Application Layer ARQ Algorithm for Real-Time Multi-Source Data Streaming in UAV Networks

Abstract

Because of the specific characteristics of Unmanned Aerial Vehicle (UAV) networks and real-time applications, the trade-off between delay and reliability imposes problems for streaming video. Buffer management and drop packets policies play a critical role in the final quality of the video received by the end station. In this paper, we present a reactive buffer management algorithm, called Multi-Source Application Layer Automatic Repeat Request (MS-AL-ARQ), for a real-time non-interactive video streaming system installed on a standalone UAV network. This algorithm implements a selective-repeat ARQ model for a multi-source download scenario using a shared buffer for packet reordering, packet recovery, and measurement of Quality of Service (QoS) metrics (packet loss rate, delay and, delay jitter). The proposed algorithm MS-AL-ARQ will be injected on the application layer to alleviate packet loss due to wireless interference and collision while the destination node (base station) receives video data in real-time from different transmitters at the same time. Moreover, it will identify and detect packet loss events for each data flow and send Negative-Acknowledgments (NACKs) if packets were lost. Additionally, the one-way packet delay, jitter, and packet loss ratio will be calculated for each data flow to investigate the performances of the algorithm for different numbers of nodes under different network conditions. We show that the presented algorithm improves the QoS of the video data received under the worst network connection conditions. Furthermore, some congestion issues during deep analyses of the algorithm’s performances have been identified and explained.

Application Layer Cooperative Automatic Repeat Request Method for Data Streaming over UAVs Network

“…The window size used for metrics measurements is defined based on the parameters of the scenario proposed (Wi-Fi standard, channel bandwidth, node velocity and reordering buffer size on the application layer). Because packet loss rate is dependent on link quality and network interference, loss events will occur which in turn invoke the application layer ALC-ARQ error control method [14]. The constant mobility of source nodes away from BS during the transmission will decrease the PLR measured on the application layer on BS.…”

Start-Up Strategy-Based Resilience Optimization of Onsite Monitoring Systems Containing Multifunctional Sensors

“…Moreover, researchers are focusing on the ability of complex systems to resist external disruptive events, among which resilience is an important indicator for evaluating system performance. Many complex systems should consider resilience because system suspension will cause substantial economic losses, especially in major engineering systems such as interdependent infrastructures [7], transportation systems [8], power systems [9], and container ports [10], oil and gas supply chain management [11], logistics systems [12], international trade [13], the large-scale optimization of damage functions [14], UAV networks [15], and epidemic vaccination [16]. The automatic replenishment of failed functions in a multiple functional system indicates the resistance ability of the system; therefore, it is necessary to analyze the resilience of multifunctional systems with multifunctional components.…”