A guaranteed data transmission system for wireless ad hoc networks

Gopi, R.; Jayanthi, J.; Pandiyan, Sanjeevi

doi:10.1002/ett.4005

Cited by 4 publications

(1 citation statement)

References 33 publications

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“…We note that the finite-density models, which are extensively discussed in this paper, can provide better guidelines on the OLA protocol design and operation in practice. The OLA techniques presented in this paper can be exploited in wireless sensor networks, IoT, communications and signal processing [49][50][51][52][53][54][55], which are representative topics covered in Sensors. Furthermore, the OLA protocols can be employed in small sensors to improve their energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

Opportunistic Large Array Propagation Models: A Comprehensive Survey

Nawaz

Kumar

Hassan

et al. 2021

Sensors

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Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

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Section: Introductionmentioning

confidence: 99%

Opportunistic Large Array Propagation Models: A Comprehensive Survey

Nawaz

Kumar

Hassan

et al. 2021

Sensors

View full text Add to dashboard Cite

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Exploring the Effects of Work Place Learning in the Robotised Millennium

Hemamalini¹,

Ramachandran²,

Kurinjimalar³

2022

cllrm

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In recent years, technology has required workplace learning, continuous professional development, and general training of employees. However, little research has been done in this area to evaluate the methods and effectiveness of these teaching styles and is welcomed by learners. Learning collection designers often use identical policy collections, targeting students or testifying to the success of younger learning students. The word used to describe the education of a very mature learner (mostly in the workplace) of androgyny (according to the knowledge of androgyny knowledge) should have a variety of experiences, while students have only a limited amount so should be basic. The concept of opportunities for learning is borrowed from classroom discourses and expands its understanding of "socially identifiable and identifiable event", including cultural and environmental aspects such as content, time and participant. In this study, teachers are used to examine the sequence of opportunities available to them as they rebuild their roles as learners through relationships with their immediate social and physical contexts. Development, environment and conditions required for workplace learning many ideas aimed at clarifying the factors The following discussion introduces. The workplace learning model is presented in fostering the need for focus change. Outlined in this paper the proposed model of workplace learning on various ideas put forward by accredited academics and incorporates elements relevant to most workplaces.

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Exploring the recent trends in Big Data Analysis

Suresh¹,

Ramachandran²,

Sivaji³

2022

Data Analytics and Artificial Intelligence

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Big Data is a collection of technologies developed to store, analyze and manage this data. It is a macro tool. Today it is used in fields as diverse as medicine, agriculture, gambling and environmental protection. Machine learning, forecasting Companies use big data to streamline their marketing campaigns and techniques. Modeling and other advanced analytics applications enable big data organizations to generate valuable insights. Companies use it in machine learning. Programs cannot balance large data in any particular database. When datasets are large in size, velocity, and volume, the following three distinct dimensions constitute "big data." Examples of big data analytics include stock markets, social media platforms, and jet engines. But it is growing exponentially with time. Traditional data management tools cannot store or process it efficiently. It is a large scale technology developed by Story, Analysis and Manoj, Macro-Tool. Find patterns of exploding confusion in information about smart design, however, implying that various big data structures are structured, whether this includes the amount of information, the speed with which it is generated and collected, or the variety or scope of related data points. In the past, data was collected only from spreadsheets and databases of large, disparate information that grew at an ever-increasing rate. Very large, complex data refers to large amounts of data for sets that are impossible to analyze with traditional data processing applications. Is software configuration used to handle the problem? Apache is an advanced application for storing and processing large, complex data sets and analyzing big data. Analytical techniques against very large, heterogeneous databases containing varying amounts of data, big data analytics help businesses gain insights from today's massive data sources. Defined as software tools for processing and extraction. People, companies and more and more machines are now developing technologies to analyze more complex and large databases that cannot be handled by traditional management tools. It is designed to discover patterns of chaos that explode in information in order to design smart solutions.

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A guaranteed data transmission system for wireless ad hoc networks

Cited by 4 publications

References 33 publications

Opportunistic Large Array Propagation Models: A Comprehensive Survey

Opportunistic Large Array Propagation Models: A Comprehensive Survey

Exploring the Effects of Work Place Learning in the Robotised Millennium

Exploring the recent trends in Big Data Analysis

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