Wireless Video Sensor Networks Research Articles

Cooperative Space-Time Block Codes for Wireless Video Sensor Networks

Wireless video sensor networks (WVSNs) are gaining popularity due to numerous potential applications such as video surveillance, environmental and habitat monitoring, and so on. Considering large-scale WVSNs, in which the sink node is not within the range of all other nodes, a multi-hop operation is desired. This paper proposes a novel cooperative system that uses space time-block codes to enhance the performance of multi-hop wireless video sensor networks. The proposed scheme is designed to deal with large-scale WVSNs, by adapting the cluster size and extending the cooperation between the cluster-heads. The performance comparison between the proposed system and a non-cooperative scheme is presented based on network lifetime for varying propagation scenarios, number of camera nodes, and on the quality of transmitted videos in a WVSN. Simulation results show an improvement in performance for the proposed system.

On the use of passive clustering in wireless video sensor networks

Wireless Video Sensor Networks are foreseen to be of a paramount importance in realising a wide spectrum of applications, mainly surveillance, target tracking and environment monitoring. In this paper, we propose a combination of an improved clustering algorithm and Directed Diffusion (DD), a well–known data–centric routing paradigm in sensor networks. On one hand, clustering allows to save bandwidth required by rich and intensive data of video applications. On the other hand, the network lifetime is prolonged by implementing an energy–aware load–balancing feature through modifying Passive Clustering (PC) rules for building/maintaining its topology. We performed extensive computer simulations and show in this paper that our solution outperforms original DD as well as when it is combined with PC with energy considerations but without load balancing.

Coverage and activity management of wireless video sensor networks for surveillance applications

Wireless Video Sensor Networks consist in nodes with miniaturised cameras. Unlike omni-directional sensors, the sensing region of a video node is limited to the field of view of its camera. This paper addresses the issues of building an intrusion detection system based on these video sensors and presents two contributions. The first contribution presents the performance of various cover set construction strategies for determining for each sensor its level of redundancy. Simulation results showed the performance of the strategies in terms of percentage of coverage, network lifetime, intrusion stealth time and number of intrusion detection. The second contribution addresses efficient activity management of nodes for mission-critical surveillance applications. The proposed approach dynamically determines a sensor's frame capture rate. We showed that varying the criticality level dynamically during the network operation increases the network lifetime while maintaining a high level of service. With reinforcement behaviour the network lifetime is further increased.

Distributed Video Coding: an overview of basics, research issues and solutions

Distributed Video Coding (DVC) is an emerging eld that offers a brand-new paradigm for answering challenging questions in video coding applications. The unique potentials of DVC lie in its particular structure, targeting low encoding complexity and error robustness. DVC shows good prospects especially in wireless video sensor network, video monitoring, mobile camera, satellitic video communication and the other energy supply limited video applications. There has been amount of activities both in research and industry. Following the evolving stages, this paper provides an overview of DVC, including the theoretical foundation: Slepian-Wolf Theorem and Wyner-Ziv Theorem, the framework foundation: Distributed Source Coding (DSC) and the relation between DSC and DVC, and unique technologies comparison to conventional compressed method, including side information, channel coding, joint decoding and motion estimation, which highlight critical research issues. Additionally, ve representative encoder are introduced as implementation aspects. Finally, several active research areas in the state of the art are reviewed with open challenging issues.

Video Compression Schemes Using Edge Feature on Wireless Video Sensor Networks

This paper puts forward a low‐complexity video compression algorithm that uses the edges of objects in the frames to estimate and compensate for motion. Based on the proposed algorithm, two schemes that balance energy consumption among nodes in a cluster on a wireless video sensor network (WVSN) are proposed. In these schemes, we divide the compression process into several small processing components, which are then distributed to multiple nodes along a path from a source node to a cluster head in a cluster. We conduct extensive computational simulations to examine the truth of our method and find that the proposed schemes not only balance energy consumption of sensor nodes by sharing of the processing tasks but also improve the quality of decoding video by using edges of objects in the frames.

Optimal H.264 Scalable Video Scheduling Policies for 3G/4G Wireless Cellular and Video Sensor Networks

We consider the problem of optimal H.264 scalable video scheduling, with an objective of maximizing the end-user video quality while ensuring fairness in 3G/4G broadband wireless networks and video sensor networks. We propose a novel framework to characterize the video quality-based utility of the H.264 temporal and quality scalable video layers. Subsequently, we formulate the scalable video scheduling framework as a Markov decision process (MDP) for long-term average video utility maximization and derive the optimal index based-scalable video scheduling policies ISVP and ISVPF towards video quality maximization. Further, we extend this framework to multiuser and multisubchannel scenario of 4G wireless networks. In this context, we propose two novel schemes for long-term streaming video quality performance optimization based on maximum weight bipartite and greedy matching paradigms. Simulation results demonstrate that the proposed algorithms achieve superior end-user video experience compared to competing scheduling policies such as Proportional Fairness (PF), Linear Index Policy (LIP), Rate Starvation Age policy (RSA), and Quality Proportional Fair Policy (QPF).

Network lifetime optimization for wireless video sensor networks with network coding/ARQ hybrid adaptive error-control scheme

This paper addresses the performance optimization of network lifetime and resource allocation for wireless video sensor networks. Network flow control and video encoding bit rate are jointly optimized, aiming to maximize the network lifetime at a given power budget and video quality requirement. We develop a generalized power consumption model for video sensors, in which video encoding, data communication and error-control behavior are completely considered. To combat packet loss over wireless channels, a hybrid error-control scheme integrating network coding and ARQ protocol is introduced. It adaptively adjusts the number of redundant coded packets according to ARQ feedbacks with a fixed code structure and decoding algorithm. Through the Lagrange dual and subgradient approach, a fully decentralized algorithm is proposed to solve the target convex problem. Finally, simulation results validate the convergence and performance of the proposed algorithm in a large-scale random topology as well as in a small static network.

Lifetime and Distortion Optimization With Joint Source/Channel Rate Adaptation and Network Coding-Based Error Control in Wireless Video Sensor Networks

In this paper, we study joint performance optimization on network lifetime and video distortion for an energy-constrained wireless video sensor network (WVSN). To seek an appropriate tradeoff between maximum network lifetime and minimum video distortion, a framework for joint source/channel rate adaptation is proposed, where the video encoding rate, link rate, and power consumption are jointly considered, formulating a weighted convex optimization problem. In the context of lossy wireless channels, an efficient error control scheme that couples network coding and multipath routing is explored. Moreover, an integrated power consumption model, including power dissipation on video compression, error control, and data communication, is specifically developed for the video sensor node. By primal decomposition, the original problem is decomposed into a two-level optimization procedure, with the high-level procedure for source adaptation (source rate optimization) and the low-level procedure for channel adaptation (network resource allocation). Finally, a fully decentralized iterative algorithm is developed to resolve the target optimization problem. Extensive simulation results evaluate the convergence performance of the proposed algorithm and demonstrate the best tradeoff performance.

Low delay distributed video coding with refined side information

Distributed video coding (DVC) is a new video coding paradigm based upon two fundamental theoretical results: the Slepian–Wolf and Wyner–Ziv theorems. Among other benefits, this new coding paradigm may allow a flexible complexity allocation between the encoder and the decoder. Several DVC codecs have been developed over the years addressing the specific requirements of emerging applications such as wireless video surveillance and sensor networks. While state-of-the-art DVC codecs, such as the DISCOVER DVC codec, have shown promising RD performance, most DVC codecs in the literature do not consider low delay requirements which are relevant for some of the addressed applications. In this context, the main objective and novelty of this paper is to propose an efficient, low delay and fully practical DVC codec based on the Stanford DVC architecture adopting a side information iterative refinement approach. The obtained performance results show that the developed DVC solution fulfils the objectives regarding relevant benchmarks, notably due to the novel side information creation and correlation noise modeling tools integrated in a side information iterative refinement framework.

Wireless Video Transmission Scheme Based on Virtual MIMO and Network Coding Technology

In this paper, we propose a novel communication scheme for real-time video transmission over wireless sensor network based on the virtual multiple-input-multiple-output (MIMO) and the network coding technology. According to the distinctive characteristic of real-time video data, the video transmission distortion, energy consumption and the end-to-end delay performance are analyzed with virtual MIMO transmission manner for our approach. The greedy algorithm is used to optimize the video distortion performance with the total energy and end-to-end delay constraints. For multiple video source application in wireless video sensor network, we propose a virtual MIMO with network coding technique scheme to improve the network throughput performance and reduce end-to-end delay effectively. From the simulation results, our approach can get better distortion performance than the traditional manner when the intra cluster distance is set to be appropriate relative to the inter cluster distance.

Cooperative STBC with fuzzy election applied to surveillance wireless video sensor networks

Wireless video sensor networks (WVSN) have been envisioned for a wide range of important applications such as video surveillance, emergency response, environmental and habitat monitoring. Transmitting video over WVSN requires large bandwidth as well as lifetime of sensor nodes long enough to fulfill the application requirements. This paper proposes an integrated system for WVSN (mainly used for surveillance) that combines the use of adaptive cooperative diversity and fuzzy logic. The cooperative spacetime block codes (STBC) are used to achieve full diversity with a simple maximum-likelihood decoding algorithm in order to enhance the performance of the considered WVSN. The performance comparison between the proposed system and a non-cooperative scheme is presented based on network lifetime, quality of transmitted videos, and required number of retransmissions under varying propagation scenarios in a WVSN. Simulation results show better performance for the proposed system, presenting greater lifetime, higher peak signal-to-noise ratio (PSNR) values of transmitted videos and lower propagation delay.

Towards Efficient Wireless Video Sensor Networks: A Survey of Existing Node Architectures and Proposal for A Flexi-WVSNP Design

The video capture, processing, and communication in wireless video sensor networks critically depend on the resources of the nodes forming the sensor networks. We provide a survey of wireless video sensor node platforms (WVSNPs). From a comprehensive literature review, we first select the node architectures that meet basic requirements for a WVSNP. We then introduce a classification of WVSNPs into general purpose architectures, heavily coupled architectures, and externally dependent architectures. We thoroughly survey and contrast the existing WVSNPs within this classification framework. Based on the insights from our survey we develop a novel Flexi-WVSNP design. The Flexi-WVSNP design includes dual-radio communication, a middleware for sensor operation and communication control, as well as a cohesive hardware and software design.

A Wireless Video Transmission Scheme Based on MAC-independent Opportunistic Routing & Encoding Protocol

It is a tremendous challenge to transmit real-time video streams over wireless sensor network because of the poor wireless communication conditions and the high requirements of video transmission. The opportunistic routing protocol can take advantage of the broadcast nature of wireless communication and can improve transfer throughput significantly. But the bigger size of transmission unit also increases the end-to-end delay at the same time. In order to overcome this problem and improve the real-time video transmission quality in wireless video sensor network, we propose a source adaptive frame discard algorithm for MAC-independent Opportunistic Routing & Encoding (MORE) Protocol in this paper. In our approach, the historical transmission delay is recorded to estimate current network transmission rate. Based on the video deadline, frames predicted to be delayed are discarded adaptively in the source node to get better overall video quality. In some practice application scenarios, there are usually need to deliver multiple video streams over multi-hop wireless network. It can’t work effectively with the originally MORE protocol in such scenarios. Furthermore, we modify the MORE protocol and design an adaptive scheme to support multiple video streams over multi-hop wireless video sensor network in this paper. The simulation results show that our algorithm can reduce frame loss rate and improve video quality significantly.

Cross layer load balanced forwarding schemes for video sensor networks

In this paper, we propose two cross layer geographic forwarding schemes which address congestion in wireless video sensor networks (VSN) to provide reliable video delivery. The first scheme Load Balanced Reliable Forwarding (LBRF) introduces the notion of local load balancing where a sensor dynamically determines the next hop among the alternative neighbors providing positive advancement towards the sink by considering the balance of their buffer occupancy levels at the time of delivery. LBRF utilizes a modified version of SMAC where the packet structure as well as the operation of SMAC is modified for the accurate monitoring of the buffer occupancy conditions of the neighbors. The second scheme Directional Load Balanced Spreading (DLBS) combines local and direction-based (spatial) load balancing approaches to provide more reliable and faster video delivery by benefiting from the advantages of both approaches. The performance of the forwarding schemes are compared using simulation with two geographic routing schemes where one applies no load balancing and the other applies spatial load balancing. The results show that both LBRF and DLBS provide more reliable video delivery as compared to other schemes, whereas DLBS is more reliable and faster as compared to LBRF. In addition, DLBS provides more energy efficient video delivery in terms of energy expenditure per successfully delivered frame to the sink as compared to LBRF and the other two schemes.

Research on tasks schedule and data transmission of video sensor networks based on intelligent agents and intelligent algorithms

As a novel application technology, wireless video sensor networks become the current research focus, especially on target tracking and surveillance scenario. Based on multiple agents' technique, this article introduces a series of intelligent algorithms such as simulated annealing algorithm (SA), genetic algorithm (GA), and ant colony optimization algorithm (ACO) or their mixed algorithms, to resolve the optimization of tasks schedule and data transmission. This article analyzes the performance of abovementioned algorithms and verifies their feasibility associated with agents. The simulations demonstrates that the mixed algorithms based on SA and GA obtain the optimal solution to tasks schedule, and those combined with SA-ACO show advantages on multimedia sensor networks routing optimization.

Wireless video sensor networks for sparse, resource-constrained, multi-robot teams

Small-size robots provide access and maneuverability in the tight confines of highly rubbled and uncertain environments such as those encountered in Urban Search and Rescue (USAR). Small size also provides easy portability and deployability and the potential for redundancy through multi-robot teaming. Unfortunately, small size does not diminish the data demands of these applications, such as high-resolution imagery and other forms of high bandwidth data. Furthermore, achieving redundancy in tight environments requires wireless operation to avoid the entanglement of tethers, but wireless communication links have proven unreliable in such environments. The net effect of this is a set of robust networking requirements that include high bandwidth, low latency, and low power with multi-hop routing in a sparse and highly volatile network configuration, which has been collectively difficult to achieve. Our metric for benchmarking these requirements is a stream of uncompressed 320 × 240, 24-bit color images updated at 1 frame per second (roughly 1.8 Mbps - image compression is not the focus of this research as it only serves to increase the possible resolution or frame rate). No existing ad hoc wireless sensor network approaches have been able to achieve these requirements. Wi-Fi requires high power and size and does not have the latency, while Zig-bee does not have the bandwidth. Instead, this work focuses on augmenting the Bluetooth protocol, which is master/slave based, with a hybrid, multi-hop routing protocol. Bluetooth has the desired low power and high bandwidth characteristics, but lacks multi-hop routing and rapid recovery. In this paper, a hybrid routing protocol for ad hoc multi-robot networking is described that features: (1) high-bandwidth, (2) low power, and (3) low latency of data traffic for sparse, highly volatile networks—exactly what is required for large teams of highly distributed, small-scale robots. Furthermore, this paper compares simulations and robot implementations of different routing protocols over Bluetooth sensor networks and demonstrates the viability of our protocol as a wireless network solution for multi-robot teams characterized by high mobility in difficult RF environments. To the best of our knowledge, the work presented in this paper is the first attempt at comparison of different routing protocols for real robots with physical experiments over Bluetooth sensor networks.

A Limited Resources-Based Approach to Coding for Wireless Video Sensor Networks

Coding for the wireless video sensor networks should be a different issue from the coding for video telephony applications. There are two special features observed in the video sensor networks, limited resources, and low fidelity. Due to these features, coding for this network application requires a new perspective. It is a direction for coding to be of simple structure and not for the entertainment purpose but sufficient for the basic sensing needs. Our coding method is accordingly developed as follows: motion compensation followed by a new idea of shape compensation to replace the conventional residue discrete cosine transform coding. More specifically, our binary images are coded by the motion vectors and the class of morphological filters to achieve a bit rate below 10 kp/s. The resources (bandwidth, power, and hardware) are thus altogether significantly saved. This limited resources approach is the first time particularly investigated for the wireless sensor networks.

On Prolonging the Lifetime for Wireless Video Sensor Networks

This paper investigates strategies for prolonging the system lifetime for wireless video sensor networks, by adopting a mobile sink and solar-powered video sensors. Issues of tracking moving objects in wireless video sensor networks are studied, and the effectiveness of adopting a mobile sink is evaluated. This paper applies a power-rate-distortion analysis framework, which provides a theoretical fundamental to quantify various properties of wireless video sensor networks. The performance of wireless video sensor networks is evaluated with a mobile sink versus a static sink, under different cluster sizes and number of sensors. Comparisons of network lifetime, tracking error, video distortion, are also covered in this paper. In addition, this paper also evaluates the performance of solar-powered video sensors under an unequal layered clustering topology.

A Dynamic Programming Approach for QoS-Aware Power Management in Wireless Video Sensor Networks

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Limited battery power at wireless video sensor nodes, along with the transmission quality requirements for video data, makes quality-of-service (QoS) provisioning in a wireless video sensor network a very challenging task. In this paper, a dynamic power-management framework is proposed for a wireless video sensor node to improve the energy-saving performance while satisfying video transmission quality requirements. This framework is developed based on a Markov decision process that considers the video traffic arrival process in the sensor node, the sleep and wakeup processes in the camera and wireless transceiver electronics, the queue status, and the wireless channel condition. A dynamic programming approach is used to find the optimum policy to achieve the desired performance measures in an energy-limited sensor node. </para>

A design for distortion-aware cooperative relaying over wireless video sensor networks

This paper describes a distortion-aware cooperative relaying (DACR)scheme for distortion minimized video transmission over wireless video sensor networks. We first introduce a simple performance metric considering the different spatial and temporal error propagation effects existing in a video packet. Then, we propose the DACR algorithm which achieves gradual video quality degradation due to packet loss under conditions of limited channel resources. Experimental results show that the proposed scheme outperforms other existing scheme, and can also support optimal video quality for variable channel status.