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摘要:
Wireless visual sensor network (VSN) can be said to be a special class of wireless sensor network (WSN) with smart-cameras. Due to its visual sensing capability, it has become an effective tool for applications such as large area surveillance, environmental monitoring and objects tracking. Different from a conventional WSN, VSN typically includes relatively expensive camera sensors, enhanced flash memory and a powerful CPU. While energy consumption is dominated primarily by data transmission and reception, VSN consumes extra power onimage sensing, processing and storing operations. The well-known energy-hole problem of WSNs has a drastic impact on the lifetime of VSN, because of the additional energy consumption of a VSN. Most prior research on VSN energy issues are primarily focusedon a single device or a given specific scenario. In this paper, we propose a novel optimal two-tier deployment strategy for a large scale VSN. Our two-tier VSN architecture includes tier-1 sensing network with visual sensor nodes (VNs) and tier-2 network having only relay nodes (RNs). While sensing network mainly performs image data collection, relay network only for wards image data packets to the central sink node. We use uniform random distribution of VNs to minimize the cost of VSN and RNs are deployed following two dimensional Gaussian distribution so as to avoid energy-hole problem. Algorithms are also introduced that optimizes deployment parameters and are shown to enhance the lifetime of the VSN in a cost effective manner.
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篇名 Deployment Optimization Strategy for a Two-Tier Wireless Visual Sensor Network
来源期刊 无线传感网络(英文) 学科 工学
关键词 Energy-Hole Problem Gaussian Distribution Relay NODE 2-Tier NETWORK VISUAL SENSOR NODE WIRELESS VISUAL SENSOR NETWORK
年,卷(期) 2012,(4) 所属期刊栏目
研究方向 页码范围 91-106
页数 16页 分类号 TN92
字数 语种
DOI
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节点文献
Energy-Hole
Problem
Gaussian
Distribution
Relay
NODE
2-Tier
NETWORK
VISUAL
SENSOR
NODE
WIRELESS
VISUAL
SENSOR
NETWORK
研究起点
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研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
无线传感网络(英文)
月刊
1945-3078
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
358
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