Performance Optimization in IoT-Based Next-Generation Wireless Sensor Networks

Behzad, Muzammil; Abdullah, Manal; Hassan, M. Y. M.; Ge, Yufeng; Khan, Madad

doi:10.1007/978-3-662-59540-4_1

Cited by 4 publications

(5 citation statements)

References 46 publications

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“…Many layers exist in IoT networks established through the interconnection between small devices that can communicate with low bandwidth and high devices that can communicate with high bandwidths. Optimization of performance needs to be done considering the network topology used in each layer and when interconnection between the networks in different layers is established [Behzad, M., Abdullah, M., Hassan et al,] [2].…”

Section: Switch Box: a Switch Box Is A Device That Receives And Trans...mentioning

confidence: 99%

“…to output 5, we will proceed as follows. The input will first arrive at the switch box (3, 1), which will forward it to (3,2), and so on until it reaches the switch box (3,5). This switch box will turn the message into column 5 and forward it to the box (2, 5), which will send it to the box (1,5), which will send it to its destination.…”

Section: Performance Improvement Through the Availability Of Alternat...mentioning

confidence: 99%

“…has been proved that the reliability of the device-based clusters tremendously improves through building networks like crossbar, butterfly, etc. The number of communication paths from any node can be computed using equation(2). Where n = Number of Inputs, if n = 3, then the number of paths available for communication from any node is = 31.…”

mentioning

confidence: 99%

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Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

Sowmya,

Sastry

2022

Scientia Iranica

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Multiple networking layers existing in the IoT network involve heterogeneity that must be addressed to facilitate proper communication such that the performance of an IoT network does not suffer. The performance of the IoT networks depends on networking topologies used in different layers, clustering algorithms, protocols used for handling heterogeneity, communication speeds, and data packet sizes. In this Research, the performance of IoT networks is improved by adding device clustering via a multi-Stage network and using an efficient SOJK clustering algorithm in the device layer, which minimizes power depletion and increases the quantity of data and data packets; transmitted at zero power. A mechanism to handle heterogeneity due to Wi-Fi, CDMA, and USB communication protocols is also presented while optimizing the communication speeds and data transmission size. It has also been shown that the use of 170Mbps cellular speed and the data size of 468 bytes give the optimum response time of an IoT network. The time taken to transport information from the device to the storage layer is reduced by 57% compared to the time taken to transport the data using the prototype network.

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Section: Switch Box: a Switch Box Is A Device That Receives And Trans...mentioning

confidence: 99%

Section: Performance Improvement Through the Availability Of Alternat...mentioning

confidence: 99%

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Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

Sowmya,

Sastry

2022

Scientia Iranica

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“…Hence quality of feature transform based image has more efficient then existing work. In figure 2, proposed approach improve the VSI as compare then Niu's[24], ASJND [1] for different image dataset. For image 1, VSI will reduce by 2.75% as compare then ASJND [1].…”

Section: Figure 1: Graphical Comparison Of Psnr(db) Among Niu's[24] mentioning

confidence: 99%

“…In figure 3, proposed approach improve the Energy Efficiency as compare then Niu's[24], ASJND [1] for different image dataset. For image 1, energy will reduce by 4.31% as compare then ASJND [1]. Hence saliency map factor is reducing through feature transform based image which is more efficient then existing work.…”

Section: Figure 3: Graphical Comparison Of Energy (Percentage) Among mentioning

confidence: 99%

Study of Energy Efficient Images with Just Noticeable Difference Threshold Based on Feature Transform

Soni¹,

Dixit²

2019

IJTSRD

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A novel method is presented for producing energy-efficient images, i.e., images that consume less electrical energy on energy-adaptive displays, yet have the same, or very similar perceptual quality to their original images. The proposed method relies on the fact the energy consumption of pixels in modern energyadaptive displays like OLED displays are directly proportional to the luminance of the pixels. Hence, in this work to reduce the energy consumption of an image while at the same time preserving its perceptual quality, it is proposed to reduce the luminance of the pixels in the image by one just-noticeable-difference (JND) threshold. To determine the JND thresholds, a Feature Transform based just Noticeable Difference Threshold (FTJNDT) model is developed. In the proposed model, the JND thresholds of each block in the given image are elevated by two non-linear saliency modulation functions using the visual saliency of the block. The parameters of the saliency modulation functions and obtain feature value are estimated through an adaptive optimization framework, which utilizes a state-of-the-art saliency-based objective image quality assessment (IQA) method. To evaluate the proposed methods, a set of subjective experiments were conducted, and the real energy consumption of the produced energy-efficient images were measured by accurate power monitor equipment on an OLED display. The obtained experimental results demonstrated that, on average, the proposed method is able to reduce the energy consumption by about 4.31% while preserving the perceptual quality of the displayed images.

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Performance Optimization in IoT-Based Next-Generation Wireless Sensor Networks

Behzad

Abdullah

Hassan

et al. 2019

Lecture Notes in Computer Science

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In this paper, we propose a novel framework for performance optimization in Internet of Things (IoT)-based next-generation wireless sensor networks. In particular, a computationally-convenient system is presented to combat two major research problems in sensor networks. First is the conventionally-tackled resource optimization problem which triggers the drainage of battery at a faster rate within a network. Such drainage promotes inefficient resource usage thereby causing sudden death of the network. The second main bottleneck for such networks is that of data degradation. This is because the nodes in such networks communicate via a wireless channel, where the inevitable presence of noise corrupts the data making it unsuitable for practical applications. Therefore, we present a layer-adaptive method via 3-tier communication mechanism to ensure the efficient use of resources. This is supported with a mathematical coverage model that deals with the formation of coverage holes. We also present a transform-domain based robust algorithm to effectively remove the unwanted components from the data. Our proposed framework offers a handy algorithm that enjoys desirable complexity for real-time applications as shown by the extensive simulation results.

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Performance Optimization in IoT-Based Next-Generation Wireless Sensor Networks

Cited by 4 publications

References 46 publications

Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

Study of Energy Efficient Images with Just Noticeable Difference Threshold Based on Feature Transform

Performance Optimization in IoT-Based Next-Generation Wireless Sensor Networks

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