Energy efficient IoT based on wireless sensor networks

Cho, Young-Bok; Kim, Minkang; Woo, Sung-Hee，

doi:10.23919/icact.2018.8323729

Cited by 7 publications

(1 citation statement)

References 7 publications

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“…Additionally, the traffic for each IoT device that collects data and further transmits smaller amounts of data to the IoT servers even though the generated data from large numbers of objects can have an impact on the performance of the network. Also, the IoT network will operate in a stable and sustainable manner for longer periods of time without a need for intervention [2].…”

Section: Introductionmentioning

confidence: 99%

Efficient Localized Data Aggregation of IoT Devices and its Application in Agriculture

2020

IJRTE

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Abstract: The Internet of Things (IoT) has a likely future for all technologies that are associated to the life of humans. Any communication between the social environments along with the user contexts will be made through the smart interfaces. The IoT will have to link to different diverse devices found in the Wireless Sensor Network (WSN) . Thus, the routing optimization which is energy efficient has become the primary factor in the performance of the network in the IoT. The widely popular routing used in WSN, Multi-hop Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, is found to be energy inefficient. The work will deal with the choice of finding the optimal path in routing through meta heuristic techniques to improve the lifespan of the network and the energy efficiency of the network. There are different techniques of metaheuristics such as Teacher Learning Based Optimization (TLBO) andParticle Swarm Optimization (PSO) were used effectively for finding optimal solutions for problems. In this work, the PSO-based algorithms were used for locating an optimal sink position to their nodes that make the network efficient in terms of energy. The TLBO metaheuristic is population-based and is based on the concept of teaching and the learning procedure observed in a classroom, which is adapted to the routing problem. The results of the experiment prove that the proposed technique was achieved better levels of performance compared to the other methods..

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Section: Introductionmentioning

confidence: 99%

Efficient Localized Data Aggregation of IoT Devices and its Application in Agriculture

2020

IJRTE

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Requirements for Energy Efficient Edge Computing: A Survey

Väänänen

Hämäläinen

2018

Lecture Notes in Computer Science

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Internet of Things is evolving heavily in these times. One of the major obstacle is energy consumption in the IoT devices (sensor nodes and wireless gateways). The IoT devices are often battery powered wireless devices and thus reducing the energy consumption in these devices is essential to lengthen the lifetime of the device without battery change. It is possible to lengthen battery lifetime by efficient but lightweight sensor data analysis in close proximity of the sensor. Performing part of the sensor data analysis in the end device can reduce the amount of data needed to transmit wirelessly. Transmitting data wirelessly is very energy consuming task. At the same time, the privacy and security should not be compromised. It requires effective but computationally lightweight encryption schemes. This survey goes thru many aspects to consider in edge and fog devices to minimize energy consumption and thus lengthen the device and the network lifetime.

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Green Computing and Internet of Things for Smart Cities: Technologies, Challenges, and Implementation

Sarkar

Gul

2020

Green Energy and Technology

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Energy efficient IoT based on wireless sensor networks

Cited by 7 publications

References 7 publications

Efficient Localized Data Aggregation of IoT Devices and its Application in Agriculture

Efficient Localized Data Aggregation of IoT Devices and its Application in Agriculture

Requirements for Energy Efficient Edge Computing: A Survey

Green Computing and Internet of Things for Smart Cities: Technologies, Challenges, and Implementation

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