Elsevier

Ad Hoc Networks

Volume 88, 15 May 2019, Pages 18-31
Ad Hoc Networks

Quality enhancement with fault tolerant embedding in video transmission over WMSNs in 802.11e WLAN

https://doi.org/10.1016/j.adhoc.2018.12.013Get rights and content

Abstract

With the ever-growing demand in video transmissions, it is essential to design an efficient compression and powerful transmission scheme to transmit a large volume of data in wireless multimedia sensor networks (WMSNs). The main objective of this work is to maximize the network throughput and to maintain/support a better visual experience to different end-users. In this paper, we propose a predictive compression with fault-tolerant embedding based multi-path routing and concealment process to maintain the Quality of Service (QoS) and Quality of Experience (QoE) in video transmission. In order to reduce the bit rate in high-efficiency videos, a Scalable High-efficiency Inter-layer Prediction based Video coding (SHIPVC) is proposed with two layer predictions such as texture color, and motion with different quantization parameters to attain the high coding efficiency. After compression, a multi-path genetic algorithm establishes a routing and fault tolerance embedding during transmission to maintain the QoS. In decoding side, QoE is maintained by concealing the Intra frame (I-frame) and Predicted frame (P-frame) separately using the motion vector estimation. Experimental results show better performances through bit rate reduction, maximum fault tolerance, and minimum delay parameters. The PSNR calculation for concealment technique shows the better result when compared to the previous standards. Hence, the proposed method performs the effective video transmission with acceptable quality measurements in WMSNs.

Introduction

Real-time streaming of high-quality video in WSMN plays a major attention for researchers. As these networks support many real-time applications, there is a need to develop an efficient scheme with the additional features [1]. Wireless sensor multimedia network is composed of several sensor nodes that contain cameras, microphones, and sensors creating multimedia content, which may sense the environmental phenomenon and retrieve the multimedia content. It is implemented in sensitive environments where the human presence is inconvenient. Video-based WSN is packed with the wireless transceiver, which is capable of transmitting video signals over the wireless sensor network. This network is applicable in real-time data delivery applications including health monitoring (in–hospital emergency and pre-hospital care), traffic monitoring (monitor and controls the traffic flow in major cities), surveillance and security measurements (track and locate the movements of the missing persons/human activities in the battlefield), etc. [2], [3].

A wireless multimedia transmission system is composed of a number of multimedia devices such as audio and video sensor that sense the scalar data and capture low-resolution videos and sent it to their multi-media processing hub or base station [4]. The hub used is for aggregating all the multimedia information from the sensor nodes. This aggregation is done by an algorithm, which is capable of reducing both volumes of data and dimension. Then the data is forwarded to the sink and storage devices. The storage hub performs information mining and feature extraction that recognize the essential characteristics of the video before sending to the user. The gateway is defined as a bridge for IP less and IP based network. The end users are found through their IP address and the result is transmitted in the WSMN.

Unlike other transmission systems, WSMN faces many challenges that affect the QoS and QoE performance include limited bandwidth, computation, storage capacity and energy usage [5]. Quality of Service (QoS) metric in Wireless Multimedia Sensor Network (WMSN) deals with set of service requirements to be met by the network at the time of packet transmission from source to destination. The QoS metrics (such as packet loss ratio and delay) deals with the utilization of all available resources in the network effectively while dealing with heterogeneous type nodes in the network. At the same time, Quality of Experience (QoE) metric such as PSNR analyzes the video quality over the wireless channels. Hence, both the metric plays a vital role in ensuring the quality driven video transmission in WMSN. The quality-driven data delivery applications in real time should improve both these metrics to provide a guaranteed transmission in WMSN. The network also faces several challenges such as packet loss, delay, and false routing during transmission while increasing the amount of data packet [6]. Besides, the proper use of nodes reduces the energy consumption, which increases the lifetime of the wireless sensor networks [7].

Due to the expeditious development in the video delivery, scalable video transmission is essential to support the variety of devices ranging from small cell phones to high display personal computer [8]. The scalable video coding (SVC) removes the parts of repeated data in the video sequence in order to adapt it to various terminal capabilities for many applications [9], [10], [11]. In this, there are three scalability types such as temporal (reduce frame rate), spatial (reduce the spatial resolution) and quality scalability (reduce the fidelity) for the effective bit rate reduction [12]. The low-resolution video streaming is encoded based on H.264 standard. The current video compression is based on the High-Efficiency Video Coding (HEVC/H.265) standard that supports the resolution up to 8 K UHD (8192 × 4320) resolution and provides less bit rate correlate to H.264 standard. Higher compression is needed for the videos at the higher resolution to reduce the repeated information of the data in the bits stream. This causes transmission delays and disturbances at the time of transmission. Thus, streaming of HD scalable video streaming over WSMN should be improved with an efficient video coding scheme and EC scheme, thereby reducing the packet loss and maintain the QoE even with the increasing capacity of the network. Scalable High-Efficiency Video Coding (SHVC) is the scalable extension of the high-efficiency video coding that compresses the numerous video sequences with different resolutions to a single bit stream. The proposed compression technique named SHIPVC considers the repeated inter-layer features (color, motion, and texture) between the frames and redundant features get eliminated to further reduce the bit rate of the video stream.

The powerful encoding and routing scheme will help to deliver the high-efficiency video content through the reliable paths. Routing with multi-path strategy delivers the video stream with available shortest path. The multi-path scheduling algorithm drops the packets with less priority due to network conditions [13] and at path based transmission [14]. Hence multi-path with best routing scheme is required to handle the heavy video traffic. With this, the intermediate node/link failure in the network further degrade the network performances. Thus, an alternate route should be generated to manage the failure within the network with maximum fault tolerance services.

For tackling the network impairments such as packet loss, false routing, and power failure in the receiver side, Error Concealment (EC) [15], [16] and Error Resilience (ER) [17] techniques can be used. However, ER makes the architecture little more complex and causes delays of packets but EC schemes allow higher compression and make the entire video into a packet. It uses the spatial-temporal information to estimate the number of packet loss and allows for re-transmission. In [18], a frame concealment based on dynamic texture extrapolation associated with the h.264 standard. Spatial error concealment (SEC) based concealment uses pixel-wise matching for losing the whole frame [19]. The hybrid concealment technique uses Set Partitioning in Hierarchical Trees (SPIHT) [20] to conceal the missing block. With proper handling of missing frames by an effective concealment method will enhance the QoE performance in video transmission.

Existing studies focus only on providing quality of services, delay maintenance with a limited number of transmitting nodes and does not consider the solution to disguise all the effects while packet drop occurs for more data generating nodes. To our knowledge, there is no existing solution for transmitting high definition videos with an optimization problem over WMSNs and maintaining proper delay, fault tolerance, and less distortion during video transmission. To overcome all the effects by the existing standard, we propose an effective compression associated with multipath routing adapted with optimization problem at the link for HD video delivery in WMSNs. The proper error concealment of the missing frame allows to maintain the acceptable quality of video at the receiving end.

The contributions to this paper include:

  • To perform inter-layer predictions between the frames with texture, and color, motion compression, we present a technique named SHIPVC to eliminate the redundancies in the higher frames, which transmit the high-resolution video over WMSNs.

  • Efficient multipath routing to improve QoS with the minimum distance transmission over the network.

  • An optimization problem is solved by our multipath genetic algorithm in consideration with maximizing fault tolerance with minimum communication delay during transmission.

  • The motion vector extrapolation (MVE) based concealment technique is used to maintain the video quality, which conceals the missing video frames at the receiver side.

The rest of this paper is organized as: in Section 2, we shortly make a review of the existing works. In Section 3, our proposed methodology is explained in three sections: processing, routing, and concealment of frames. In Sections 4 and 5, the experimental analysis is made for the proposed method and made a small discussion about it. Finally, in Section 6, we conclude the work based on the obtained results.

Section snippets

Related work

The existing studies concentrate on single layer improvement without improving the network throughput performance. The previous H.264 compression standard cannot be adapted for multiple applications with variable network conditions. Hence, the high-efficiency video input needs more compression with efficient transmission at varying requirements of the receivers.

Chang et al. [21] proposed the high-efficiency channel access mechanism Multi Polling Controlled Access (MPCA) for H.264 video at the

Predictive compression with fault tolerant embedding based multi-path routing and concealment for quality video transmission

The proposed video transmission over WMSNs architecture operates based on the following phases: processing the video, multi-path routing with fault-tolerant embedding and concealment technique. Fig. 1 shows the stages of video stream transmission over WMSNs. Initially, the transmission starts with the encoding of a video stream using a novel compression method to reduce the bit stream with scalable inter-layer processing coding. The compression of the high definition video frames containing

Experimental result and analysis

In this section, we evaluate the performance of our proposed framework. The network topology is based on the IEEE.802.11e or 802.11e standard, which offers users with high-speed internet access for delay-sensitive applications. This standard is mostly suitable for the subscribers accessing Wi-Fi with the applications include Voice over IP (VoIP), video streaming applications. Hence, we choose 802.11e that provides a greater need for QoS in controlling the data transmitted over the network. The

Discussion

Video transmission over WMSNs faces several challenges such as bandwidth limitation, packet drop, channel error problem, false routing, false decoding, and causes quality degradation at the receiver. Under this scenario, a proper data delivery scheme should be needed with an effective quality enhancement to the user. Hence, at each stage of transmission, the data packet should be maintained properly to obtain a better performance. The proposed data delivery scheme associated with fault-tolerant

Conclusion

In this research work, we solve the problems of video transmission in WMSNs and propose a solution to overcome all the previous effects. The traditional video transmission scheme operated based on limited nodes on the network without maintaining the fault tolerant optimization and network impairment problems happened over the network system. The powerful compression is required to handle a large amount of input data without out degrading the quality of services. On the other hand, QoE has to be

Dr. Praveen Kumar K (Kodoth) was born in Kasaragod, Kerala, India in 1974. He received the Bachelor's Degree in Technology from University of Calicut, India in 1997. Then he obtained Master's Degree in Technology from National Institute of Technology, Karnataka, in 2005, and the Ph.D. degree in Computer Engineering majoring in Wireless Sensor Networks from the Anna University, Chennai, India, 2014. Currently he is a Professor in the Department of Computer Science & Engineering in LBS College of

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  • Dr. Praveen Kumar K (Kodoth) was born in Kasaragod, Kerala, India in 1974. He received the Bachelor's Degree in Technology from University of Calicut, India in 1997. Then he obtained Master's Degree in Technology from National Institute of Technology, Karnataka, in 2005, and the Ph.D. degree in Computer Engineering majoring in Wireless Sensor Networks from the Anna University, Chennai, India, 2014. Currently he is a Professor in the Department of Computer Science & Engineering in LBS College of Engineering, Kasaragod, Kerala. His research interests are in Machine Learning, Energy aware routing in wireless sensor networks, heterogeneous wireless networks and IoT.

    Dr. Govindaraj E (Edechena) was born in Kalpetta,Wayanad,India in 1974. Obtained his Bachelor's degree in Computer Science and Engineering from Calicut University, India. Then he obtained his Master's degree in Computer Science and Engineering and Ph.D. in Computer Science and Engineering majoring in Wireless Mesh Network from Anna University Chennai India. Currently, he is an Associate Professor in the Department of Computer Science & Engineering in MES College of Engineering, Kuttippuram, Kerala, India. His specializations include Bluetooth network, networking, Wireless Sensor Network and Cognitive Radio Network. His current research interests are Fuzzy Decision Model for Multipath Routing in Wireless Multimedia Sensor Networks, and Non uniform node distribution.

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