scholarly journals A Quality-Configurable Approximate Serial Bus for Energy-Efficient Sensory Data Transfer

2018 ◽  
Vol 8 (3) ◽  
pp. 379-390 ◽  
Author(s):  
Setareh Behroozi ◽  
Vijay Raghunathan ◽  
Anand Raghunathan ◽  
Younghyun Kim
Keyword(s):  
Energy Efficient ◽  
Data Transfer ◽  
Sensory Data

scholarly journals Dual-shot dynamics and ultimate frequency of all-optical magnetic recording on GdFeCo

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Sicong Wang ◽  
Chen Wei ◽  
Yuanhua Feng ◽  
Hongkun Cao ◽  
Wenzhe Li ◽  
...  
Keyword(s):  
Magnetization Reversal ◽  
Energy Efficient ◽  
High Speed ◽  
Data Transfer ◽  
Laser Pulses ◽  
Time Resolved ◽  
All Optical ◽  
Fs Laser ◽  
High Speed Data ◽  
Natural Way

AbstractAlthough photonics presents the fastest and most energy-efficient method of data transfer, magnetism still offers the cheapest and most natural way to store data. The ultrafast and energy-efficient optical control of magnetism is presently a missing technological link that prevents us from reaching the next evolution in information processing. The discovery of all-optical magnetization reversal in GdFeCo with the help of 100 fs laser pulses has further aroused intense interest in this compelling problem. Although the applicability of this approach to high-speed data processing depends vitally on the maximum repetition rate of the switching, the latter remains virtually unknown. Here we experimentally unveil the ultimate frequency of repetitive all-optical magnetization reversal through time-resolved studies of the dual-shot magnetization dynamics in Gd27Fe63.87Co9.13. Varying the intensities of the shots and the shot-to-shot separation, we reveal the conditions for ultrafast writing and the fastest possible restoration of magnetic bits. It is shown that although magnetic writing launched by the first shot is completed after 100 ps, a reliable rewriting of the bit by the second shot requires separating the shots by at least 300 ps. Using two shots partially overlapping in space and minimally separated by 300 ps, we demonstrate an approach for GHz magnetic writing that can be scaled down to sizes below the diffraction limit.

scholarly journals Energy Efficient Opportunistic Sensing Management in Fog Cloud Environment

2021 ◽  
Vol 10 (10) ◽  
pp. 20-26
Author(s):  
Anju Gupta ◽  
R K Bathla
Keyword(s):  
Energy Efficient ◽  
Cost Effective ◽  
Sensory Data ◽  
Computing Platform ◽  
Opportunistic Sensing ◽  
Battery Power ◽  
Wide Range ◽  
Sensor Cloud ◽  
Set Up ◽  
Potential Challenge

With so many people now wearing mobile devices with sensors (such as smartphones), utilizing the immense capabilities of these business mobility goods has become a prospective skill to significant behavioural and ecological sensors. A potential challenge for pervasive context assessment is opportunistic sensing, has been effectively used to a wide range of applications. The sensor cloud combines cloud technology with a wireless sensor, resulting in a scalable and cost-effective computing platform for real-time applications. Because the sensor's battery power is limited and the data centre’s servers consume a significant amount of energy to supply storage, a sensor cloud must be energy efficient. This study provides a Fog-based semantic for enabling these kinds of technologies quickly and successfully. The suggested structure is comprised of fundamental algorithms to help set up and coordinate the fog sensing jobs. It creates effective multihop routes for coordinating relevant devices and transporting acquired sensory data to fog sinks. It was claimed that energy-efficient sensor cloud approaches were categorized into different groups and that each technology was examined using numerous characteristics. The outcomes of a series of thorough test simulation in NS3 to define the practicality of the created console, as well as the proportion of each parameter utilized for each technology, are computed.

scholarly journals A Reconfigurable IoT Architecture with Energy Efficient Event-Based Data Traffic Reduction Scheme

2017 ◽  
Vol 13 (02) ◽  
pp. 34 ◽  
Author(s):  
Varun Tiwari ◽  
Avinash Keskar ◽  
NC Shivaprakash
Keyword(s):  
Network Traffic ◽  
Energy Efficient ◽  
Data Transfer ◽  
Large Network ◽  
Data Traffic ◽  
Transfer Scheme ◽  
Data Packets ◽  
Traffic Reduction ◽  
Low Probability ◽  
Event Based

Designing an Internet of Things (IoT) enabled environment requires integration of various things/devices. Integrating these devices require a generalized approach as these devices can have different communication protocols. In this paper, we have proposed generalized nodes for connecting various devices. These nodes are capable of creating a scalable local wireless network that connects to the cloud through a network gateway. The nodes also support over the air programming to re-configure the network from the cloud. As number of devices connected to the cloud increases, the network traffic also increases. In order to reduce the network traffic we have used different data transfer schemes for the network. We have also proposed an event-based data transfer scheme for situations where there is low probability of change in sensor value. The experimental results shows that the event-based scheme reduces the data traffic by up to 48% under practical conditions without any loss of information compared to priority based data transfer. We have also shown that the proposed scheme is more reliable for data transfer in a large network with a success rate of 99.5% measured over 200 minutes for 1201 data packets.

scholarly journals Adaptive Framework Combining Sensors and IoT for Data Monitoring in Restricted Areas

2019 ◽  
Vol 8 (11) ◽  
pp. 564-567 ◽  
Keyword(s):  
Energy Efficiency ◽  
Data Transmission ◽  
Energy Efficient ◽  
Data Transfer ◽  
Sensor Data ◽  
Data Monitoring ◽  
Security Measures ◽  
Improve Energy Efficiency ◽  
Location Data ◽  
Adaptive Framework

The deployment of Internet-of-Things (IoT) enables an even richer variety of sensors at a much larger scale. Where offloading both the evaluation and the polling of IoT sensor data to the cloud would improve energy efficiency and data transfer costs for the mobile. We build an energy efficient framework for Combining Sensors and IoT to help developers easily builds applications that evaluate sensor data on the server via data transmission. We built a advanced framework to compress data i.e Novel Data Compression Approach that helps the user to know the regular movement of particular person with the sensor within the limited premises and the location surveillance of the host will be saving the location data with some security measures We also implement our protocol and compare it with the certificate-based scheme to illustrate its feasibility.

Sign in / Sign up

Export Citation Format

Share Document