scholarly journals An NB-IoT-Based Edge-of-Things Framework for Energy-Efficient Image Transfer

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5929
Author(s):  
Sikandar Zulqarnain Khan ◽  
Yannick Le Moullec ◽  
Muhammad Mahtab Alam
Keyword(s):  
Machine Learning ◽  
Energy Consumption ◽  
Low Power ◽  
Data Transmission ◽  
Energy Efficient ◽  
Transmission Time ◽  
Processing Unit ◽  
Image Transfer ◽  
Visual Data ◽  
Smart Gateway

Machine Learning (ML) techniques can play a pivotal role in energy efficient IoT networks by reducing the unnecessary data from transmission. With such an aim, this work combines a low-power, yet computationally capable processing unit, with an NB-IoT radio into a smart gateway that can run ML algorithms to smart transmit visual data over the NB-IoT network. The proposed smart gateway utilizes supervised and unsupervised ML algorithms to optimize the visual data in terms of their size and quality before being transmitted over the air. This relaxes the channel occupancy from an individual NB-IoT radio, reduces its energy consumption and also minimizes the transmission time of data. Our on-field results indicate up to 93% reductions in the number of NB-IoT radio transmissions, up to 90.5% reductions in the NB-IoT radio energy consumption and up to 90% reductions in the data transmission time.

scholarly journals Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Energy Efficient ◽  
Fog Computing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hierarchical Routing

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime

scholarly journals IESDAD :improved energy efficient structure- free data aggregation and delivery protocol in WSN

2018 ◽  
Vol 7 (2.27) ◽  
pp. 132
Author(s):  
Avneet Kaur ◽  
Neeraj Sharma
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Transmission ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Sensor Node ◽  
Base Station ◽  
Wireless Sensor ◽  
Gateway Node ◽  
Free Data

The wireless sensor is deployed to sense large amount of data from the far places. With the large deployment of the sensor networks, it faces major issues like energy consumption, dynamic routing and security. The Energy efficient structure-free data aggregation and delivery (ESDAD) is the protocol which is hierarchal in nature. The ESDAD protocol can be further improved to increase lifetime of wireless sensor networks. The base station localizes the position of each sensor node and defines level of each node for the data transmission. In the ESDAD protocol, the next hop node is selected based on cost function for the data transmission. In this research work, improved in ESDAD protocol is proposed in which gateway nodes are deployed after each level for the data transmission. The sensor node will sense the information and transmit it to gateway node. The gateway node aggregates data to the base station and simulation results show that improved ESDAD protocol performs well in terms of energy consumption and number of throughput. 

An Energy-Efficient Receiver for Human Body Communication

2012 ◽  
Vol 195-196 ◽  
pp. 84-89
Author(s):  
Da Hui Zhang ◽  
Ze Dong Nie ◽  
Feng Guan ◽  
Lei Wang
Keyword(s):  
Low Power ◽  
Human Body ◽  
Data Transmission ◽  
Energy Efficient ◽  
Low Noise ◽  
Variable Gain Amplifier ◽  
Cmos Process ◽  
Variable Gain ◽  
Active Balun ◽  
Noise Amplifier

A low-power, wideband signaling receiver for data transmission through a human body was presented in this paper. The receiver utilized a novel implementation of energy-efficient wideband impulse communication that uses the human body as the transmission medium, provides low power consumption, high reception sensitivity. The receiver consists of a low-noise amplifier, active balun, variable gain amplifier (VGA) Gm-C filter, comparator, and FSK demodulator. It was designed with 0.18um CMOS process in an active area of 1.54mm0.414mm. Post-simulation showed that the receiver has a gain range of-2dB~40dB. The receiver consumes 4mW at 1.8V supply and achieves transmission bit energy of 0.8nJ/bit.

scholarly journals Exploiting Data-dependencies in Ultra Low-power DSP Arithmetic

VLSI Design ◽  
2001 ◽  
Vol 12 (3) ◽  
pp. 349-363
Author(s):  
V. A. Bartlett ◽  
E. Grass
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Low Power ◽  
Energy Efficient ◽  
Dynamic Logic ◽  
Low Power Consumption ◽  
Ultra Low Power ◽  
Data Dependencies ◽  
Simulation Results ◽  
Asynchronous Environments

Strategies for the design of ultra low power multipliers and multiplier-accumulators are reported. These are optimized for asynchronous applications being able to take advantage of data-dependent computation times. Nevertheless, the low power consumption can be obtained in both synchronous and asynchronous environments. Central to the energy efficiency is a dynamic-logic technique termed Conditional Evaluation which is able to exploit redundancies within the carry-save array and deliver energy consumption which is also heavily data-dependent.Energy efficient adaptations for handling two's complement operands are introduced. Area overheads of the proposed designs are estimated and transistor level simulation results of signed and unsigned multipliers as well as a signed multiplier-accumulator are given.Normalized comparisons with other designs show our approach to use less energy than other published multipliers.

scholarly journals Energy Optimization in a Multihop Sensor Network for a WBAN Application

2021 ◽  
Vol 25 (1) ◽  
pp. 3-10
Author(s):  
Vishakha Tyagi ◽  
◽  
Sindhu Hak Gupta ◽  
Monica Kaushik ◽  
◽  
...  
Keyword(s):  
Energy Consumption ◽  
Data Transmission ◽  
Energy Efficient ◽  
Data Packet ◽  
Packet Size ◽  
Body Area ◽  
Swarm Optimization ◽  
Posture Change ◽  
Long Time ◽  
Efficient Data

Movement and posture change of human body plays a crucial role in energy consumption while data transmission between strategically deployed nodes in wireless body area networks (WBANs). The majority of energy is used in transmission rather than processing of the data. Nodes within body are there for long time and need to be energy efficient so that the network lifetime is increased. In this paper, we propose an energy efficient data transmission for multi-hop network that uses particle swarm optimization (PSO) for optimizing the parameters on which energy consumption relies. An energy efficient data transmission and reception takes place by altering the parameters like node to node distance and packet size of data. The obtained results show a significant reduction of energy consumed by reducing the packet size and keeping the node-to-sink distance a constant value. The total energy consumed per hop per bit length of data packet Emh/L shows 75% optimization. The energy consumed in data transmission per bit length of data E tx /L and the energy consumed for data received per bit length of data packet E rx /L is optimized by approximately 70% and 50% respectively for hope count 2 to 5.

scholarly journals Development of Low-Power Wide-Area Communication Gateway for Power Data Transmission

2021 ◽  
Vol 2083 (2) ◽  
pp. 022059
Author(s):  
Jian Sun ◽  
Hao Wu ◽  
Zhiyuan Huang ◽  
Binbin Bei ◽  
Songqian Cao ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Low Power ◽  
Data Transmission ◽  
Loss Rate ◽  
Rapid Development ◽  
Wide Area ◽  
Sensor Technology ◽  
Test Results ◽  
Network Nodes ◽  
Transmission Distance

Abstract With the rapid development and maturity of communication technology, integrated computer technology and sensor technology, small sensors with sensing, computing and communication capabilities have begun to appear all over the world. The sensor network composed of these small sensors has received a lot of attention. This paper studies the low-power wide-area communication gateway for power data transmission. Based on the analysis of the energy consumption strategy of the power data transmission process, the low-power wide-area communication gateway for power data transmission is developed, and the developed gateway was tested. According to the peer test results of the gateway, the packet loss rate of the gateway within 100m is relatively good. Therefore, when arranging network nodes, try to control the transmission distance of the gateway within 100m. The energy consumption test shows that the energy consumption of the gateway is basically in an ideal state.

scholarly journals Energy Efficient Policies for Data Transmission in Disruption Tolerant Heterogeneous IoT Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2891 ◽  
Author(s):  
George  Stamatakis ◽  
Elias Z.  Tragos ◽  
Apostolos Traganitis
Keyword(s):  
Energy Consumption ◽  
Data Transmission ◽  
Energy Efficient ◽  
Packet Transmission ◽  
Base Stations ◽  
The Internet ◽  
Network Resources ◽  
Battery Lifetime ◽  
Disruption Tolerant Networks ◽  
Intermittent Connectivity

The Internet-of-things facilitates the development of many groundbreaking applications. A large number of these applications involve mobile end nodes and a sparsely deployed network of base stations that operate as gateways to the Internet. Most of the mobile nodes, at least within city areas, are connected through low power wide area networking technologies (LPWAN) using public frequencies. Mobility and sparse network coverage result in long delays and intermittent connectivity for the end nodes. Disruption Tolerant Networks and utilization of heterogeneous wireless interfaces have emerged as key technologies to tackle the problem at hand. The first technology renders communication resilient to intermittent connectivity by storing and carrying data while the later increases the communication opportunities of the end nodes and at the same time reduces energy consumption whenever short-range communication is possible. However, one has to consider that end nodes are typically both memory and energy constrained devices which makes finding an energy efficient data transmission policy for heterogeneous disruption tolerant networks imperative. In this work we utilize information related to the spatial availability of network resources and localization information to formulate the problem at hand as a dynamic programming problem. Next, we utilize the framework of Markov Decision Processes to derive approximately optimal and suboptimal data transmission policies. We also prove that we can achieve improved packet transmission policies and reduce energy consumption, extending battery lifetime. This is achieved by knowing the spatial availability of heterogeneous network resources combined with the mobile node’s location information. Numerical resultsshow significant gains achieved by utilizing the derived approximately optimal and suboptimal policies.

scholarly journals Energy-aware mobile edge computing for low-latency visual data processing

2017 ◽  
Author(s):  
◽  
Huy Trinh
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Data Processing ◽  
Real Time ◽  
Energy Efficient ◽  
User Preferences ◽  
Low Latency ◽  
Mobile Edge Computing ◽  
Incident Response ◽  
Visual Data

New paradigms such as Mobile Edge Computing (MEC) are becoming feasible for use in e.g., real-time decision-making during disaster incident response to handle the data deluge occurring in the network edge. However, MEC deployments today lack flexible IoT device data handling such as e.g., handling user preferences for real-time versus energy-efficient processing. Moreover, MEC can also benefit from a policy based edge routing to handle sustained performance levels with efficient energy consumption. In this thesis, we study the potential of MEC to address application issues related to energy management on constrained IoT devices with limited power sources, while also providing low-latency processing of visual data being generated at high resolutions. Using a facial recognition application that is important in disaster incident response scenarios, we propose a novel 'offload decision-making' algorithm that analyzes the tradeoffs in computing policies to offload visual data processing (i.e., to an edge cloud or a core cloud) at low-to-high workloads. This algorithm also analyzes the impact on energy consumption in the decision-making under different visual data consumption requirements (i.e., users with thick clients or thin clients). To address the processing-throughput versus energy-efficiency tradeoffs, we propose a ‘Sustainable Policy-based Intelligence-Driven Edge Routing' (SPIDER) algorithm that uses machine learning within Mobile Ad hoc Networks (MANETs). This algorithm improves the geographic routing baseline performance (i.e., minimizes impact of local minima) for performance sustainability, and enables easy/flexible policy specification. We evaluate our proposed algorithms by conducting experiments on a realistic edge and core cloud testbed, and recreate disaster scenes of tornado damages (occurred in Joplin, MO in 2011) within simulations. From our empirical results obtained from experiments with a facial recognition application in the GENI Cloud testbed, we show how MEC can provide flexibility to users who desire energy conservation over low-latency or vice versa in the visual data processing. Our NS-3 based simulation results show that our routing approach is more sustainable in terms of throughput, more energy-efficient and flexible than existing solutions to handle diverse user preferences under high node mobility and severe node failure conditions.

scholarly journals Mobility management for RPL protocol in internet of things

2020 ◽  
Vol 19 (1) ◽  
pp. 451
Author(s):  
Zohreh Royaee ◽  
Hamid Mirvaziri ◽  
Amid Khatibi bardsiri
Keyword(s):  
Low Power ◽  
Routing Protocol ◽  
Data Transmission ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Lossy Networks ◽  
Routing Metrics ◽  
Biological Behaviour ◽  
Packet Delivery ◽  
Low Power Wireless Networks

<p>The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) was proposed for various applications of IPv6 low power wireless networks. While RPL supports various routing metrics and is designed to be suitable for wireless sensor network environments, it does not consider the mobility of nodes. Therefore, there is a need for a method that is energy efficient and that provides stable and reliable data transmission by considering the mobility of nodes in RPL networks. In this paper a new heuristic flabellum algorithm inspired by physical and biological behaviour of flabella in the sea is presented, and bottleneck and swarm problems are resolved through managing the moving nodes by flabellum algorithm. Finally, the proposed algorithm’s performance is evaluated using the Cooja simulator. The proposed algorithm;Flabellum RPL; shows significant improvements with regards to packet delivery, and convergence and lifetime.</p>

scholarly journals CMOS: Efficient Clustered Data Monitoring in Sensor Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jun-Ki Min
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Transmission ◽  
Energy Efficient ◽  
Data Gathering ◽  
Synthetic Data ◽  
Sensor Nodes ◽  
Smart Sensors ◽  
User Query ◽  
Energy Efficient Clustering

Tiny and smart sensors enable applications that access a network of hundreds or thousands of sensors. Thus, recently, many researchers have paid attention to wireless sensor networks (WSNs). The limitation of energy is critical since most sensors are battery-powered and it is very difficult to replace batteries in cases that sensor networks are utilized outdoors. Data transmission between sensor nodes needs more energy than computation in a sensor node. In order to reduce the energy consumption of sensors, we present an approximate data gathering technique, called CMOS, based on the Kalman filter. The goal of CMOS is to efficiently obtain the sensor readings within a certain error bound. In our approach, spatially close sensors are grouped as a cluster. Since a cluster header generates approximate readings of member nodes, a user query can be answered efficiently using the cluster headers. In addition, we suggest an energy efficient clustering method to distribute the energy consumption of cluster headers. Our simulation results with synthetic data demonstrate the efficiency and accuracy of our proposed technique.

Sign in / Sign up

Export Citation Format

Share Document