An Energy-Efficient Framework for Internet of Things Underlaying Heterogeneous Small Cell Networks

Jiang, Hongbo; Xiao, Zhu; Li, Zexian; Xu, Jiankuan; Zeng, Fanzi

doi:10.1109/tmc.2020.3005908

Cited by 181 publications

(42 citation statements)

References 40 publications

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“…It is considered to be one of the promising strategies for the development of green communication. Depending on the traffic loads and quality of service of end users, an elastic CZ algorithm is proposed by the authors in Reference 42 to increase the EE of the IoT underlying heterogeneous small‐cell networks. SWIPT‐CH selection algorithm was further proposed to optimize the average residual energy.…”

Section: Related Workmentioning

confidence: 99%

A new method of hybrid optimization of small cell range development and density for energy efficient ultra‐dense networks

Sidiq

Sheikh

Mustafa

et al. 2022

Trans Emerging Tel Tech

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Ultra-dense networks (UDNs) which comprise of small and macro cells, are considered the principal solution for increasing demands of data. However, making energy efficient networks will be a challenge for researchers. In this article, a hybrid optimization technique is proposed to enhance the energy efficiency (EE) of the UDNs, considering the user correlation and hybrid optimization of the density and transmitting power of the small-cell-base-station (SBS). More precisely, the problem framed is a problem of convex-linear programming and hence is divided into two sub-problems: cell correlation and hybrid optimization. The expression for the EE of the system is derived in the closed-form as a factor of the density of SBSs and small cell-range-development (CRD) bias dependent on the Poisson point process (PPP) followed by the sequential-search-algorithm to improve the small CRD bias and SBS density correspondingly. Additionally, to realize hybrid optimization of the small CRD bias and density of SBSs, a heuristic algorithm is put forward to accomplish the EE of the system. It is revealed from the simulation outcomes that the proposed small CRD bias and SBS density hybrid optimization significantly enhances the EE of the system with low computational intricacy.

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Section: Related Workmentioning

confidence: 99%

A new method of hybrid optimization of small cell range development and density for energy efficient ultra‐dense networks

Sidiq

Sheikh

Mustafa

et al. 2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…The high-sensitivity receiver receives the Xrays that pass through this layer and converts them into visible light, which is converted into electrical signals by photoelectric conversion, and then converted into digital signals by an analog-digital converter. Each number in the digital matrix is converted into small squares from black to white (i.e., pixels) by a digital-to-analog converter and arranged into a matrix to obtain CT images [16,17]. After entering the computer, the selected layer is divided into multiple voxels, and the scanned information is calculated to obtain the X-ray attenuation coefficient or absorption coefficient of each voxel and arranged in a digital matrix.…”

Section: Ct Tomography Technologymentioning

confidence: 99%

Research on Data Optimization of CT System for Patients with Severe Pneumonia Based on Filtered Back Projection and Internet of Things

Qin

Wang

2021

Wireless Communications and Mobile Computing

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CT technology can clearly and intuitively display the internal structure, composition, material, and defect status of the detected object under the condition of no damage to the detected object. This paper is based on the filtering back projection and the Internet of Things technology to carry out the data optimization of the CT system of patients with severe pneumonia. First of all, the Internet of Things technology is used in the structural design and operation process of the CT system for patients with severe pneumonia, which improves the advancement and convenience of the original system. Secondly, the system data is optimized through the filtering back projection algorithm, which improves the data accuracy and transmission efficiency. Finally, simulation tests have verified the effectiveness of the established CT system data optimization method for patients with severe pneumonia, which is helpful for medical comparison, analysis, and diagnosis.

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“…With the help of analyzing the estimated classifier, a variety of effective measures for the detection of improper task are observed, including words that appeared in task information, reward or money which will be received by the workers after performing the task, and their qualification for performing the task [5]. Various research fields can benefit from using the proposed approach such as IoT underlying heterogeneity [28], investigation of data aggregation in mobile sensor networks for IIoT [29], sharing of resource in heterogeneous vehicular network [30], and many other fields.…”

Section: Related Workmentioning

confidence: 99%

MCDM Approach for Assigning Task to the Workers by Selected Features Based on Multiple Criteria in Crowdsourcing

Zhao

Khan

et al. 2021

Scientific Programming

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Crowdsourcing in simple words is the outsourcing of a task to an online market to be performed by a diverse group of crowds in order to utilize human intelligence. Due to online labor markets and performing parallel tasks, the crowdsourcing activity is time- and cost-efficient. During crowdsourcing activity, selecting the proper labeled tasks and assigning them to an appropriate worker are a challenge for everyone. A mechanism has been proposed in the current study for assigning the task to the workers. The proposed mechanism is a multicriteria-based task assignment (MBTA) mechanism for assigning the task to the most suitable worker. This mechanism uses approaches for weighting the criteria and ranking the workers. These MCDM methods are Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Criteria have been made for the workers based on the identified features in the literature. Weight has been assigned to these selected features/criteria with the help of the CRITIC method. The TOPSIS method has been used for the evaluation of workers, with the help of which the ranking of workers is performed in order to get the most suitable worker for the selected tasks to be performed. The proposed work is novel in several ways; for example, the existing methods are mostly based on single criterion or some specific criteria, while this work is based on multiple criteria including all the important features. Furthermore, it is also identified from the literature that none of the authors used MCDM methods for task assignment in crowdsourcing before this research.

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An Energy-Efficient Framework for Internet of Things Underlaying Heterogeneous Small Cell Networks

Cited by 181 publications

References 40 publications

A new method of hybrid optimization of small cell range development and density for energy efficient ultra‐dense networks

A new method of hybrid optimization of small cell range development and density for energy efficient ultra‐dense networks

Research on Data Optimization of CT System for Patients with Severe Pneumonia Based on Filtered Back Projection and Internet of Things

MCDM Approach for Assigning Task to the Workers by Selected Features Based on Multiple Criteria in Crowdsourcing

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