High Loss Improved Broadcasting Retransmission Approach Based on Network Coding

2014 ◽  
Vol 1021 ◽  
pp. 261-265
Author(s):  
Hang Liu ◽  
Jie Li ◽  
Guang Chen
Keyword(s):  
Wireless Networks ◽  
Network Coding ◽  
Packet Loss ◽  
Loss Rate ◽  
Packet Loss Rate ◽  
High Loss ◽  
Simulation Results

When the packet loss rate is high in the wireless networks, the performance of network coding wireless broadcasting retransmission scheme becomes worse. Aiming at the problem of network coding wireless broadcasting retransmission scheme, high loss improved broadcasting retransmission approach based on network coding is proposed. Simulation results demonstrate that compared with the traditional wireless broadcasting retransmission scheme and the network coding wireless broadcasting retransmission scheme, high loss improved broadcasting retransmission approach based on network coding can ensure the ensure the reliability and effectiveness of the transmission in wireless broadcasting network.

An Improvement of Contention Window for IEEE 802.15.6 CSMA/CA

2020 ◽  
Vol 17 (8) ◽  
pp. 3333-3336
Author(s):  
Neji Kouka ◽  
Tarek Guesmi ◽  
K. Ashokkumar ◽  
Ouajdi Korbaa
Keyword(s):  
Wireless Communications ◽  
Packet Loss ◽  
Loss Rate ◽  
Packet Loss Rate ◽  
Wireless Access ◽  
Contention Window ◽  
Ieee 802.15.6 ◽  
Window Length ◽  
Access Technology ◽  
Simulation Results

The IEEE 802.15.6 standard is become an essential wireless access technology for the WBAN networks, with an objective to adapt wireless communications to the recent applications. This paper proposes an improvement of the well known CSMA/CA procedure with an idea to give a new size of its contention window length. Simulation results show that, compared with standard IEEE 802.15.6, the delay time, packet loss rate of the improved CSMA/CA are be significantly reduced.

scholarly journals Network Coding for Efficient Video Multicast in Device-to-Device Communications

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2254 ◽  
Author(s):  
Lei Wang ◽  
Yulong Li ◽  
Bo Pan ◽  
Qiuwei Wu ◽  
Jun Yin ◽  
...  
Keyword(s):  
Network Coding ◽  
Packet Loss ◽  
Loss Rate ◽  
Transmission Rate ◽  
Packet Loss Rate ◽  
Source Node ◽  
Video Multicast ◽  
Data Packets ◽  
Device To Device ◽  
Efficient Video

Device-to-Device (D2D) communication is one of the critical technologies for the fifth-generation network, which allows devices to communicate directly with each other while increasing transmission rate, but this communication is vulnerable to interference. When video transmission is carried out in an environment with interference, problems such as high packet loss rate, poor quality of the video, and blurred screen may exist. These problems can be effectively solved by redundant coding operations at the source node, but the extra coding operation imposes a heavy computational burden on the source node. In order to alleviate the computational overhead of the source node, reduce transmission delay, and guarantee transmission quality, this paper proposes an efficient video multicast transmission scheme based on Random Linear Network Coding (RLNC) in D2D networks. In the scheme, the receiving devices in the transmission participate in the process of generating repair packets that are used to remedy the loss of encoded packets during transmission. The source node multicasts the encoded video file. The receiving nodes re-encode the received data packets with RLNC and then send them to the network again. The nearby nodes can decode the original data through the encoded or re-encoded data packets. The performance of the proposed scheme is evaluated through both simulation and real experiments. The experimental results show that compared with the traditional RLNC scheme, this scheme could balance the computation overhead of the mobile devices and reduce the encoding and decoding delay by about 8%. When the packet loss rate is high, the proposed scheme can obtain better video quality than the traditional replication-based scheme.

scholarly journals TCP adaptation with network coding and opportunistic data forwarding in multi-hop wireless networks

2016 ◽  
Vol 2 ◽  
pp. e89 ◽  
Author(s):  
Chen Zhang ◽  
Yuanzhu Chen ◽  
Cheng Li
Keyword(s):  
Wireless Networks ◽  
Network Coding ◽  
Packet Loss ◽  
Mesh Networks ◽  
Congestion Window ◽  
Data Forwarding ◽  
Positive Feedbacks ◽  
Wireless Mesh ◽  
Simulation Results ◽  
Adaptation Layer

Opportunistic data forwarding significantly increases the throughput in multi-hop wireless mesh networks by utilizing the broadcast nature of wireless transmissions and the fluctuation of link qualities. Network coding strengthens the robustness of data transmissions over unreliable wireless links. However, opportunistic data forwarding and network coding are rarely incorporated with TCP because the frequent occurrences of out-of-order packets in opportunistic data forwarding and long decoding delay in network coding overthrow TCP’s congestion control. In this paper, we propose a solution dubbed TCPFender, which supports opportunistic data forwarding and network coding in TCP. Our solution adds an adaptation layer to mask the packet loss caused by wireless link errors and provides early positive feedbacks to trigger a larger congestion window for TCP. This adaptation layer functions over the network layer and reduces the delay of ACKs for each coded packet. The simulation results show that TCPFender significantly outperforms TCP/IP in terms of the network throughput in different topologies of wireless networks.

Packet loss rate monitoring model of IOT based on differential evolution algorithm

2021 ◽  
pp. 1-12
Author(s):  
Yinghua Feng ◽  
Wei Yang
Keyword(s):  
Internet Of Things ◽  
Differential Evolution ◽  
Packet Loss ◽  
Loss Rate ◽  
Differential Evolution Algorithm ◽  
Packet Loss Rate ◽  
Data Space ◽  
Monitoring Model ◽  
Evolution Algorithm ◽  
The Internet Of Things

In order to overcome the problems of high energy consumption and low execution efficiency of traditional Internet of things (IOT) packet loss rate monitoring model, a new packet loss rate monitoring model based on differential evolution algorithm is proposed. The similarity between each data point in the data space of the Internet of things is set as the data gravity. On the basis of the data gravity, combined with the law of gravity in the data space, the gravity of different data is calculated. At the same time, the size of the data gravity is compared, and the data are classified. Through the classification results, the packet loss rate monitoring model of the Internet of things is established. Differential evolution algorithm is used to solve the model to obtain the best monitoring scheme to ensure the security of network data transmission. The experimental results show that the proposed model can effectively reduce the data acquisition overhead and energy consumption, and improve the execution efficiency of the model. The maximum monitoring efficiency is 99.74%.

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