Compressed Sensing based Low-Power Multi-View Video Coding and Transmission in Wireless Multi-Path Multi-Hop Networks

Wireless Multimedia Sensor Network (WMSN) is increasingly being deployed for surveillance, monitoring and Internet-of-Things (IoT) sensing applications where a set of cameras capture and compress local images and then transmit the data to a remote controller. Such captured local images may also be compressed in a multi-view fashion to reduce the redundancy among overlapping views. In this paper, we present a novel paradigm for compressed-sensing-enabled multi-view coding and streaming in WMSN. We first propose a new encoding and decoding architecture for multi-view video systems based on Compressed Sensing (CS) principles, composed of cooperative sparsity-aware block-level rate-adaptive encoders, feedback channels and independent decoders. The proposed architecture leverages the properties of CS to overcome many limitations of traditional encoding techniques, specifically massive storage requirements and high computational complexity. Then, we present a modeling framework that exploits the aforementioned coding architecture. The proposed mathematical problem minimizes the power consumption by jointly determining the encoding rate and multi-path rate allocation subject to distortion and energy constraints. Extensive performance evaluation results show that the proposed framework is able to transmit multi-view streams with guaranteed video quality at lower power consumption

Reliable multimedia transmission over wireless sensor network

Nowadays, video streaming application is widely used in wired as well as wireless environment. Extending this application into Wireless Sensor Networks (WSN) for IEEE 802.15.4 network has attracted lots of attention in the research community. Reliable data transmission is one of the most important requirements in WSN especially for multimedia application. Moreover, multimedia application requires high bandwidth and consumes large memory size in order to send video data that requires small end-to-end (ETE) delay. To overcome this problem, rate control serves as an important technique to control the bit rate of encoded video for transmission over a channel of limited bandwidth and low data rate which is 250kbps with small Maximum Transmission Unit (MTU) size of 127 bytes. Therefore, a rate control model called enhanced Video Motion Classification based (e-ViMoC) model using an optimal combination of parameter setting is proposed in this thesis. Another challenging task to maintain the video quality is the design of an enhanced transport protocol. Standard transport protocols cannot be directly applied in WSN specifically, but some modifications are required. Therefore, to achieve high reliability of video transmission, the advantages of User Datagram Protocol (UDP) features are applied to the proposed transport protocol called Lightweight Reliable Transport Protocol (LRTP) to tailor to the low data rate requirement of WSN. Besides, priority queue scheme is adopted to reduce the end-to-end delay while maintaining the reliability and energy efficiency. Evalvid simulation tool and exhaustive search method are used to determine optimal combination of quantization scale (q), frame rate (r) and Group of Picture (GOP) size (l) values to control the bit rate at the video encoder. The model of e-ViMoC is verified both with simulation and experimental work. The proposed transport protocol has been successfully studied and verified through simulation using Network Simulator 2 (NS-2). From the simulation results, the proposed e-ViMoC encoded video enhances the Packet Delivery Ratio (PDR) by 5.14%, reduces the energy consumed by 16.37%, improves the Peak Signal to Noise Ratio (PSNR) by 4.37% and reduces the ETE delay by 23.69% in average, compared to non-optimized encoded video. The tested experiment experiences slightly different result where the PDR is 6% lower than simulation results. Meanwhile, the combination of e-ViMoC and LRTP outperforms the standard transport protocol by average improvement of 142.9% for PDR, average reduction of 8.87% for energy consumption, average improvement of 4.1% for PSNR, and average reduction of 19.38% for ETE delay. Thus, the simulation results show that the combination of proposed e-ViMoC and LRTP provides better reliability performance in terms of the PDR while simultaneously improves the energy efficiency, the video quality and ETE delay

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

State-of-the-Art Sensors Technology in Spain 2015: Volume 1

This book provides a comprehensive overview of state-of-the-art sensors technology in specific leading areas. Industrial researchers, engineers and professionals can find information on the most advanced technologies and developments, together with data processing. Further research covers specific devices and technologies that capture and distribute data to be processed by applying dedicated techniques or procedures, which is where sensors play the most important role. The book provides insights and solutions for different problems covering a broad spectrum of possibilities, thanks to a set of applications and solutions based on sensory technologies. Topics include: • Signal analysis for spectral power • 3D precise measurements • Electromagnetic propagation • Drugs detection • e-health environments based on social sensor networks • Robots in wireless environments, navigation, teleoperation, object grasping, demining • Wireless sensor networks • Industrial IoT • Insights in smart cities • Voice recognition • FPGA interfaces • Flight mill device for measurements on insects • Optical systems: UV, LEDs, lasers, fiber optics • Machine vision • Power dissipation • Liquid level in fuel tanks • Parabolic solar tracker • Force sensors • Control for a twin roto

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks