Performance analysis of solar-powered wireless visual sensor network and its applications

This thesis discusses the performance of a solar-powered wireless visual sensor network and its visual applications. We examine the performance of a layered clustering model in sparing communication energy consumption and prolonging the system lifetime. The experimental result illustrates that the system can transmit the same amount of video packets with less energy consumption when video quality is at achievable minimum distortion rate. Therefore, the visual sensor network may achieve higher performance by applying rechargeable solar cell and layered clustering. After receiving all the video data, the sink may be applied with advanced post-processing techniques. We propose an innovative post-processing algorithm, Parallel Self-Organizing Tree Map (PSOTM) that can be implemented in the sink. By means of processing visual data in parallel, PSOTM may achieve faster image segmentation with insignificant impacts on the visual quality.

Power-Rate-Distortion Analysis Of Wireless Visual Sensor Network

The emergence of low-cost and mature technologies in wireless communication, visual sensor devices, and digtial signal processing, facilitates the potential of wirelss sensor networks (WSN). Like sensor networks which respond to sensory information such as temerpature and humidity, WSN interconnects autonomous devices for capturing and processing video and audio sensory information. This thesis highlights the following topics: (1) a summary of applications and challenges of WVSN; (2) the performance analysis of a wireless sensor network and wireless multimedia sensor network. To extend the system performance, two methods are provided in this thesis. First, mobile sink with node scheduling in multiple tracking targets is proposed. Second, a layered clustering model in sparing communication energy consumption in wirelsess visual sensor network is proposed. The experimental results validate our correlated approaches extend the system lifetime; (3) direction for Future Research are given.

Power-Rate-Distortion Analysis Of Wireless Visual Sensor Network

The emergence of low-cost and mature technologies in wireless communication, visual sensor devices, and digtial signal processing, facilitates the potential of wirelss sensor networks (WSN). Like sensor networks which respond to sensory information such as temerpature and humidity, WSN interconnects autonomous devices for capturing and processing video and audio sensory information. This thesis highlights the following topics: (1) a summary of applications and challenges of WVSN; (2) the performance analysis of a wireless sensor network and wireless multimedia sensor network. To extend the system performance, two methods are provided in this thesis. First, mobile sink with node scheduling in multiple tracking targets is proposed. Second, a layered clustering model in sparing communication energy consumption in wirelsess visual sensor network is proposed. The experimental results validate our correlated approaches extend the system lifetime; (3) direction for Future Research are given.

Performance analysis of solar-powered wireless visual sensor network and its applications

This thesis discusses the performance of a solar-powered wireless visual sensor network and its visual applications. We examine the performance of a layered clustering model in sparing communication energy consumption and prolonging the system lifetime. The experimental result illustrates that the system can transmit the same amount of video packets with less energy consumption when video quality is at achievable minimum distortion rate. Therefore, the visual sensor network may achieve higher performance by applying rechargeable solar cell and layered clustering. After receiving all the video data, the sink may be applied with advanced post-processing techniques. We propose an innovative post-processing algorithm, Parallel Self-Organizing Tree Map (PSOTM) that can be implemented in the sink. By means of processing visual data in parallel, PSOTM may achieve faster image segmentation with insignificant impacts on the visual quality.

Security Framework for Smart Visual Sensor Networks

Due to the significance of image data over the scalar data, the camera-integrated wireless sensor networks have attained the focus of researchers in the field of smart visual sensor networks. These networks are inexpensive and found wide application in surveillance and monitoring systems. The challenge is that these systems are resource deprived systems. The visual sensor node is typically an embedded system made up of a light weight processor, low memory, low bandwidth transceiver, and low-cost image sensor unit. As these networks carry sensitive information of the surveillance region, security and privacy protection are critical needs of the VSN. Due to resource limited nature of the VSN, the image encryption is crooked into an optimally lower issue, and many findings of image security in VSN are based on selective or partial encryption systems. The secure transmission of images is more trivial. Thus, in this chapter, a security frame work of smart visual sensor network built using energy-efficient image encryption and coding systems designed for VSN is presented.

Security Framework for Smart Visual Sensor Networks

Due to the significance of image data over the scalar data, the camera-integrated wireless sensor networks have attained the focus of researchers in the field of smart visual sensor networks. These networks are inexpensive and found wide application in surveillance and monitoring systems. The challenge is that these systems are resource deprived systems. The visual sensor node is typically an embedded system made up of a light weight processor, low memory, low bandwidth transceiver, and low-cost image sensor unit. As these networks carry sensitive information of the surveillance region, security and privacy protection are critical needs of the VSN. Due to resource limited nature of the VSN, the image encryption is crooked into an optimally lower issue, and many findings of image security in VSN are based on selective or partial encryption systems. The secure transmission of images is more trivial. Thus, in this chapter, a security frame work of smart visual sensor network built using energy-efficient image encryption and coding systems designed for VSN is presented.

A Sustainable Scheme for Minimizing Energy in Visual Sensor Network using Disjoint Set Cover Approach

Directional sensors in wireless visual sensor networks attract growing attention as a promising tool for monitoring the real world; directional sensors consume energy for two main tasks: sensing and communication. Since a VSN contains a number of configurable visual sensors with changeable spherical sectors of restricted angle known as a field of view that is intended to monitor a number of targets located in a random manner over a given area. Therefore maximizing the network lifetime through minimizing power consumption while covering the targets remains a challenge. In this paper, the problem of obtaining a disjoint set cover includes a minimum number of camera sensors is solved. The problem is known to be NP-complete. The sustainable design is improving an existing Iterative Target Oriented Algorithm (ITOA) to cover moving targets move randomly over a given area of deployment starting from entry points reaching to exit ones in a realistic simulation. To evaluate the performance of the modified algorithm, a comparison is provided with three existing algorithms (Iterative centralized Greedy Algorithm (ICGA), Iterative Centralized Forced-directed Algorithm ICFA, and Iterative Target Oriented Algorithm ITOA). Simulation results revealed that the sustainable scheme can find a disjoint set with a minimum number of sensors covers the maximum number of moving targets in an energy-efficient way and extended network lifetime.

A Generalized Threat Model for Visual Sensor Networks

Today, visual sensor networks (VSNs) are pervasively used in smart environments such as intelligent homes, industrial automation or surveillance. A major concern in the use of sensor networks in general is their reliability in the presence of security threats and cyberattacks. Compared to traditional networks, sensor networks typically face numerous additional vulnerabilities due to the dynamic and distributed network topology, the resource constrained nodes, the potentially large network scale and the lack of global network knowledge. These vulnerabilities allow attackers to launch more severe and complicated attacks. Since the state-of-the-art is lacking studies on vulnerabilities in VSNs, a thorough investigation of attacks that can be launched against VSNs is required. This paper presents a general threat model for the attack surfaces of visual sensor network applications and their components. The outlined threats are classified by the STRIDE taxonomy and their weaknesses are classified using CWE, a common taxonomy for security weaknesses.