Loss Retransmission Research Articles

A energy efficiency optimization routing processing method for Linear Wireless Sensor Networks

Linear wireless Sensor networks (LWSNs) are extensively utilized to monitor linear infrastructure such as railways, bridges, mines, and borders. In the large-scale deployment of sensor networks, extending network life and improving network energy balance remains a significant challenge. The existing routing protocols adopt the path planning method based on the routing information database, which can effectively transmit data packets. However, the methods consume additional energy when establishing and maintaining routing tables, significantly reducing the nodes’ lifespan and leading to unstable data transmission quality. This paper proposes a dynamic random multipath routing method (DRMRM) for LWSNs. The technique combines the node depth and residual energy models to select the optimal next-hop relay node without relying on the transmission routing table. At the same time, we designed a data loss retransmission mechanism and a data loop retreat mechanism to prevent data packets from reaching a dead end. The experimental results demonstrate that our routing method is superior to existing energy consumption balance and network lifespan protocols.

Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoT

Wireless sensor networks (WSNs) based on compressed sensing (CS) can complete data sampling and data compression simultaneously, thereby greatly reducing the data transmission volume and the energy consumption of the network. However, many studies have not considered the loss of data packets due to the unreliable wireless communication, which leads to the data reconstruction not being as accurate as the applications require. In this paper, a Compressed Sensing with Dynamic Retransmission (CSDR) algorithm is proposed to guarantee high data reconstruction accuracy, high network lifetime and high energy utilization. The CSDR algorithm dynamically determines the max packet loss retransmission times of different nodes according to their residual energies, for Internet of Thing (IoT) devices with relative high energy consumption, fewer max retransmission times is adopted to maintain a longer network lifetime. For energy-rich IoT devices, more max retransmission times is used to improve the data transmission accuracy and the performance of data reconstruction. Strict theoretical analysis and experimental results show that the CSDR algorithm significantly improves the main performance indicators compared to the previous strategy: The Normalized Mean Absolute Error (NMAE) is reduced by 64.5%, and the effective utilization of energy is improved by 34.1% on average, under the condition that the network lifetime is no less than the previous scheme.

Increasing uplink broadband video streaming protocol performance in WiMAX network

WiMAX as a broadband wireless access technology is used increasingly for last mile infrastructures, including video distribution network. Although WiMAX offers high bit-rate wireless connectivity, wireless interference remains an issue. Various transport layer protocols have been proposed to enhance wireless video streaming performance, including re-transmission-based protocol. However, re-transmission yields additional delay, which is not expected in a real-time environment. This paper proposes a cross-layer approach to improve uplink broadband video streaming protocol. The proposed method is aimed at reducing delay caused by the packet loss re-transmission, and to enhance the video quality by implementing the cross-layer bandwidth request. NS-2 simulations demonstrate the significance of the proposed method.

Analysis of RTO Caused by Retransmission Loss to Combat Channel Noise

A Retransmission Time Out (RTO) is inevitable, when the retransmission of a packet fails to reach the receiver. An RTO compels TCP to reduce packet flow drastically. However, in case of an RTO resulting from retransmission failure caused by the channel noise, reduction in the flow is inappropriate. The problem is compounded when a TCP sender is forbidden to continue transmission till the occurrence of the timeout. In this paper, we investigate the impact of such RTOs with the help of an empirical mathematical analysis. The analysis presented in the paper calculates the idle period of the sender in terms of number of RTTs, which depends on the value of congestion window before the timeout. The mathematical analysis is supported by the results of simulation based experiments and the evaluation of a scheme that improves TCP performance in case of avoidable timeouts caused by the loss of retransmission on an erroneous wireless link.

QoS Multicast Protocol for Live Streaming

Live streaming media are delay sensitive and have limited allowable delays. Current conventional multicast protocols do not have a loss retransmission mechanism. Even though several reliable multicast protocols with retransmission mechanisms have been proposed, the long delay and high packet loss rate make them inefficient for live streaming. This paper proposes a multicast protocol focusing on the allowable delay called the QoS Multicast for Live Streaming (QMLS) protocol. QMLS routers are placed along the multicast tree to detect and retransmit lost packets. We propose a method that enables data recovery to be done immediately after lost packets are detected by the QMLS router and a method that reduces the unnecessary packets sent to end receivers. This paper discusses the mathematical analysis of the proposed protocol and compares it with other multicast protocols. The results reveal that our protocol is more effective in live streaming. Finally, we do a simulation to evaluate its performance and study the effect of consecutive losses. The simulation reveals that consecutive losses can slightly increase losses with our protocol.

Retransmission Loss Recovery by Duplicate Acknowledgment Counting

The performance of transmission control protocol (TCP) is largely dependent upon its loss recovery. Therefore, it is a very important issue whether the packet losses may be recovered without retransmission timeout (RTO) or not. TCP always evokes RTO if a retransmitted packet is lost again. In order to alleviate this problem, we propose an algorithm called duplicate acknowledgment counting (DAC). We use a stochastic model to evaluate the performance of DAC, and compare it with TCP NewReno. Numerical results evaluated by simulations show that DAC can improve TCP loss recovery significantly in presence of random losses.