Integrated Model of Bandwidth Optimization and Energy Efficiency in Internet-of-Things

Author(s):  
Bhagyashree Ambore ◽  
L. Suresh
Technologies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 22
Author(s):  
Eljona Zanaj ◽  
Giuseppe Caso ◽  
Luca De Nardis ◽  
Alireza Mohammadpour ◽  
Özgü Alay ◽  
...  

In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers in the deployment of networks of interconnected devices. As network and spatial device densities grow, energy efficiency and consumption are becoming an important aspect in analyzing the performance and suitability of different technologies. In this framework, this survey presents an extensive review of IoT technologies, including both Low-Power Short-Area Networks (LPSANs) and Low-Power Wide-Area Networks (LPWANs), from the perspective of energy efficiency and power consumption. Existing consumption models and energy efficiency mechanisms are categorized, analyzed and discussed, in order to highlight the main trends proposed in literature and standards toward achieving energy-efficient IoT networks. Current limitations and open challenges are also discussed, aiming at highlighting new possible research directions.


2018 ◽  
Vol 5 (4) ◽  
pp. 2605-2619 ◽  
Author(s):  
Jie Tang ◽  
Daniel K. C. So ◽  
Nan Zhao ◽  
Arman Shojaeifard ◽  
Kai-Kit Wong

2021 ◽  
pp. 026666692110641
Author(s):  
Najmul Hasan ◽  
Yukun Bao ◽  
Shah Jahan Miah ◽  
Alex Fenton

The Internet of Things (IoT) enabled technologies to have proliferated due to their abilities to capture and exchange quality information. This empirical study aims to investigate the factors influencing the intention to use IoT services in healthcare by young physicians. An integrated model based on the theory of planned behaviour (TPB) and diffusion of innovations (DOI) theories are drawn upon and analyzed through a Structural Equation Modelling (SEM) with importance-performance map analysis (IPMA). Data were collected through a structured survey questionnaire. The results indicated that behavioural intention to use IoT in healthcare services vastly affected by the attitude and value co-creation. Attitude was found to be a principal determinant followed by the relative advantage towards behavioural intention to use IoT services. The novelty of this empirical study is that the proposed integrated model provides a meaningful application of the young physicians’ intention to use IoT in healthcare in developing countries.


Author(s):  
Christos J Bouras ◽  
Apostolos Gkamas ◽  
Spyridon Aniceto Katsampiris Salgado ◽  
Nikolaos Papachristos

This chapter presents the design and development of a search and rescue (SAR) system, for the location and provision of aid to people who are missing or in imminent danger, especially those belonging to population groups with a particularly high probability of getting lost. With the use of low-power wide area network (LPWAN) technology, such as narrow band internet of things (NB-IoΤ), the authors are able to provide search and rescue solutions for individuals, especially those belonging to groups of people who are more likely to get lost. The central part of the system is a modular “wearable (portable)” device, while in the framework of the implementation of this system, the authors have seriously taken into consideration the aspects of energy efficiency in order to provide better battery life.


2016 ◽  
Vol 54 (11) ◽  
pp. 3414-3428 ◽  
Author(s):  
Wen Su ◽  
Xiaolei Xie ◽  
Jingshan Li ◽  
Li Zheng

Author(s):  
Praveen Kumar Reddy Maddikunta ◽  
Rajasekhara Babu Madda

Energy efficiency is a major concern in Internet of Things (IoT) networks as the IoT devices are battery operated devices. One of the traditional approaches to improve the energy efficiency is through clustering. The authors propose a hybrid method of Gravitational Search Algorithm (GSA) and Artificial Bee Colony (ABC) algorithm to accomplish the efficient cluster head selection. The performance of the hybrid algorithm is evaluated using energy, delay, load, distance, and temperature of the IoT devices. Performance of the proposed method is analyzed by comparing with the conventional methods like Artificial Bee Colony (ABC), Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and GSO algorithms. The performance of the hybrid algorithm is evaluated using of number of alive nodes, convergence estimation, normalized energy, load and temperature. The proposed algorithm exhibits high energy efficiency that improves the life time of IoT nodes. Analysis of the authors' implementation reveals the superior performance of the proposed method.


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