scholarly journals An Adaptive Multi-Channel Cooperative Data Transmission Scheduling in VANETs

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5612
Author(s):  
Benhong Zhang ◽  
Baorui Yuan ◽  
Xiang Bi ◽  
Zhenchun Wei ◽  
Mingyue Zhang
Keyword(s):  
Data Transmission ◽  
Model Simulation ◽  
Scheduling Algorithm ◽  
Transmission Scheduling ◽  
Service Capacity ◽  
Transmission Delays ◽  
The Road ◽  
High Data ◽  
Service Delay ◽  
Cooperative Scheduling

The Internet of Vehicle (IoV) technology is one of the most important technologies of modern intelligent transportation. The data transmission scheduling method is a research hotspot in the technology of IoV. It is a challenge to ensure the stability of data transmission due to fast network topology changes, high data transmission delays, and some other reasons. Aiming at the above problems, a multi-channel data transmission cooperative scheduling algorithm is proposed. First, construct a feasible interference map based on the data items sent and received by vehicles in the road scene. Second, assign channels to the nodes in the interference map based on the Signal-to-Interference-Noise-Ratio (SINR). Finally, the optimal multi-channel data transmission cooperative scheduling scheme is achieved through the ISing model. Simulation results show that compared with the traditional algorithm, the network service capacity is increased by about 31% and the service delay is reduced by about 20%. It ensures that emergency data is preferentially transmitted to the target vehicle and the maximum weighted service capacity of the network.

scholarly journals A Satellite Observation Data Transmission Scheduling Algorithm Oriented to Data Topics

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Hao Chen ◽  
Baorong Zhai ◽  
Jiangjiang Wu ◽  
Chun Du ◽  
Jun Li
Keyword(s):  
Data Transmission ◽  
Domain Knowledge ◽  
Scheduling Algorithm ◽  
Satellite Observation ◽  
Observation Data ◽  
Transmission Scheduling ◽  
Expected Time ◽  
Knowledge Based ◽  
Sensing Applications ◽  
Speed Up

The scheduling of Earth Observation Satellite (EOS) data transmission is a complex combinatorial optimization problem. With the development of remote sensing applications, a new special requirement named data transmission oriented to topics has appeared. It supposes that the data obtained from each observation activity by satellites belong to certain observation data topics, and every observation data topic has completeness and timeliness requirements. Unless all of the observation data belonging to one topic has been transmitted to the ground before the expected time, the value of the observation data will be decayed sharply and only a part of the rewards (or even no reward) for the data transmission will be obtained. Current researches do not meet the new data topic transmission requirements well. Based on the characteristics of the problem, a mathematic scheduling model is established, and a novel hybrid scheduling algorithm based on evolutionary computation is proposed. In order to further enhance the performance and speed up the convergence process of our algorithm, a domain-knowledge-based mutation operator is designed. Quantitative experimental results show that the proposed algorithm is more effective to solve the satellite observation data topic transmission scheduling problem than that of the state-of-the-art approaches.

A large-scale multiobjective satellite data transmission scheduling algorithm based on SVM+NSGA-II

2019 ◽  
Vol 50 ◽  
pp. 100560 ◽  
Author(s):  
Jiawei Zhang ◽  
Lining Xing ◽  
Guansheng Peng ◽  
Feng Yao ◽  
Cheng Chen
Keyword(s):  
Satellite Data ◽  
Data Transmission ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Transmission Scheduling ◽  
Nsga Ii

Lane Detection Algorithm Based on Genetic Algorithm and its Parallel Computing Realization

2012 ◽  
Vol 479-481 ◽  
pp. 65-70
Author(s):  
Xiao Hui Zhang ◽  
Liu Qing ◽  
Mu Li
Keyword(s):  
Genetic Algorithm ◽  
Data Transmission ◽  
High Speed ◽  
High Performance ◽  
Large Data ◽  
Detection Algorithm ◽  
Lane Detection ◽  
The Road ◽  
Time Problem ◽  
High Speed Data

Based on the target detection of alignment template, the paper designs a lane alignment template by using correlation matching method, and combines with genetic algorithm for template stochastic matching and optimization to realize the lane detection. In order to solve the real-time problem of lane detection algorithm based on genetic algorithm, this paper uses the high performance multi-core DSP chip TMS320C6474 as the core, combines with high-speed data transmission technology of Rapid10, realizes the hardware parallel processing of the lane detection algorithm. By Rapid10 bus, the data transmission speed between the DSP and the DSP can reach 3.125Gbps, it basically realizes transmission without delay, and thereby solves the high speed transmission of the large data quantity between processor. The experimental results show that, no matter the calculated lane line, or the running time is better than the single DSP and PC at the parallel C6474 platform. In addition, the road detection is accurate and reliable, and it has good robustness.

Transmission scheduling algorithm for MIMO link ad hoc networks

2011 ◽  
Vol 55 (6) ◽  
pp. 1351-1359 ◽  
Author(s):  
Dan Chen ◽  
JianDong Li ◽  
ChangLe Li
Keyword(s):  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Scheduling Algorithm ◽  
Transmission Scheduling ◽  
Hoc Networks

scholarly journals Neighborhood condition for all fractional (g, f, n′, m)-critical deleted graphs

Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 544-553 ◽  
Author(s):  
Wei Gao ◽  
Yunqing Zhang ◽  
Yaojun Chen
Keyword(s):  
Data Transmission ◽  
Transmission Networks ◽  
Neighborhood Conditions ◽  
Transmission Rates ◽  
High Data ◽  
Critical Graph ◽  
Network Research ◽  
Neighborhood Condition ◽  
Fractional Factor ◽  
The Relationship

Abstract In data transmission networks, the availability of data transmission is equivalent to the existence of the fractional factor of the corresponding graph which is generated by the network. Research on the existence of fractional factors under specific network structures can help scientists design and construct networks with high data transmission rates. A graph G is named as an all fractional (g, f, n′, m)-critical deleted graph if the remaining subgraph keeps being an all fractional (g, f, m)-critical graph, despite experiencing the removal of arbitrary n′ vertices of G. In this paper, we study the relationship between neighborhood conditions and a graph to be all fractional (g, f, n′, m)-critical deleted. Two sufficient neighborhood conditions are determined, and furthermore we show that the conditions stated in the main results are sharp.

scholarly journals Group Buying-based Data Transmission in Flying Ad-hoc Networks: A Coalition Game Approach

2018 ◽  
Author(s):  
Lang Ruan ◽  
Jin Chen ◽  
Qiuju Guo ◽  
Xiaobo Zhang ◽  
Yuli Zhang ◽  
...  
Keyword(s):  
Formation Mechanism ◽  
Coalition Formation ◽  
Data Transmission ◽  
Large Scale ◽  
Ad Hoc ◽  
Model Simulation ◽  
System Model ◽  
Throughput Maximization ◽  
Coalition Game ◽  
Group Buying

In scenarios such as natural disasters and military strike, it is common for unmanned aerial vehicles (UAVs) to form groups to execute reconnaissance and surveillance. To ensure the effectiveness of UAV communications, repeated resource acquisition issues and transmission mechanism design need to be addressed urgently. In this paper, we build an information interaction scenario in a Flying Ad-hoc network (FANET). The data transmission problem with the goal of throughput maximization is modeled as a coalition game framework. Then, a novel mechanism of coalition selection and data transmission based on group-buying is investigated. Since large-scale UAVs will generate high transmission overhead due to the overlapping resource requirements, we propose a resource allocation optimization method based on distributed data content. Comparing existing works, a data transmission and coalition formation mechanism is designed. Then the system model is classified into graph game and coalition formation game. Through the design of the utility function, we prove that both games have stable solutions. We also prove the convergence of the proposed approach with coalition order and Pareto order. Binary log-linear learning based coalition selection algorithm (BLL-CSA) is proposed to explore the stable coalition partition of system model. Simulation results show that the proposed data transmission and coalition formation mechanism can achieve higher data throughput than the other contrast algorithms.

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