Description: Abstract—Wireless networks in combination with image
sensors open up a multitude of previously unthinkable sensing
applications. Capable tools and testbeds for these wireless image
sensor networks can greatly accelerate development of complex,
yet efficient algorithms that meet application requirements. In this
paper, we introduce WiSNAP, a Matlab-based application
development platform intended for wireless image sensor
networks. It allows researchers and developers of such networks
to investigate, design, and evaluate algorithms and applications
using real target hardware. WiSNAP offers standardized and
easy-to-use Application Program Interfaces (APIs) to control
image sensors and wireless motes, which do not require detailed
knowledge of the target hardware. Nonetheless, its open system
architecture enables support of virtually any kind of sensor or
wireless mote. Application examples are presented to illustrate the
usage of WiSNAP as a powerful development tool.-Abstract-Wireless networks in combination with imagesensors open up a multitude of previously unthinkable sensingapplications. Capable tools and testbeds for these wireless imagesensor networks can greatly accelerate development of complex, yet efficient algorithms that meet application requirements. In thispaper, we introduce WiSNAP, a Matlab-based applicationdevelopment platform intended for wireless image sensornetworks. It allows researchers and developers of such networksto investigate, design, and evaluate algorithms and applicationsusing real target hardware. WiSNAP offers standardized andeasy-to-use Application Program Interfaces (APIs) to controlimage sensors and wireless motes, which do not require detailedknowledge of the target hardware. Nonetheless, its open systemarchitecture enables support of virtually any kind of sensor orwireless mote. Application examples are presented to illustrate theusage of WiSNAP as a powerful development tool. Platform: |
Size: 493568 |
Author:北原修 |
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Description: In recent years there has been a growing interest in
wireless sensor networks (WSN) applications. Such sensor
networks can be used to control temperature, humidity,
contamination, pollution etc. Self-organization and
routing algorithms dedicated to wireless sensor networks
usually assume that sensors absolute positions are
unknown and all decisions are based on sensor’s own
local information. Platform: |
Size: 278528 |
Author:nakula |
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Description: Security in wireless sensor networks is currently provided
through symmetric key cryptography. Although the low
computational complexity involved in private key algorithms is
advantageous, session keys must be embedded in the sensor nodes
before the nodes can be deployed. Protocols are also necessary to
ensure synchronization of keys between the devices on a network.
These protocols require significant communication and storage
overhead. The limitation of such a cryptosystem is that it is not
possible to guarantee the confidentiality of the session keys Platform: |
Size: 179200 |
Author:yared |
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Description: 无线传感器网，PEGASIS算法组网程序。在1*1范围内的以node_number个节点，以PEGASIS算法成网。-Wireless sensor networks, PEGASIS algorithm networking program. 1* 1 to node_number within the nodes in order to PEGASIS algorithms into a network. Platform: |
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Author:dawn |
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Description: One of the most critical issues in the wireless sensor networks is the network s nodes limited availability of energy. The network lifetime strictly depends on its energy efficiency.
Clustering is a method to make the consumed energy efficient. LEACH is one of the fundamental clustering algorithms. In
this paper we have proposed an algorithm which extends LEACH by considering number of neighbors and remaining of the energy of each node to be a cluster head. We have also proposed to use gateway nodes in each cluster to enable the
cluster head to reduce its transmission radius within the cluster to achieve better power saving. We analyze and compared the proposed algorithm along with the LEACH, LEACH-c and MIMO the most recent extend over the LEACH and show that the proposed algorithm can prolong the lifetime of the network. Platform: |
Size: 307200 |
Author:Mohamed Rias |
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Description: 定位技术是无线传感器网络中关键的基础支撑技术, 目前提出了许多静态网络的节点定位算
法, 移动无线传感器网络的定位研究相对较少. 针对定位节点和参考节点随机运动的网络模型, 提出了
一个基于动态网格划分的蒙特卡罗定位算法. 算法中当接收的参考节点数超过一定阈值时使用最远距
离节点选择模型, 选出部分参考节点参与定位和信息转发, 节约能耗. 接着基于选择的或所有接收的参
考节点构建采样区域, 进行网格划分, 使用网格单元数计算最大采样次数, 在采样区域内采样并使用误
差补偿的运动模型进行过滤, 提高了采样效率, 减少了计算开销, 并保证了较好的定位精度. 仿真实验表
明算法在定位精度, 计算开销、能耗等方面都具有较好的性能.-Positioning technology is critical in wireless sensor networks based supporting technologies, currently made many static network node localization algorithms, the positioning of mobile wireless sensor network research is relatively small. Locate node and a reference node for random motion network model, proposed a Dynamic meshing based Monte Carlo localization algorithm. algorithm when the received reference nodes exceeds a certain threshold, the most distant node selection model selects some reference nodes involved locating and forwarding information, save energy. then based on the selection or building all received reference node sampling area, meshing, the number of grid cells used to calculate the maximum sampling frequency, the sampling area sampling and using motion model error compensation filter to improve sampling efficiency, reducing the computational overhead and to ensure a better positioning accuracy. Simulation experiments show that the algorithm in positioning accuracy, Platform: |
Size: 576512 |
Author:Jeff |
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Description: In this paper, we propose a novel compressive
sensing (CS) based approach for sparse target counting and
positioning in wireless sensor networks. While this is not the
first work on applying CS to count and localize targets, it
is the first to rigorously justify the validity of the problem
formulation. Moreover, we propose a novel greedy matching
pursuit algorithm (GMP) that complements the well-known
signal recovery algorithms in CS theory and prove that GMP can
accurately recover a sparse signal with a high probability. We
also propose a framework for counting and positioning targets
from multiple categories, a novel problem that has never been
addressed before. Finally, we perform a comprehensive set of
simulations whose results demonstrate the superiority of our
approach over the existing CS and non-CS based techniques. Platform: |
Size: 188416 |
Author:saeede abbasi |
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Description: 无线传感器网络分簇路由算法，很经典的，适合初学者练习使用-Clustering routing algorithms in wireless sensor networks, very classic, suitable for beginners to use
Platform: |
Size: 22528 |
Author:朱攀 |
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Description: Localization in wireless sensor networks is the process of determining the geographical positions of
sensors. Only some of the sensors (anchors) in the networks have prior knowledge about their geographical
positions. Localization algorithms use the location information of anchors and estimates
of distances between neighbouring nodes to determine the positions of the rest of the sensors. Platform: |
Size: 1506304 |
Author:vinod |
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Description: This document presents a survey on using machine learning algorithms in wireless sensor networks applications such as localization ,routing... Platform: |
Size: 653312 |
Author:hanen |
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Description: Improve network lifetime by managing the base station receiver in wireless sensor networks
Hierarchical algorithms - persian paper Platform: |
Size: 1111040 |
Author:saeed |
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Description: 无线传感器网络时间同步算法案例及matlab仿真(Case Study of Time Synchronization Algorithms in Wireless Sensor Networks) Platform: |
Size: 1024 |
Author:zirmly |
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Search - algorithms in wireless sensor networks