A comparative study of in-sensor processing vs. raw data transmission using ZigBee, BLE and Wi-Fi for data intensive monitoring applications

2014 ◽  
Author(s):  
Khurram Shahzad ◽  
Bengt Oelmann
Keyword(s):  
Comparative Study ◽  
Data Transmission ◽  
Raw Data ◽  
Intensive Monitoring ◽  
Data Intensive ◽  
Monitoring Applications ◽  
Sensor Processing

scholarly journals Raw data queries during data-intensive parallel workflow execution

2017 ◽  
Vol 75 ◽  
pp. 402-422 ◽  
Author(s):  
Vítor Silva ◽  
José Leite ◽  
José J. Camata ◽  
Daniel de Oliveira ◽  
Alvaro L.G.A. Coutinho ◽  
...  
Keyword(s):  
Raw Data ◽  
Workflow Execution ◽  
Data Intensive ◽  
Parallel Workflow

scholarly journals Undersampled Differential Phase Shift On–Off Keying for Visible Light Vehicle-to-Vehicle Communication

2021 ◽  
Vol 11 (5) ◽  
pp. 2195
Author(s):  
Michael Plattner ◽  
Gerald Ostermayer
Keyword(s):  
Phase Shift ◽  
Bit Error Rate ◽  
Error Rate ◽  
Data Transmission ◽  
Raw Data ◽  
Differential Phase Shift ◽  
Differential Phase ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Vehicle To Vehicle Communication

An important development direction for the future of the automotive industry is connected and cooperative vehicles. Some functionalities in traffic need the cars to communicate with each other. In platooning, multiple cars driving in succession reduce the distances between them to drive in the slipstream of each other to reduce drag, energy consumption, emissions, and the probability of traffic jams. The car in front controls the car behind remotely, so all cars in the platoon can accelerate and decelerate simultaneously. In this paper, a system for vehicle-to-vehicle communication is proposed using modulated taillights for transmission and an off-the-shelf camera with CMOS image sensor for reception. An Undersampled Differential Phase Shift On–Off Keying modulation method is used to transmit data. With a frame sampling rate of 30 FPS and two individually modulated taillights, a raw data transmission rate of up to 60 bits per second is possible. Of course, such a slow communication channel is not applicable for time-sensitive data transmission. However, the big benefit of this system is that the identity of the sender of the message can be verified, because it is visible in the captured camera image. Thus, this channel can be used to establish a secure and fast connection in another channel, e.g., via 5G or 802.11p, by sending a verification key or the fingerprint of a public key. The focus of this paper is to optimize the raw data transmission of the proposed system, to make it applicable in traffic and to reduce the bit error rate. An improved modulation mode with smoother phase shifts is used that can reduce the visible flickering when data is transmitted. By additionally adjusting the pulse width ratio of the modulation signal and by analyzing the impact of synchronization offsets between transmitter and receiver, major improvements of the bit error rate (BER) are possible. In previously published research, such a system without the mentioned adjustments was able to transmit data with a BER of 3.46%. Experiments showed that with those adjustments a BER of 0.48% can be achieved, which means 86% of the bit errors are prevented.

scholarly journals Technique to Generate the Secure Symmetric Key Under Variable Keys Environment using Genetic Algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 4384-4389
Keyword(s):  
Genetic Algorithm ◽  
Information Security ◽  
Comparative Study ◽  
Data Transmission ◽  
Initial Distribution ◽  
Artificial Intelligent ◽  
Unauthorized Access ◽  
Symmetric Key ◽  
A New Technique ◽  
Secured Communication

The purpose of information security is to protect information or data from misuse, unauthorized access and also to ensure the secured communication between transmitter and receiver. In this regard, one of the primary and foremost necessity is to protect the key by any means and should also be unbreakable. In this context, a mechanism namely, Automatic Variable Key (AVK) has been introduced to maintain the secrecy of the key. However, in this approach the initial key must be established earlier, then only it changes the keys and make unpredictable to guess, for every new block of data transmission. Thus, to overcome from this extra burden of initial distribution of key, we propose a new technique using Artificial Intelligent (AI) in order to generate the initial key automatically using the Genetic Algorithm (GA). We have demonstrated the importance of AI in the area of cryptography by our scheme. A comparative study is also carried out with the existing schemes to prove the proficiency of proposed scheme. Thus, in order to prove the unpredictability among the auto-generated keys, we have verified the randomness with the help of National Institute of Standards Technology (NIST) Test suite.

scholarly journals On the Exploration of Adaptive Mechanisms Providing Reliability in Clustered WSNs for Power Plant Monitoring

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Sathiyaseelan Rathinavel ◽  
Vijayakumar Pandi ◽  
Audithan Sivaraman
Keyword(s):  
Power Plant ◽  
Data Transmission ◽  
Simulation Analysis ◽  
Wireless Sensor ◽  
Packet Delivery ◽  
Reliable Transmission ◽  
Adaptive Mechanisms ◽  
Monitoring Applications ◽  
Plant Monitoring

Wireless Sensor Networks (WSNs) are used in almost every sensing and detection environment instead of wired devices in the current world, all the more in power plant monitoring applications. In such a kind of environment, providing reliability is a challenging task, since WSN makes use of low powered sensors. There are many existing works that provide reliable transmission in WSN (predominantly via multipath routing). However, most of the existing works take additional delay, excessive packet loss, and energy consumption, and hence they provide less packet delivery and throughput. Adaptive Priority Routing (APR) is first proposed during the initial design to provide efficiency in next hop selection. APR computes the priority value for selecting the intermediate nodes during the data transmission in order to improve the packet delivery, throughput, and energy efficiency. In addition to this, APR is developed into QAPR protocol to provide reliability which can operate in two modes,Drepresenting distance mode andQrepresenting quality of service (QoS) mode. The proposed work is simulated in both flat topology and hierarchical topologies and the simulation analysis shows that the reliability is increased significantly in comparison with existing works.

scholarly journals Adaptive Real-Time Offloading Decision-Making for Mobile Edges: Deep Reinforcement Learning Framework and Simulation Results

2020 ◽  
Vol 10 (5) ◽  
pp. 1663 ◽  
Author(s):  
Soohyun Park ◽  
Dohyun Kwon ◽  
Joongheon Kim ◽  
Youn Kyu Lee ◽  
Sungrae Cho
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Data Transmission ◽  
Energy Efficient ◽  
Computing Systems ◽  
Decision Algorithm ◽  
Dynamic Algorithm ◽  
Data Intensive ◽  
Learning Framework ◽  
Task Offloading

This paper proposes a novel dynamic offloading decision method which is inspired by deep reinforcement learning (DRL). In order to realize real-time communications in mobile edge computing systems, an efficient task offloading algorithm is required. When the decision of actions (offloading enabled, i.e., computing in clouds or offloading disabled, i.e., computing in local edges) is made by the proposed DRL-based dynamic algorithm in each unit time, it is required to consider real-time/seamless data transmission and energy-efficiency in mobile edge devices. Therefore, our proposed dynamic offloading decision algorithm is designed for the joint optimization of delay and energy-efficient communications based on DRL framework. According to the performance evaluation via data-intensive simulations, this paper verifies that the proposed dynamic algorithm achieves desired performance.

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