scholarly journals An Energy-Efficient and Adaptive Channel Coding Approach for Narrowband Internet of Things (NB-IoT) Systems

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3465 ◽  
Author(s):  
Emmanuel Migabo ◽  
Karim Djouani ◽  
Anish Kurien
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Channel Coding ◽  
Energy Efficient ◽  
Research Work ◽  
Link Adaptation ◽  
Long Distance ◽  
Coding Scheme ◽  
Channel Conditions ◽  
Repetition Number

Most of the current research work on the Narrowband Internet of Things (NB-IoT) is focused on enhancing its network coverage. Many of the existing NB-IoT channel coding techniques are based on repeating transmission data and control signals as a way of enhancing the network’s reliability and therefore, enabling long-distance transmissions. Although most of these efforts are made at the expense of reducing the energy consumption of the NB-IoT network, they do not always consider the channel conditions. Therefore, this work proposes a novel NB-IoT Energy-Efficient Adaptive Channel Coding (EEACC) scheme. The EEACC approach is a two-dimensional (2D) approach which not only selects an appropriate channel coding scheme based on the estimated channel conditions (dynamically classified as bad, medium or good from initial based on a periodically assessed BLER performance outcome) but also minimizes the transmission repetition number under a pre-assessed probability of successful transmission (based on the ratio of previous successful transmissions over the total number of transmissions). This results in creating a single mixed gradient based on which a higher or lower Modulating Coding Scheme (MCS) is selected on each transmission. It is aimed at enhancing the overall energy efficiency of the network by dynamically selecting the appropriate Modulation Coding Scheme (MCS) number and efficiently minimizing the transmission repetition number. Link-level simulations are performed under different channel conditions (good, medium, or bad) considerations to assess the performance of the proposed up-link adaptation technique for NB-IoT. The obtained results demonstrate that the proposed technique outperforms the existing Narrowband Link Adaptation (NBLA) as well as the traditional repetition schemes in terms of the achieved energy efficiency as well as network reliability, latency, and scalability.

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 Novel model for boosting security strength and energy efficiency in internet-of-things using multi-staged game

2019 ◽  
Vol 9 (5) ◽  
pp. 4326 ◽  
Author(s):  
Bhagyashree Ambore ◽  
Suresh L
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Large Scale ◽  
Research Work ◽  
Balance Performance ◽  
Large Scale Network ◽  
Joint Solution ◽  
Scale Network ◽  
Threat Mitigation ◽  
Novel Model

Security as well as energy efficiency is one of the most inevitable and challenging problems when it comes it large scale network deployment like INternet-of-Things (IoT). After reviewing existing research work on IoT, it was found that there are discrete set of solution for security as well as for energy. However, there is little research work that has jointly investigated both the problems with respect to IoT. Apart from this, there are also various form of attacks that cost energy of sensors that constitutes core physical devices in IoT. Therefore, these manuscripts present a novel idea for identifying and resisting the security breach within an IoT system ensuring energy efficiency too. Harnessing the modelling capability of game-theory, the proposed system offers a joint solution towards these problems. The simulated outcome of the study is found to offer balance performance for better energy efficiency and robust threat mitigation capability when compared with existing approaches.

scholarly journals Energy Efficiency Optimization of Cognitive UAV-Assisted Edge Communication for Semantic Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yilong Gu ◽  
Yangchao Huang ◽  
Hang Hu ◽  
Weiting Gao ◽  
Yu Pan
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Optimization Problem ◽  
Optimization Scheme ◽  
Battery Capacity ◽  
Aerial Vehicle ◽  
Efficient Alternative ◽  
The Internet Of Things

With the consolidation of the Internet of Things (IoT), the unmanned aerial vehicle- (UAV-) based IoT has attracted much attention in recent years. In the IoT, cognitive UAV can not only overcome the problem of spectrum scarcity but also improve the communication quality of the edge nodes. However, due to the generation of massive and redundant IoT data, it is difficult to realize the mutual understanding between UAV and ground nodes. At the same time, the performance of the UAV is severely limited by its battery capacity. In order to form an autonomous and energy-efficient IoT system, we investigate semantically driven cognitive UAV networks to maximize the energy efficiency (EE). The semantic device model for cognitive UAV-assisted IoT communication is constructed. And the sensing time, the flight speed of UAV, and the coverage range of UAV communication are jointly optimized to maximize the EE. Then, an efficient alternative algorithm is proposed to solve the optimization problem. Finally, we provide computer simulations to validate the proposed algorithm. The performance of the joint optimization scheme based on the proposed algorithm is compared to some benchmark schemes. And the simulation results show that the proposed scheme can obtain the optimal system parameters and can significantly improve the EE.

scholarly journals Green Energy Efficient Routing with Deep Learning Based Anomaly Detection for Internet of Things (IoT) Communications

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 500
Author(s):  
E. Laxmi Lydia ◽  
A. Arokiaraj Jovith ◽  
A. Francis Saviour Devaraj ◽  
Changho Seo ◽  
Gyanendra Prasad Joshi
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Anomaly Detection ◽  
Energy Efficient ◽  
Short Term Memory ◽  
Data Communication ◽  
Green Energy ◽  
Sensor Nodes ◽  
Energy Efficient Routing ◽  
Iot Applications

Presently, a green Internet of Things (IoT) based energy aware network plays a significant part in the sensing technology. The development of IoT has a major impact on several application areas such as healthcare, smart city, transportation, etc. The exponential rise in the sensor nodes might result in enhanced energy dissipation. So, the minimization of environmental impact in green media networks is a challenging issue for both researchers and business people. Energy efficiency and security remain crucial in the design of IoT applications. This paper presents a new green energy-efficient routing with DL based anomaly detection (GEER-DLAD) technique for IoT applications. The presented model enables IoT devices to utilize energy effectively in such a way as to increase the network span. The GEER-DLAD technique performs error lossy compression (ELC) technique to lessen the quantity of data communication over the network. In addition, the moth flame swarm optimization (MSO) algorithm is applied for the optimal selection of routes in the network. Besides, DLAD process takes place via the recurrent neural network-long short term memory (RNN-LSTM) model to detect anomalies in the IoT communication networks. A detailed experimental validation process is carried out and the results ensured the betterment of the GEER-DLAD model in terms of energy efficiency and detection performance.

scholarly journals Review of Energy Efficient Techniques of IoT

2019 ◽  
Vol 7 (5) ◽  
pp. 17-21 ◽  
Author(s):  
Ritesh Awasthi ◽  
Navneet Kaur
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Research Work ◽  
Base Station ◽  
Sensor Nodes ◽  
Dynamic Nature ◽  
Work Related ◽  
Reduce Energy Consumption ◽  
The Internet Of Things

The network across which the information is sensed by the sensor devices and then forwarded to the sink is known as Internet of Things (IoT). Even though this system is deployed in several applications, there are certain issues faced in it due to its dynamic nature. The internet of things is derived from the wireless sensor networks. The sensor nodes which are deployed to sense environmental conditions are very small in size and also deployed on the far places due to which energy consumption is the major issue of internet of things. This research work related to reduce energy consumption of the network so that lifetime can be improved. In the existing system the approach of multilevel clustering is used for the data aggregation to base station. In the approach of multilevel clustering, the whole network is divided into clusters and cluster heads are selected in each cluster. The energy efficient techniques of internet of things are reviewed and analyzed in terms of certain parameters.

Fuzzy based Data Fusion for Energy Efficient Internet of Things

2019 ◽  
Vol 11 (3) ◽  
pp. 46-58 ◽  
Author(s):  
Madan Mohan Agarwal ◽  
Mahesh Chandra Govil ◽  
Madhavi Sinha ◽  
Saurabh Gupta
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Data Fusion ◽  
Energy Efficient ◽  
Fuzzy Controller ◽  
Light Weight ◽  
Embedded Devices ◽  
Simulation Based ◽  
Domains Of Life ◽  
Network Quality

Internet of Things will serve communities across the different domains of life. The resource of embedded devices and objects working under IoT implementation are constrained in wireless networks. Thus, building a scheme to make full use of energy is key issue for such networks. To achieve energy efficiency, an effective Fuzzy-based network data Fusion Light Weight Protocol (FLWP) is proposed in this article. The innovations of FLWP are as follows: 1) the simulated network's data fusion through fuzzy controller and optimize the energy efficiency of smart tech layer of internet of things (Energy IoT); 2) The optimized reactive route is dynamically adjusted based on fuzzy based prediction accurately from the number of routes provided by base protocol. If the selection accuracy is high, the performance enhances the network quality; 3) FLWP takes full advantage of energy to further enhance target tracking performance by properly selecting reactive routes in the network. Authors evaluated the efficiency of FLWP with simulation-based experiments. FLWP scheme improves the energy efficiency.

scholarly journals Energy Efficient Decision based Routing Technique using Fog Computing Paradigm

2019 ◽  
Vol 8 (9S) ◽  
pp. 964-969
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Energy Efficient ◽  
New Technologies ◽  
Fog Computing ◽  
Emergency Situation ◽  
The Internet ◽  
Computing Paradigm ◽  
Current Scenario ◽  
The Internet Of Things

In the era of new technologies, Fog computing becomes very popular in today’s scenario. Fog computing paradigm brings a concept that extends cloud computing to the edge and close proximity to the Internet of Things (IoT) network. The fundamental components of fog computing are fog nodes. Additionally, fog nodes are energy efficient nodes. Numerous fog nodes are deployed in the associated fields that will handle the Internet of Things (IoT) sensors computation. Meanwhile, the Internet of Things (IoT) faces challenges, among which energy efficiency is one of the most prominent or critical challenges in the current scenario. However, sensor devices are an energy constraintthatcreateshotspotduringtheroutingprocess.Forthis reason,tohandlesuchconstraints,thispaperpresentsaneffective hotspot mechanism using fog nodes that demonstrate the routing process and directed the sensors to choose the routing path as selected by the fog node. Moreover, fog node will act as a decision maker node and maintain the energy efficiency of sensors during the routing as fog nodes are energy efficient nodes. As it moves towards the emergency situation, the most appropriate and effective routing approach has been designed who maintain the energy level of sensors will be high during the routing process. The proposed routing technique could be better performance for the sake of efficient routing in terms of energy consumption and prolonging networklifetime.

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