Decodable Frame Rate Research Articles

UAV Cluster-Based Video Surveillance System Optimization in Heterogeneous Communication of Smart Cities

Video surveillance system is the integration of computers, networks, communications, and video CODEC, etc. Because of its distributed architecture, parallel image processing and ease of installation and expansion, it is widely used in many fields such as education, transportation and industry. However, there are some challenges of video surveillance applications in smart cities such as large scale of video events, low quality and big delay of video data transmission, and the loss of video surveillance data integrity. In order to solve the above problems, this paper designs a series of optimization algorithms and scheduling strategies based on Unmanned Aerial Vehicle (UAV) cluster. Firstly, we construct a full device coverage network with UAV cluster in heterogeneous communication environment of smart cities. Secondly, we formulate the scheduling problem of UAV cluster as bi-objective fragile bin packing problem, and design an optimal scheduling algorithm with constant approximation performance ratio. The simulation experimental results fully demonstrate the effectiveness, feasibility and robustness of the proposed solution in terms of system life cycle, video decodable frame rate, the ratio of UAV flight time to system life cycle, throughput and delay.

RETRACTED ARTICLE: Invulnerability mechanism based on mobility prediction and opportunistic cloud computing with topological evolution for wireless multimedia sensor networks

According to the loss network problems caused by limited resources and environment interference factors, we presented a survivability mechanism based on mobility prediction and based on the topological evolution of cloud computing wireless multimedia sensor network (WMSN). First, based on cooperative neural network and opportunity Markov chain model, the multimedia mobile sensor node state and state transition probability could be predicted. Then, the opportunity computational scheme was given based on mobility prediction of dynamic topology evolution mechanism. Finally, using the network topology reconfiguration and opportunities for cloud computing, an enhanced WMSN survivability and end-to-end quality of service guarantee mechanism was proposed. Experimental results show that compared with the static scheme for WMSNs, the proposed survivability mechanism has the obvious advantage in the node protection, data communication, network life cycle, and decodable frame rate and other aspects, and can effectively improve the invulnerability of WMSNs.

Evaluation of the MDC and FEC over the quality of service and quality of experience for video distribution in ad hoc networks

Mobile ad hoc networks (MANETs) offer an excellent scenario for deploying communication applications because of the connectivity and versatility of this kind of networks. In contrast, the topology is usually extremely dynamic causing high rate of packet loss, so that ensuring a specific Quality of Service (QoS) for real-time video services becomes a hard challenge. In this paper, we evaluate the effect of using Multiple Description Coding (MDC) and Forward Error Correction (FEC) techniques for improving video quality in a multimedia content distribution system. A hybrid architecture using fixed and wireless ad hoc networks is proposed, which enables the use of multipoint-to-point transmission. MDC and FEC mechanisms can be combined with multipath transmission to increase the network efficiency and recover lost packets, improving the overall Quality of Experience (QoE) of the receiver. Simulations have been analyzed paying attention to objective parameters (Peak Signal to Noise Ratio, Packet Delivery Ratio, Decodable Frame Rate and interruptions) and subjective parameters. Results show that MDC increases the probability of packet delivery and FEC is able to recover lost frames and reduce video interruptions in moderate mobility scenarios, resulting in the improvement of video quality and the final user experience.

Forward-Looking Forward Error Correction Mechanism for Video Streaming Over Wireless Networks

Video streaming over wireless network poses a great challenge because the high packet error rate usually decreases the quality of video streaming. Forward error correction (FEC) mechanism is generally used to protect the video quality. However, the recovery performance of the FEC mechanism decreases when burst packet loss is larger than the added FEC redundant packets. In this paper, the forward-looking forward error correction (FL-FEC) mechanism is proposed to recover lost packets for video streaming over wireless networks. The FL-FEC mechanism recovers not only the lost packet from its FEC block but also the previous FEC block from the recovered packet, repeating the recovery procedure until recovering the first FEC block. If the play-out buffer at the receiver is large, the FL-FEC mechanism can execute a chain of recovery procedures to ultimately recover all lost packets without any negative impact on application performance. The FL-FEC mechanism selects non-continuous source packets in previous FEC blocks to generate FEC redundancy with the FEC block. Hence, the FL-FEC mechanism can significantly disperse burst packet loss into different FEC blocks. The FL-FEC mechanism uses an analytical model to decide the number of FEC redundant packets in order to obtain the minimum recovery overhead. The FL-FEC mechanism is tested to show the benefits of high recovery performance and low recovery overhead in improving the peak signal-to-noise ratio and the decodable frame rate of video streaming over wireless networks.

Unequal error protection under bitrate constraint for video streaming over internet

This article describes a simple packet-level FEC system suitable for unequal error protection of layered video streams, that we called TAPIOCA (in French, Transport Audiovisuel avec Protection Inegale des Objets et Controle d'Admission). It is designed in a way that the FEC overhead induced by redundant packets is perfectly controlled by the sender. In order to achieve that, TAPIOCA calculates on-the-fly the optimal erasure code to be used, video data unit by video data unit, under a given bitrate constraint. In addition, and contrary to the well-known PET (Priority Encoding Transmission) system, the video data units of each layer are encoded separately. This is especially useful when all layers are not output from the video coder at the same time. Simulation results for MPEG-4 video streaming show that the proposed FEC system can be very efficient even if packet losses are due to network congestion. Moreover, comparison with PET system shows that TAPIOCA exhibits better performance, considering criteria including the decodable frame rate, protection system efficiency and computational cost.

Adaptive hybrid error correction model for video streaming over wireless networks

The Hybrid ARQ (HARQ) mechanism is the well-known error packet recovery solution composed of the Automation Repeat reQuest (ARQ) mechanism and the Forward Error Correction (FEC) mechanism. However, the HARQ mechanism neither retransmits the packet to the receiver in time when the packet cannot be recovered by the FEC scheme nor dynamically adjusts the number of FEC redundant packets according to network conditions. In this paper, the Adaptive Hybrid Error Correction Model (AHECM) is proposed to improve the HARQ mechanism. The AHECM can limit the packet retransmission delay to the most tolerable end-to-end delay. Besides, the AHECM can find the appropriate FEC parameter to avoid network congestion and reduce the number of FEC redundant packets by predicting the effective packet loss rate. Meanwhile, when the end-to-end delay requirement can be met, the AHECM will only retransmit the necessary number of redundant FEC packets to receiver in comparison with legacy HARQ mechanisms. Furthermore, the AHECM can use an Unequal Error Protection to protect important multimedia frames against channel errors of wireless networks. Besides, the AHECM uses the Markov model to estimate the burst bit error condition over wireless networks. The AHECM is evaluated by several metrics such as the effective packet loss rate, the error recovery efficiency, the decodable frame rate, and the peak signal to noise ratio to verify the efficiency in delivering video streaming over wireless networks.

Dynamical combination of byte level and Sub-Packet level FEC in HARQ mechanism to reduce error recovery overhead on video streaming over wireless networks

Byte level Forward Error Correction (B-FEC) is efficient for recovery from uniform bit errors, but not suitable to handle recovery from burst bit errors. Conversely, Sub-Packet level Forward Error Correction (SP-FEC) can alleviate the problem of large encoding/decoding delay jitter in Packet level Forward Error Correction (P-FEC) to efficiently handle recovery from burst bit errors, but has large error recovery overhead as P-FEC for recovery from uniform bit errors. This paper proposes a dynamic combination of byte level and Sub-Packet level Forward Error Correction (BSP-FEC) in the Hybrid Automatic Repeat reQuest (HARQ) mechanism to reduce the error recovery overhead. BSP-FEC not only can solve the problems appearing in B-FEC and SP-FEC, but also can get the advantages of B-FEC and SP-FEC in the HARQ mechanism. BSP-FEC replaces the SP-FEC checksum with B-FEC and uses Automatic Repeat reQuest (ARQ) when the network condition deteriorates. BSP-FEC not only utilizes an overhead cost model to dynamically decide the SP-FEC parameter and the B-FEC bit rate according to network conditions, but also utilizes a time constraint model to decide the ARQ retry limit. BSP-FEC dynamically adjusts the FEC redundancy to save bandwidth and improves the Decodable Frame Rate (DFR) and the Peak Signal to Noise Ratio (PSNR) of the delivered video streaming. Accordingly, BSP-FEC can improve multimedia communication performance to both avoid network congestion and shorten end-to-end delay by decreasing effective packet loss rate and packet recovery overhead. Because of the low packet recovery overhead, furthermore, BSP-FEC allows applications to transmit more application data in networks with limited bandwidth. Considering the compatibility, BSP-FEC is implemented in the application layer as the end-to-end protection method to protect packets from errors in wired/wireless networks. Numerical and simulation experimental results show that BSP-FEC obtains better recovery efficiency with the minimum error recovery overhead.

Content-Based Video Quality Prediction for MPEG4 Video Streaming over Wireless Networks

There are many parameters that affect video quality but their combined effect is not well identified and understood when video is transmitted over mobile/ wireless networks. In addition, video content has an impact on video quality under same network conditions. The main aim of this paper is the prediction of video quality combining the application and network level parameters for all content types. Firstly, video sequences are classified into groups representing different content types using cluster analysis. The classification of contents is based on the temporal (movement) and spatial (edges, brightness) feature extraction. Second, to study and analyze the behaviour of video quality for wide range variations of a set of selected parameters. Finally, to develop two learning models based on – (1) ANFIS to estimate the visual perceptual quality in terms of the Mean Opinion Score (MOS) and decodable frame rate (Q value) and (2) regression modeling to estimate the visual perceptual quality in terms of the MOS. We trained three ANFIS-based ANNs and regression based- models for the three distinct content types using a combination of network and application level parameters and tested the two models using unseen dataset. We confirmed that the video quality is more sensitive to network level compared to application level parameters. Preliminary results show that a good prediction accuracy was obtained from both models. However, the regression based model performed better in terms of the correlation coefficient and the root mean squared error. The work should help in the development of a reference-free video prediction model and Quality of Service (QoS) control methods for video over wireless/mobile networks.

An adaptive multi‐hop forward error correction protection scheme for video streaming over wireless mesh networks

AbstractTraditional forward error correction (FEC) mechanisms can be divided into end‐to‐end FEC protection schemes and hop‐by‐hop FEC protection schemes. The end‐to‐end FEC protection schemes over‐allocate FEC redundancy to each link and may induce a self‐congestion effect in a link. The hop‐by‐hop FEC protection scheme incurs a long end‐to‐end delay that harms the video performance at the video receiver. Accordingly, the Adaptive Multi‐Hop FEC (AM‐FEC) protection scheme is proposed in this paper to improve the quality of video streaming data over Wireless Mesh Networks by means of simultaneously minimizing the end‐to‐end delay and reducing the FEC computational cost. The AM‐FEC protection scheme uses a heuristic algorithm to minimize the number of FEC‐encoded segments between the video sender and receiver. Moreover, according to the decodable frame rate the AM‐FEC protection scheme can dynamically adjust FEC redundancy on each link to outperform end‐to‐end FEC protection schemes and hop‐by‐hop FEC protection schemes. In the experiments, the AM‐FEC protection scheme achieves timely loss recovery for delay‐sensitive video streaming and outperforms traditional FEC protection schemes in terms of video peak signal‐to‐noise ratio. Copyright © 2009 John Wiley & Sons, Ltd.