Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks

Wireless Multimedia Sensor Network is a new Sensor Network based on the traditional Wireless Sensor Network with the introduction of Multimedia information sensing function. The paper aims to solve the problems of the energy constraint in the Wireless Multimedia Sensor Network and the data of information encoded in the image has the characteristic of big size and high redundancy. The research can be conducted in the following two aspects. The first is to find a fast and accurate image registration algorithm which can be used to reduce the total amount of the extracted feature point and improve the matching precision. The second is to provide an image fusion approach which can be applied in the Wireless Multimedia Sensor Network. With this approach, the detailed features of the image can be highlighted, and the image clarity can be improved. The research in this paper can lay the theoretical foundation for research of image fusion in Wireless Multimedia Sensor Networks, and promote the development of wireless multimedia sensor network as an emerging cross-disciplinary science. The research are of important economic significance and social value in the informatization and networking of the fields of military, transportation, agriculture and etc.

In the framework of block Compressed Sensing (CS), the reconstruction algorithm based on the Smoothed Projected Landweber (SPL) iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA) to perform the adaptive hard-thresholding shrinkage. However, during learning the PCA matrix, it affects the reconstruction performance of Landweber iteration to neglect the stationary local structural characteristic of image. To solve the above problem, this paper firstly uses the Granular Computing (GrC) to decompose an image into several granules depending on the structural features of patches. Then, we perform the PCA to learn the sparse representation basis corresponding to each granule. Finally, the hard-thresholding shrinkage is employed to remove the noises in patches. The patches in granule have the stationary local structural characteristic, so that our method can effectively improve the performance of hard-thresholding shrinkage. Experimental results indicate that the reconstructed image by the proposed algorithm has better objective quality when compared with several traditional ones. The edge and texture details in the reconstructed image are better preserved, which guarantees the better visual quality. Besides, our method has still a low computational complexity of reconstruction.

In the networking research community, Wireless Sensor Networks (WSN) has achieved considerable significance in the past years and it can be used in extensive variety of domains. In recent years, the tremendous growth of WSN does not meet all the necessities of environmental monitoring. Wireless Multimedia Sensor Network (WMSN) is required to fulfill the requirements of environment monitoring. In this paper, WMSN is used to monitor the agriculture soil environment. In order to ensure optimal use of the sensor nodes in WMSN and accurate access to the collected data,the routing protocols with both energy efficiency and quality of service ( QoS) properties are necessary for the transmission of photo, video and scalar data.This paper proposes a priority aware energy efficient QoS based data transmission for agriculture soil environment and also detects the pest. It utilizes the available bandwidth and data rate in the best way and in order to be more energy efficient during data transmission.For performance analysis, the proposed system is simulated using Java and the results of the experiments suggest that the proposed algorithm is more efficient compared to other methods in terms of delay and energy consumption.

Energy efficiency of MAC protocols in low data rate wireless multimedia sensor networks: A comparative study

In recent years, wireless multimedia sensor networks (WMSNs) attract great attention. Generally, WMSNs node is equipped with only one single camera for visual observation. In order to achieve wider view-angle, existing solutions, such as node rotation and view-angle adjustment, always cause high cost, high energy consumption and non-real-time response. In this paper, we propose a feasible solution by utilizing four wide-angle cameras to form omni-directional visual sensing for WMSNs node. The omni-directional probability sensing model is analyzed and defined. With DSP processor, we carry out the system architecture in details. Energy consumption is analyzed by comparing with rotatable camera. To our best knowledge, it is the first time that omni-directional vision with multiple cameras is introduced for WMSNs node to monitor the surrounding environment in real time. Experiment results show that the proposed omni-directional sensing can achieve better performance on deployment and energy cost than traditional WMSNs node.

Transmission of multimedia data over wireless multimedia sensor networks (WMSNs) is a challenging task and requires an effective design for the transport layer protocols to meet both the resource‐constrained WMSN and the requirements of multimedia streaming. The standard transport layer protocols (eg, UDP, TCP, SCTP, and DCCP) have been shown inefficient to transport multimedia data over WMSN without modification in the design of end‐to‐end (ETE) reliability and the congestion control mechanisms. This paper proposed a lightweight reliability mechanism for datagram congestion control protocol (LW‐DCCP) over WMSNs. The lightweight reliability mechanism consists of caching and retransmission algorithms that consider the resource‐constrained WMSNs and the requirements of video streaming over WMSN. Moreover, this paper presents an important modification to TCP‐friendly rate control congestion control mechanism that calculates the loss interval based on intracoded frame sending time. The LW‐DCCP has been evaluated through comprehensive simulation experiments and compared with baseline transport protocols using the 2 frameworks (Eval‐SCTP and Eval‐DCCP) that we developed in NS‐2 environment. The experimental results show that LW‐DCCP ensures effective congestion control and ETE reliability for video transmission over WMSN. In addition, LW‐DCCP experiences better performance in terms of energy consumption, ETE delay, jitter delay, frame delivery ratio, frame peak signal‐to‐noise ratio, and visual quality of the received video as compared to the baseline transport layer protocols.

In wireless multimedia sensor networks (WMSN), many video sensors distributed in the same scene acquire large quantities of data. However, sensor devices are constrained in terms of power, processing, and bandwidth capacity. This paper presents a new framework of distributed video processing system for WMSN that takes advantage of distributed compressive sensing (DCS) theory. In the encoder analysis the residual joint sparse model. In the decoder, efficient reconstruction is implemented using the GPSR algorithm to recover images. Side information is generated using the temporal correlation between adjacent frames from a single view and the spatial correlation of the two nearest views. Experimental results show that the method presented achieves 1-3dB improvement in PSNR compared to the coding method of single-view videos.

One of the remarkable challenges in the area of Wireless Sensor Networks (WSNs) is how to route the collected data and transfer them in the nodes. Due to the high rate of packet loss, guaranteeing reliable and efficient packet transfer and delivery is considered to be one of the hot issues in the area of WSNs. Indeed, due to energy limitation of nodes in WSNs, reliability and energy are regarded as critical parameters in these networks. In this paper, a method has been proposed for optimizing the parameters of reliability and energy consumption in multimedia WSNs. In the proposed protocol, Increasing the Delivery Ratio with Network Coding (IDRNC) a network coding mechanism has been used for transmitting data which enhances the reliability of the network. Furthermore, reducing the number of transmissions and receptions in network nodes results in the reduction of energy consumption. In the proposed protocol, the transmitted packets are first coded and transmitted to the sink through the shortest route. In the middle of the route, in case packets are lost, median nodes can detect and recover the lost packet through the coded packet. The simulation results indicated that the method proposed in this study operates better than the LIEMRO method with respect to the following features: system efficiency, average remaining energy of the network, the number of lost packets and reliability. Keywords: Multipath Routing, Network Coding, Reliability, Wireless Multimedia Sensor Networks (WMSNs)

Applying multimedia to Wireless Sensor Network (WSN) adds more challenges due to WSN resource constraints and the strict Quality of Service (QoS) requirements for multimedia transmission. Different multimedia applications may have different QoS requirements, so routing protocols designed for Wireless Multimedia Sensor Network (WMSN) should be conversant of these requirements and challenges in order to ensure the efficient use of resources to transfer multimedia packets in an utmost manner. The majority of solutions proposed for WMSN depends on traditional layered based mechanisms which are inefficient for multimedia transmission. In this paper we propose a cross-layer Ant based Routing Protocol for WMSN (CARPM) by using modified ant colony optimization (ACO) technique to enhance the routing efficiency. The proposed protocol uses an improved ACO to search for the best path that are satisfied with the multimedia traffic requirements. While making best decision the weightage is given to energy consumption, and queuing delay. The proposed cross layer scheme works between the routing, MAC, and physical layers. Since, the remaining power and timestamp metrics are exchanged from physical layer to network layer. Dynamics duty cycle assignment is proposed at MAC layer which changes according to traffic rate. The presented algorithm is simulated using NS2 and is proven to satisfy its goals through a series of simulations.

Compressed sensing (CS) has emerged as a promising technique to jointly sense and compress sparse signals. One of the most promising applications of CS is compressive imaging. Leveraging the fact that images can be represented as approximately sparse signals in a transformed domain, images can be compressed and sampled simultaneously using low-complexity linear operations. Recently, these techniques have been extended beyond imaging to encode video. Much of the compression in traditional video encoding comes from using motion vectors to take advantage of the temporal correlation between adjacent frames. However, calculating motion vectors is a processing-intensive operation that causes significant power consumption. Therefore, any technique appropriate for resource constrained video sensors must exploit temporal correlation through low-complexity operations. In this tutorial, we first briefly discuss challenges involved in the transmission of video over a wireless multimedia sensor network (WMSN). We then discuss the different techniques available for applying CS encoding first to images, and then to videos for error-resilient transmission in lossy channels. Existing solutions are examined, and compared in terms of applicability to wireless multimedia sensor networks (WMSNs). Finally, open issues are discussed and future research trends are outlined.

Improvements in nanotechnology have introduced contemporary sensory devices that are capable of gathering multimedia data in form of images, audio and video. Wireless multimedia sensor networks handles such type of heterogeneous traffic. Since these networks are an emergent of wireless sensor networks, they inherit constraints that exist in these traditional networks. This paper is a survey of characteristics and requirements of wireless multimedia sensor networks and approaches to mitigating existing challenges in these networks. Further presents a review of recent research on multipath routing protocols and multi-channel media access protocols that offer quality of service assurances in handling multimedia data. The survey shows that there still exist bottlenecks in current routing solutions when applied to wireless multimedia sensor networks due to the nature of traffic involved as well as inherent characteristics, requirements and constraints. The findings are useful in the discovery of solutions to the challenges and issues. The authors further suggest approaches and plausible solutions to the problems in order to assist in the development of protocols that achieve quality of service in wireless multimedia sensor networks.

New security approach in real-time wireless multimedia sensor networks

Multimedia applications are routed from source nodes via neighboring nodes to a sink in Wireless Multimedia Sensor Networks (WMSNs). However, the existing routing protocols in the WMSNs do not fulfill the quality of service (QoS) constraint yet for multimedia transmission. The WMSNs have specific characteristics such as multi-hop way, limited node capability and varying bandwidth, which can affect the quality of service of multimedia applications during the routing process. The best quality of service (QoS) is required by the multimedia applications consisting of high throughput, low end-to-end delay and low packet drop rate. A routing optimization based on the cross-layer design is proposed for multimedia transmission in the WMSNs. The cross-layer design utilizes H.264/Scalable Video Coding (SVC) and IEEE 802.11e Enhanced Distributed Channel Access (EDCA) and has been implemented in Network Simulator 2 (NS2) simulation. The NS2 simulation indicates that the H.264/SVC video application has an average delay of 0.02 sec. Thus, the routing optimization has accomplished to deliver multimedia application successfully via Wireless Multimedia Sensor Network (WMSN).

Wireless Sensor Network (WSN) has limited resources such as energy, computation and transmission capacity. These resources are not sufficient for transmitting large amount of data collected by the sensor nodes. Wireless Multimedia Sensor Network (WMSN) generates large amount of data that requires more energy and transmission capacity as compared to scalar data. So it is desired to perform in-network data compression in WMSN. In this paper the authors have used Principal Component Analysis (PCA) technique for data compression. PCA can be efficiently used in wireless multimedia sensor network to reduce the energy consumption, reduce the network load and prolong the network lifetime. Simulation results show that PCA based compression conserves energy of sensor nodes and prolongs the lifetime of WMSN.

In recent years, there has been intense research and considerable progress in solving numerous wireless sensor networking challenges. However, the key problem of enabling real-time quality-aware multimedia transmission over wireless sensor networks is largely unexplored. The large amount of data generated by most multimedia applications (compared to traditional scalar sensor networks), along with the higher QoS requirements make it difficult to meet the low energy use requirements of practical sensor networks. We explore the use of compressed sensing (aka “compressive sampling”) to reduce the energy required to encode and transmit high quality video in a severely resource-constrained environment. In this chapter, we will examine some of the major challenges of wireless multimedia sensor network (WMSN) implementation. Specifically, we examine what it would take to develop a WMSN that has similar performance (and restrictions) as a traditional scalar wireless sensor network (WSN). We then examine how we can use the new paradigm of compressed sensing (CS) to solve many of these problems.KeywordsSensor NodeWireless Sensor NetworkDiscrete Cosine TransformVideo QualityCompress SenseThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.