scholarly journals A New Data Transfer Scheme for eMMC Connected Subsystems

2014 ◽  
Author(s):  
Deng Shulan
Keyword(s):  
Data Transfer ◽  
Transfer Scheme

Energy-Effective and Secure Data Transfer Scheme for Mobile Nodes in Smart City Applications

2021 ◽  
Author(s):  
Mukesh Soni ◽  
Gaurav Dhiman ◽  
Brajendra Singh Rajput ◽  
Rajan Patel ◽  
Nitesh Kumar Tejra
Keyword(s):  
Smart City ◽  
Data Transfer ◽  
Mobile Nodes ◽  
Transfer Scheme ◽  
Secure Data

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.

A Novel Segment-Based Data Transfer Scheme for Low-Power CMOS Surveillance Image Sensors

2017 ◽  
Vol 27 (02) ◽  
pp. 1850027
Author(s):  
Mehdi Habibi ◽  
Khatereh Akbari ◽  
Marzieh Mokhtari ◽  
Peyman Moallem
Keyword(s):  
Data Transfer ◽  
Cmos Technology ◽  
Image Sensor ◽  
Data Rate ◽  
Image Sensors ◽  
Solar Panels ◽  
Transfer Scheme ◽  
Data Rates ◽  
Low Power Cmos ◽  
The Given

Smart image sensors with low data rate output are well fitted for security and surveillance tasks, since at lower data rates, power consumption is reduced and the image sensor can be operated with limited energy resources such as solar panels. In this paper, a new data transfer scheme is presented to reduce the data rate of the pixels which have undergone value change. Although different pixel difference detecting architectures have been previously reported but it is shown that the given method is more effective in terms of power dissipation and data transfer rate reduction. The proposed architecture is evaluated as a [Formula: see text]-pixel sensor in a standard CMOS technology and comparison with other data transfer approaches is performed in the same process and configuration.

scholarly journals Integrating GPU support for FreeSurfer with OpenACC

2020 ◽  
Author(s):  
Jingcheng Shen ◽  
Jie Mei ◽  
Marcus Walldén ◽  
Fumihiko Ino
Keyword(s):  
Graphics Processing Units ◽  
High Performance ◽  
Data Transfer ◽  
Target Function ◽  
Brain Anatomy ◽  
Transfer Scheme ◽  
Accelerated Program ◽  
The Core ◽  
Computationally Expensive ◽  
Graphics Processing

AbstractFreeSurfer is among the most widely used suites of software for the study of cortical and subcortical brain anatomy. However, analysis using FreeSurfer can be time-consuming and it lacks support for the graphics processing units (GPUs) after the core development team stopped maintaining GPU-accelerated versions due to significant programming cost. As FreeSurfer is a large project with millions of source lines, in this work, we introduce and examine the use of a directive-based framework, OpenACC, in GPU acceleration of FreeSurfer, and we found the OpenACC-based approach significantly reduces programming costs. Moreover, because the overhead incurred by CPU-to-GPU data transfer is the major challenge in delivering GPU-based codes of high performance, we compare two schemes, copy- and-transfer and overlapped-fully-transfer, to reduce such data transfer overhead. Exper-imental results show that the target function we accelerated with overlapped-fully-transfer scheme ran 2.3 as fast as the original CPU-based function, and the GPU-accelerated program achieved an average speedup of 1.2 compared to the original CPU-based program. These results demonstrate the usefulness and potential of utilizing the proposed OpenACC-based approach to integrate GPU support for FreeSurfer which can be easily extended to other computationally expensive functions and modules of FreeSurfer to achieve further speedup.

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