Cooperative Error Control Mechanism Combining Cognitive Technology for Video Streaming Over Vehicular Networks

Cooperative Error Control Mechanism Combining Cognitive Technology for Video Streaming Over Vehicular Networks

Ming-Fong Tsai, Naveen Chilamkurti, Hsia-Hsin Li
DOI: 10.4018/978-1-4666-3902-7.ch019
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Abstract

Video streaming over vehicular networks is an attractive feature to many applications, such as emergency video transmission and inter-vehicle video transmission. Vehicles accessing road-side units have a few seconds to download information and experience a high packet loss rate. Hence, this paper proposes Cooperative Error Control (CEC) mechanism combining Cognitive Technology (CT) for video streaming over wireless vehicular networks. CEC mechanism combining CT uses a cooperative error recover scheme to recover lost packets not only from a road-side unit which uses the primary channel but also from the other vehicles using a free channel. Hence, CEC mechanism with CT can enhance error recovery performance and quality of video streaming over vehicular networks. Simulation results show the error recover performance of the CEC mechanism combining CT performs better than the other related mechanisms.
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1. Introduction

Vehicular networks have emerged as a promising wireless communication technology in recent years (Leinmueller, Schoch, Kargl, & Maihofer, 2010; Coronado & Cherkaoui, 2010; Haas, Hu, & Laberteauz, 2010). Video streaming over vehicular networks is challenging because the video data dependencies within the compressed stream make any data loss damaging. The organization of video streaming over vehicular networks was investigated in Guo, Ammar, and Zegura (2005). The quality of video streaming will decrease with packet loss which errors will propagate in the dependency frames. Chilamkurti, Tsai, Ke, Park, and Kang (2010) proposed a Reliable Transmission Mechanism (RTM) which proposed the roadside unit relies on extra parity bytes adaptively added to a byte-level Forward Error Correction (FEC) to enhance the transmission quality. However, vehicular networks are characterized by intermittent connectivity to the roadside unit. Hence, the lost packets can’t recover when the vehicles aren’t in range of roadside unit. Therefore, innovative error recover mechanism is needed. Because passing vehicles may not linger sufficiently for a full video sequence to be transferred from a roadside unit, partial storage in any one vehicle may occur. Morillo-Pozo, Trullols, Barcelo. and Garcia-Vidal (2008) proposed a Cooperative Automatic Repeat reQuest (CARQ) mechanism to solve this problem. CARQ mechanism is used in wireless vehicular networks where cars download delay-tolerant information form a road-side unit, suffering an intermittent connectivity. Cooperation among cars is established in the dark areas where connectivity with the road-side units is lost. CARQ can effectively reduce packet losses of transmission from road-side unit to vehicles in a platoon. The main idea is to effectively reduce the packet losses of transmission from road-side unit to vehicles in a platoon. However, the lost packets can’t recover when the data packet losses are the same in the different neighbour vehicles. Moreover, the transmission channel of road-side unit to vehicles and transmission channel of vehicles to vehicles are the same which will decrease the transmission performance because of channel collision.

In order to solve previous problems, this paper proposes Cooperative Error Control (CEC) mechanism combining Cognitive Technology (CT) for video streaming over vehicular networks. CEC mechanism combining CT uses packet-level FEC mechanism to recover the lost source packets. The sender side overcomes packet losses by transmitting redundant information, allowing the recovery of a certain amount of missing video data at the receiver without retransmitting the lost packets using the primary channel in the range of road-side unit. When packet loss happens as vehicles leave the range of road-side unit, vehicles will try to receive the lost packet from the other vehicle’s free channel which is searched by CT. The lost packets received can not only recover lost packets but can also help the receiver recover the other lost packets again with a packet-level FEC mechanism. Hence, CEC mechanism combining CT uses the error recover scheme to recover the lost packets not only from the road-side unit using the primary channel but also from the other vehicles using the free channel. CEC mechanism combining CT uses an analytical model to decide the number of FEC redundant packets in order to obtain the minimum recovery overhead. Accordingly, CEC mechanism combining CT not only can avoid network collision stemming from unlimited packet retransmission but also can reduce the FEC redundancy to conserve network bandwidth by predicting the effective packet loss rate. Moreover, CEC mechanism combining CT can obtain a higher reduction in the packet losses of transmission. CEC mechanism combining CT is tested to show the benefits of low Effective Packet Loss Rate (EPLR) in improving the Peak Signal to Noise Ratio (PSNR) and the Decodable Frame Rate (DFR) of video streaming over vehicular networks. Compared with two related works, CEC mechanism combining CT shows the promising results when delivering video streaming over vehicular networks.

The remainder of this paper is organized as follows. The background and related works are introduced in Section 2. CEC mechanism combining CT is presented in Section 3. Section 4 discusses the experimental set-up and analyzes the experimental results. Final, the paper is summarized in Section 5.

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