarises the studies considered on evaluation of IoT and WSN based infrastructures and shows the contribution of our approach. [11], [14], [27]…”

Section: Related Workmentioning

confidence: 99%

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On the performance, availability and energy consumption modelling of clustered IoT systems

et al. 2019

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Section: Quality Of Service For Iot Applicationsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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On the performance, availability and energy consumption modelling of clustered IoT systems

et al. 2019

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“…Efforts have been made to reduce the delay and improve the efficiency without compromising on the QoS of the network [3]. A close observation and monitoring of the intended environmental changes and the physical phenomenon and continuous reporting of all the changes or incidents of important activities recorded at a remote location over a wireless ad hoc network and executed by a small‐sized group of sensing nodes separated by equal or unequal space over a geographical area are the basic operations of a WSN, and the physical or environmental state is not limited to pressure gauging, sound detection and temperature fluctuations [4]. Many QoS improvements are needed to get a flawless sensing network [5].…”

Section: Introductionmentioning

confidence: 99%

NOSS (novel optimal sleep scheduling) scheme for energy and data reliability optimisation in mobile cloud‐assisted wireless sensor networks

Kumar

Ramaswamy

Basha³

et al. 2019

J. eng.

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“…There are already some studies on energy-efficient QoS for IWSNs [49][50][51], such as energy-efficient QoS awares routing and delays reduction algorithm [52]. However, there are several key issues in these studies that deserve further study.…”

Section: Introductionmentioning

confidence: 99%

Cross-layer design for reducing delay and maximizing lifetime in industrial wireless sensor networks

Tan

Liu

Zhao

et al. 2018

J Wireless Com Network

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Low delay and long lifetime are a very important issue for industrial wireless sensor networks (IWSNs) in which it require long-time monitoring of industrial sites and respond quickly to events that is monitored; therefore, high delay communications can cause serious damage to property and personnel at industrial field. Due to delay, lifetime, and other performance involved to multiple layers, it is difficult to optimize from a single layer. Therefore, a cross-layer design optimal scheme for reducing delay and maximizing lifetime (RDML) scheme is proposed for IWSNs which is from several layers such as transmitted power, duty cycle, and node deployment positions to optimize the network performance of delay and lifetime etc. Firstly, due to the node which sends a packet within a cycle, different duty cycle leads to different selection of the modulation level, resulting in different power consumption efficiency of transmitting data. Through careful analysis, the optimal value of the duty cycle is given which has the lowest energy consumption per bit. In fact, the energy consumption of the node is not balanced. Therefore, an optimization method of changing the duty cycle is proposed. In this paper, larger duty cycle is chosen for nodes with residual energy to improve the reliability of data transmission, reducing the probability of data retransmission, so that the network delay can be reduced in IWSNs. Third, based on the previous analysis, a network optimization deployment algorithm is proposed, which not only maximizes the energy efficiency of a single node but also maximizes the network lifetime and the total network energy efficiency. Both our comprehensive theoretical analysis results indicate that the performance of RDML scheme is better than the previous studies. Relative to equal distance and optimal duty cycle scheme, the RDML scheme can reduce the delay by 19-30% and increase the lifetime by more than 43%.

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Wireless Sensor Network Softwarization: Towards WSN Adaptive QoS

Cited by 37 publications

References 24 publications

On the performance, availability and energy consumption modelling of clustered IoT systems

On the performance, availability and energy consumption modelling of clustered IoT systems

NOSS (novel optimal sleep scheduling) scheme for energy and data reliability optimisation in mobile cloud‐assisted wireless sensor networks

Cross-layer design for reducing delay and maximizing lifetime in industrial wireless sensor networks

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