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Designing k-coverage schedules in wireless sensor networks

Yingshu Li, Shan Gao
2007 Journal of combinatorial optimization  
In addition, we develop a guideline for users to better design a sensor deployment plan to save energy by employing a density control scheme.  ...  Some sensor network applications require k-coverage to ensure the quality of surveillance. Meanwhile, energy is another primary concern for sensor networks.  ...  In addition, we develop a guideline for users to better design a sensor deployment plan by employing density control. Simulation results are presented to evaluate our proposed algorithms.  ... 
doi:10.1007/s10878-007-9072-6 fatcat:qpdjum6o7nfnncmx7lrlkaniei

Optimization of people evacuation plans on the basis of wireless sensor networks

Yedilkhan Amirgaliyev, Rassul Yunussov, Orken Mamyrbayev
2016 Open Engineering  
of wireless sensor networks.  ...  Next tasks are to be solved: creation of mathematical model of optimal enclosed area surveillance by wireless sensors, database and data interrogation modelling of wireless sensor network, creation of  ...  Wireless sensor network optimal coverage problem Optimal coverage by the wireless sensor network is a common task to be solved to minimize resource allocation and expenditure.  ... 
doi:10.1515/eng-2016-0026 fatcat:wn2kkqkefvev7imrorvvecoyra

Intelligent wakening scheme for wireless sensor networks surveillance

Rui Wang, Lei Zhang, Li Cui
2011 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)  
The effective energy control while maintaining reliable detection performance is a key problem in wireless sensor networks surveillance, such as blue-green algae surveillance.  ...  Keywords-wireless sensor networks; intelligent wakening scheme; energy control; blue-green algae surveillance I.  ...  In [4] , Ye et al. developed a distributed density control algorithm named PEAS, which is probing based. In PEAS, each node sleeps for an exponentially distributed duration.  ... 
doi:10.1109/infcomw.2011.5928910 fatcat:yln7bui2c5aqlfaaub7p642shi

Study of Node Distribution and Density Optimization in Mobile Sensor Network 3D Space

Musong Gu, Chaobang Gao, Jingjing Lyu, Wenjie Fan, Lei You, Balakrishnan Nagaraj
2021 Wireless Communications and Mobile Computing  
deploy mobile sensor nodes in the 3D space to have reasonable layout and optimized density.  ...  Mobile sensor network is applied in information collection in emergencies.  ...  Literature [4] holds that although the full coverage is very important to the surveillance and control of wireless sensor network, however, as it is inevitable to cover voids for various reasons, the  ... 
doi:10.1155/2021/6978812 fatcat:2bk35llfjrcnfalvrcx6spqkye

Image Processing in Intelligent Traffic Management

2019 International journal of recent technology and engineering  
There is a need for developing algorithms with robust performance under heavy traffic loads and varied environmental conditions.  ...  Video surveillance has proven advantageous over traditional systems based on inductive loops sensors and detectors for traffic monitoring.  ...  A common architect of traffic control incorporates image acquisition, preprocessing and density calculation [17] .  ... 
doi:10.35940/ijrte.b1040.0782s419 fatcat:mg7uow3g35etvlj3tcumjqm3aa

Urban Road Traffic Management - Present and the Future Scenario

Prof. Rajashree Shettar, Prof. Manjunath A. E
2017 IOSR Journal of Computer Engineering  
This paper discusses various approaches for handling real time traffic by controlling the traffic signal lights accordingly.  ...  Vehicles either two or four wheeler has been increasing at very phenomenal rate year by year leading to congestion, pollution and wastage of man-hours waiting at signal lights for a longer period leading  ...  In [8] authors have developed a multi-agent system using fuzzy neural networks. Neural network is trained online continuously for agent based controller.  ... 
doi:10.9790/0661-1901041315 fatcat:6qmp35dzgrcqpm7gsgy34zxmpm

Putting the lab on the map

Mohammad Hammoudeh
2016 Proceedings of the International Conference on Internet of things and Cloud Computing - ICC '16  
Hammoudeh, MH (2016)Putting the lab on the map: A wireless sensor network system for border security and surveillance. In: ICC '16  ...  Putting the lab on the map: A wireless sensor network system for border security and surveillance ABSTRACT Traditionally, countries viewed international border control as mostly immigration-and customs-based  ...  Given an appropriate network density, how to determine if a region is indeed k-barrier covered?  ... 
doi:10.1145/2896387.2900338 dblp:conf/iotdcc/Hammoudeh16 fatcat:yglomcgol5asbmwcgbdnttwqtq

Sensor Scheduling for k-Coverage in Wireless Sensor Networks [chapter]

Shan Gao, Chinh T. Vu, Yingshu Li
2006 Lecture Notes in Computer Science  
In addition, we develop a guideline for users to better design a sensor deployment plan to save energy by employing density control.  ...  Some sensor network applications require k-coverage to ensure the quality of surveillance. Meanwhile, energy is another primary concern for sensor networks.  ...  Effect of Density Control on Network Lifetime In this set of experiments, we apply Density Control (DC) for sensor deployment and evaluate its effectiveness.  ... 
doi:10.1007/11943952_23 fatcat:rtrk2uhwm5dprlv2efuj6s2ywm

Sacrificing a Little Coverage Can Substantially Increase Network Lifetime

Limin Wang, Sandeep Kulkarni
2006 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks  
We present a simple, local protocol, pCover, which provides partial (but high) coverage in sensor networks.  ...  In particular, we show that we are able to maintain 94% coverage for a duration that is 2.3-7 times the duration for which existing protocols maintain full coverage.  ...  Introduction A surveillance sensor network needs to operate unattended for a long time, usually from several weeks to several months.  ... 
doi:10.1109/sahcn.2006.288437 dblp:conf/secon/WangK06 fatcat:5iswhgiuf5aqxalpstnrjtn4pq

Sacrificing a little coverage can substantially increase network lifetime

Limin Wang, Sandeep S. Kulkarni
2008 Ad hoc networks  
We present a simple, local protocol, pCover, which provides partial (but high) coverage in sensor networks.  ...  In particular, we show that we are able to maintain 94% coverage for a duration that is 2.3-7 times the duration for which existing protocols maintain full coverage.  ...  Introduction A surveillance sensor network needs to operate unattended for a long time, usually from several weeks to several months.  ... 
doi:10.1016/j.adhoc.2007.11.013 fatcat:kzkbnscq6raffkiczz5bnerejm

Maximising α-lifetime for wireless sensor networks

Honghai Zhang, Jennifer C. Hou
2006 International Journal of Sensor Networks (IJSNet)  
We then design, based on the derived upper bound, an algorithm that sub-optimally schedules node activities to maximise the α-lifetime of a sensor network.  ...  In this paper, we investigate how to maximise the α-lifetime of wireless sensor networks, where α-lifetime is defined as the time duration during which at least α portion of the surveillance region is  ...  Ye et al. (2002 Ye et al. ( , 2003 present PEAS, a distributed, probing-based density control algorithm for robust sensing coverage.  ... 
doi:10.1504/ijsnet.2006.010835 fatcat:bmod3yebg5dtfmqls2eprfnajm

Multi-vehicle testbed for decentralized environmental sensing

R Andres Cortez, Jose-Marcio Luna, Rafael Fierro, John Wood
2010 2010 IEEE International Conference on Robotics and Automation  
Two cooperative control algorithms: prioritized multi-sensing behavior, and a distributed adaptive algorithm for nonholonomic sensor networks are qualitatively verified using our multi-vehicle testbed.  ...  In this paper we present our multi-vehicle testbed that was designed for verification and validation of cooperative control algorithms involving environmental sensing.  ...  Adaptive Algorithm for Nonholonomic Sensor Networks Having a density function of a measurable phenomenon we can employ dynamic sensor networks to get an estimation of the concentration.  ... 
doi:10.1109/robot.2010.5509294 dblp:conf/icra/CortezLFW10a fatcat:dbhf5e64yzfajmlshbidakoira

Improvement in K-medoid Clustering using Density based Node Selection

Biresh Kumar, Pallab Banerjee, Amarnath Singh, Anurag Kumar, Avinash Kumar
2020 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
A wireless sensor network is collection of large number of individual sensor nodes. A sensor usually comprises of components for sensing the environment, processing, communicating and a power supply.  ...  The wireless sensor networks have become a very hot topic of research in the recent years because of their wide range of applications such as industrial and agricultural monitoring, military surveillance  ...  .: An Energy-Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks. In: Proceedings of IEEE INFOCOM (2003). [5]. J.Y. Chang and P.H.  ... 
doi:10.32628/cseit2062142 fatcat:mkei5hupcbea3cvqdfw2hmuopa

A Density Control Algorithm For Wireless Sensor Network

Danyan Luo, Haiying Zhou, Zhan Zhang, Decheng Zuo
2011 International Journal of Wireless and Microwave Technologies  
This paper proposes SNDC (Sensor Network Density Control), a location-free and range-free density control algorithm for wireless sensor network to keep as few as possible sensors in active state to achieve  ...  Consequently, density control technology is necessary for sensor networks, because it can reduce the number of active sensor nodes under the precondition of ensuring network coverage and network connectivity  ...  A Density Control Algorithm For Wireless Sensor Network 9 node failed. Therefore, this algorithm is fault tolerant.  ... 
doi:10.5815/ijwmt.2011.06.01 fatcat:7dwiux2nljaytesmb7psnwwfnm

Multiplatform information-based sensor management: an inverted UAV demonstration

Chris Kreucher, John Wegrzyn, Michel Beauvais, Ralph Conti, Raja Suresh
2007 Defense Transformation and Net-Centric Systems 2007  
This paper describes an experimental demonstration of a distributed, decentralized, low communication sensor management algorithm.  ...  We first review the mathematics surrounding the method, which includes a novel combination of particle filtering for predictive density estimation and information theory for maximizing information flow  ...  The sensor management algorithm, described in detail elsewhere, 2 is a novel combination of particle filtering for predictive density estimation, information theory for action selection, and a physicomimetic  ... 
doi:10.1117/12.719395 fatcat:lj3n4bdldbdldmyxclcytgwyvi
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