Computational Intelligence Based Heuristic Approach for Maximizing Energy Efficiency in Internet of Things

2017 ◽  
pp. 53-76 ◽  
Author(s):  
Amandeep Verma ◽  
Sakshi Kaushal ◽  
Arun Kumar Sangaiah
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Computational Intelligence ◽  
Heuristic Approach

scholarly journals Energy Efficiency in Short and Wide-Area IoT Technologies—A Survey

Technologies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 22
Author(s):  
Eljona Zanaj ◽  
Giuseppe Caso ◽  
Luca De Nardis ◽  
Alireza Mohammadpour ◽  
Özgü Alay ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Low Power ◽  
Energy Efficient ◽  
Wide Area ◽  
Wide Area Networks ◽  
The Internet ◽  
Extensive Review ◽  
Research Directions ◽  
The Internet Of Things

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.

scholarly journals Energy Efficiency Optimization With SWIPT in MIMO Broadcast Channels for Internet of Things

2018 ◽  
Vol 5 (4) ◽  
pp. 2605-2619 ◽  
Author(s):  
Jie Tang ◽  
Daniel K. C. So ◽  
Nan Zhao ◽  
Arman Shojaeifard ◽  
Kai-Kit Wong
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Broadcast Channels ◽  
Efficiency Optimization ◽  
Mimo Broadcast Channels

Search and Rescue System Based on NB-IoT Wearable Device

2021 ◽  
pp. 195-222
Author(s):  
Christos J Bouras ◽  
Apostolos Gkamas ◽  
Spyridon Aniceto Katsampiris Salgado ◽  
Nikolaos Papachristos
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
High Probability ◽  
Search And Rescue ◽  
Portable Device ◽  
Battery Life ◽  
Area Network ◽  
Wide Area Network ◽  
Rescue System ◽  
Getting Lost

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.

Energy Aware Cluster Head Selection for Maximizing Lifetime Improvement in Internet of Things

2017 ◽  
Vol 9 (4) ◽  
pp. 71-91 ◽  
Author(s):  
Praveen Kumar Reddy Maddikunta ◽  
Rajasekhara Babu Madda
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Hybrid Algorithm ◽  
Artificial Bee Colony ◽  
Cluster Head ◽  
High Energy ◽  
Superior Performance ◽  
Cluster Head Selection ◽  
Bee Colony ◽  
Iot Devices

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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