Omnidirectional antennas are often used for radio frequency (RF) communication in wireless sensor networks (WSNs). Outside noise, electromagnetic interference (EMI), overloaded network traffic, large obstacles (vegetation and buildings), terrain and atmospheric composition, along with climate patterns can degrade signal quality in the form of data packet loss or reduced RF communication range. This paper explores the RF range reduction properties of a particular WSN designed to operate in agricultural crop fields to collect aggregate data composed of subsurface soil moisture and soil temperature. Our study, using simulation, anechoic and field measurements shows that the effect of antenna placement close to the ground (within 10 cm) signi?cantly changes the omnidirectional transmission pattern. We then develop and propose a prediction method that is more precise than current practices of using the Friis and Fresnel equations. Our prediction method takes into account environmental properties for RF communication range based on the height of nodes and gateways.
{"title":"Predicting Ground Effects of Omnidirectional Antennas in Wireless Sensor Networks","authors":"J. Janek, Jeffrey J. Evans","doi":"10.4236/wsn.2010.212106","DOIUrl":"https://doi.org/10.4236/wsn.2010.212106","url":null,"abstract":"Omnidirectional antennas are often used for radio frequency (RF) communication in wireless sensor networks (WSNs). Outside noise, electromagnetic interference (EMI), overloaded network traffic, large obstacles (vegetation and buildings), terrain and atmospheric composition, along with climate patterns can degrade signal quality in the form of data packet loss or reduced RF communication range. This paper explores the RF range reduction properties of a particular WSN designed to operate in agricultural crop fields to collect aggregate data composed of subsurface soil moisture and soil temperature. Our study, using simulation, anechoic and field measurements shows that the effect of antenna placement close to the ground (within 10 cm) signi?cantly changes the omnidirectional transmission pattern. We then develop and propose a prediction method that is more precise than current practices of using the Friis and Fresnel equations. Our prediction method takes into account environmental properties for RF communication range based on the height of nodes and gateways.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114781877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Approaches based on integer linear programming have been recently proposed for topology optimization in wireless sensor networks. They are, however, based on over-theoretical, unrealistic models. Our aim is to show that it is possible to accommodate realistic models for energy consumption and communication protocols into integer linear programming. We analyze the maximum lifetime broadcasting topology problem and we present realistic models that are also shown to provide efficient and practical solving tools. We present a strategy to substantially speed up the convergence of the solving process of our algorithm. This strategy introduces a practical drawback, however, in the characteristics of the optimal solutions retrieved. A method to overcome this drawback is discussed. Computational experiments are reported.
{"title":"Integer Programming Formulations for Maximum Lifetime Broadcasting Problems in Wireless Sensor Networks","authors":"R. Montemanni","doi":"10.4236/wsn.2010.212111","DOIUrl":"https://doi.org/10.4236/wsn.2010.212111","url":null,"abstract":"Approaches based on integer linear programming have been recently proposed for topology optimization in wireless sensor networks. They are, however, based on over-theoretical, unrealistic models. Our aim is to show that it is possible to accommodate realistic models for energy consumption and communication protocols into integer linear programming. We analyze the maximum lifetime broadcasting topology problem and we present realistic models that are also shown to provide efficient and practical solving tools. We present a strategy to substantially speed up the convergence of the solving process of our algorithm. This strategy introduces a practical drawback, however, in the characteristics of the optimal solutions retrieved. A method to overcome this drawback is discussed. Computational experiments are reported.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117249914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bhaskar Bhuyan, H. Sarma, N. Sarma, A. Kar, R. Mall
Wireless sensor networks (WSNs) are required to provide different levels of Quality of Services (QoS) based on the type of applications. Providing QoS support in wireless sensor networks is an emerging area of research. Due to resource constraints like processing power, memory, bandwidth and power sources in sensor networks, QoS support in WSNs is a challenging task. In this paper, we discuss the QoS requirements in WSNs and present a survey of some of the QoS aware routing techniques in WSNs. We also explore the middleware approaches for QoS support in WSNs and finally, highlight some open issues and future direction of research for providing QoS in WSNs.
{"title":"Quality of Service (QoS) Provisions in Wireless Sensor Networks and Related Challenges","authors":"Bhaskar Bhuyan, H. Sarma, N. Sarma, A. Kar, R. Mall","doi":"10.4236/wsn.2010.211104","DOIUrl":"https://doi.org/10.4236/wsn.2010.211104","url":null,"abstract":"Wireless sensor networks (WSNs) are required to provide different levels of Quality of Services (QoS) based on the type of applications. Providing QoS support in wireless sensor networks is an emerging area of research. Due to resource constraints like processing power, memory, bandwidth and power sources in sensor networks, QoS support in WSNs is a challenging task. In this paper, we discuss the QoS requirements in WSNs and present a survey of some of the QoS aware routing techniques in WSNs. We also explore the middleware approaches for QoS support in WSNs and finally, highlight some open issues and future direction of research for providing QoS in WSNs.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123754079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Node localization is commonly employed in wireless networks. For example, it is used to improve routing and enhance security. Localization algorithms can be classified as range-free or range-based. Range-based algorithms use location metrics such as ToA, TDoA, RSS, and AoA to estimate the distance between two nodes. Proximity sensing between nodes is typically the basis for range-free algorithms. A tradeoff exists since range-based algorithms are more accurate but also more complex. However, in applications such as target tracking, localization accuracy is very important. In this paper, we propose a new range-based algorithm which is based on the density-based outlier detection algorithm (DBOD) from data mining. It requires selection of the K-nearest neighbours (KNN). DBOD assigns density values to each point used in the location estimation. The mean of these densities is calculated and those points having a density larger than the mean are kept as candidate points. Different performance measures are used to compare our approach with the linear least squares (LLS) and weighted linear least squares based on singular value decomposition (WLS-SVD) algorithms. It is shown that the proposed algorithm performs better than these algorithms even when the anchor geometry about an unlocalized node is poor.
{"title":"Range-Based Localization in Wireless Networks Using Density-Based Outlier Detection","authors":"Khalid K. Almuzaini, T. Gulliver","doi":"10.4236/wsn.2010.211097","DOIUrl":"https://doi.org/10.4236/wsn.2010.211097","url":null,"abstract":"Node localization is commonly employed in wireless networks. For example, it is used to improve routing and enhance security. Localization algorithms can be classified as range-free or range-based. Range-based algorithms use location metrics such as ToA, TDoA, RSS, and AoA to estimate the distance between two nodes. Proximity sensing between nodes is typically the basis for range-free algorithms. A tradeoff exists since range-based algorithms are more accurate but also more complex. However, in applications such as target tracking, localization accuracy is very important. In this paper, we propose a new range-based algorithm which is based on the density-based outlier detection algorithm (DBOD) from data mining. It requires selection of the K-nearest neighbours (KNN). DBOD assigns density values to each point used in the location estimation. The mean of these densities is calculated and those points having a density larger than the mean are kept as candidate points. Different performance measures are used to compare our approach with the linear least squares (LLS) and weighted linear least squares based on singular value decomposition (WLS-SVD) algorithms. It is shown that the proposed algorithm performs better than these algorithms even when the anchor geometry about an unlocalized node is poor.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126478134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a simulation framework for wireless sensor networks developed to allow the design exploration and the complete microprocessor-instruction-level debug of network formation, data congestion, nodes interaction, all in one simulation environment. A specifically innovative feature is the co-emulation of selected nodes at clock-cycle-accurate hardware processing level, allowing code debug and exact execution latency evaluation (considering both protocol stack and application), together with other nodes at abstract protocol level, meeting a designer’s needs of simulation speed, scalability and reliability. The simulator is centered on the Zigbee protocol and can be retargeted for different node micro-architectures.
{"title":"TikTak: A Scalable Simulator of Wireless Sensor Networks Including Hardware/Software Interaction","authors":"F. Menichelli, M. Olivieri","doi":"10.4236/wsn.2010.211098","DOIUrl":"https://doi.org/10.4236/wsn.2010.211098","url":null,"abstract":"We present a simulation framework for wireless sensor networks developed to allow the design exploration and the complete microprocessor-instruction-level debug of network formation, data congestion, nodes interaction, all in one simulation environment. A specifically innovative feature is the co-emulation of selected nodes at clock-cycle-accurate hardware processing level, allowing code debug and exact execution latency evaluation (considering both protocol stack and application), together with other nodes at abstract protocol level, meeting a designer’s needs of simulation speed, scalability and reliability. The simulator is centered on the Zigbee protocol and can be retargeted for different node micro-architectures.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122682532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As one of the commonly used queries in modern databases, skyline query has received extensive attention from database research community. The uncertainty of the data in wireless sensor networks makes the corresponding skyline uncertain and not unique. This paper investigates the Pr-Skyline problem, i.e., how to compute the skyline with the highest existence probability in a computational and energy-efficient way. We formulate the problem and prove that it is NP-Complete and cannot be approximated in a given expression. However, the proposed algorithm SKY-SEARCH with pruning techniques can guarantee the computational efficiency given relatively large input size, while the filter-based distributed optimization strategy significantly reduces the transmission cost and the required storage space of the sensor nodes. Extensive experiments verify the efficiency and scalability of SKY-SEARCH and the distributed optimizing strategy.
{"title":"Efficient Pr-Skyline Query Processing and Optimization in Wireless Sensor Networks","authors":"Jianzhong Li, Shuguang Xiong","doi":"10.4236/wsn.2010.211101","DOIUrl":"https://doi.org/10.4236/wsn.2010.211101","url":null,"abstract":"As one of the commonly used queries in modern databases, skyline query has received extensive attention from database research community. The uncertainty of the data in wireless sensor networks makes the corresponding skyline uncertain and not unique. This paper investigates the Pr-Skyline problem, i.e., how to compute the skyline with the highest existence probability in a computational and energy-efficient way. We formulate the problem and prove that it is NP-Complete and cannot be approximated in a given expression. However, the proposed algorithm SKY-SEARCH with pruning techniques can guarantee the computational efficiency given relatively large input size, while the filter-based distributed optimization strategy significantly reduces the transmission cost and the required storage space of the sensor nodes. Extensive experiments verify the efficiency and scalability of SKY-SEARCH and the distributed optimizing strategy.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116686306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this work we propose an orthogonal pulse waveform for wireless ultra wideband (UWB) transmission. The design is based on an ideal low-pass prototype filter having a windowed sinc impulse response. The frequency response of the prototype filter is transferred to the high frequency region using a specific sign modulator. The UWB pulse waveform comprises of the weighted summation of the left singular vectors of the impulse response matrix. The power spectral density of the pulse waveform fulfils the FCC constraint (allowed frequency band 3.1-10.6 GHz) for unlicensed UWB transmission. Applications of the UWB pulse waveform in multi-channel wireless sensor networks are considered.
{"title":"Design of Orthogonal UWB Pulse Waveform for Wireless Multi-Sensor Applications","authors":"H. Olkkonen, J. Olkkonen","doi":"10.4236/wsn.2010.211102","DOIUrl":"https://doi.org/10.4236/wsn.2010.211102","url":null,"abstract":"In this work we propose an orthogonal pulse waveform for wireless ultra wideband (UWB) transmission. The design is based on an ideal low-pass prototype filter having a windowed sinc impulse response. The frequency response of the prototype filter is transferred to the high frequency region using a specific sign modulator. The UWB pulse waveform comprises of the weighted summation of the left singular vectors of the impulse response matrix. The power spectral density of the pulse waveform fulfils the FCC constraint (allowed frequency band 3.1-10.6 GHz) for unlicensed UWB transmission. Applications of the UWB pulse waveform in multi-channel wireless sensor networks are considered.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130647337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wavelet packets decompose signals in to broader components using linear spectral bisecting. Mixing matrix is the key issue in the Blind Source Separation (BSS) literature especially in under-determined cases. In this paper, we propose a simple and novel method in Short Time Wavelet Packet (STWP) analysis to estimate blindly the mixing matrix of speech signals from noise free linear mixtures in over-complete cases. In this paper, the Laplacian model is considered in short time-wavelet packets and is applied to each histogram of packets. Expectation Maximization (EM) algorithm is used to train the model and calculate the model parameters. In our simulations, comparison with the other recent results will be computed and it is shown that our results are better than others. It is shown that complexity of computation of model is decreased and consequently the speed of convergence is increased.
{"title":"Underdetermined Blind Mixing Matrix Estimation Using STWP Analysis for Speech Source Signals","authors":"B. M. Tazehkand, M. Tinati","doi":"10.4236/wsn.2010.211103","DOIUrl":"https://doi.org/10.4236/wsn.2010.211103","url":null,"abstract":"Wavelet packets decompose signals in to broader components using linear spectral bisecting. Mixing matrix is the key issue in the Blind Source Separation (BSS) literature especially in under-determined cases. In this paper, we propose a simple and novel method in Short Time Wavelet Packet (STWP) analysis to estimate blindly the mixing matrix of speech signals from noise free linear mixtures in over-complete cases. In this paper, the Laplacian model is considered in short time-wavelet packets and is applied to each histogram of packets. Expectation Maximization (EM) algorithm is used to train the model and calculate the model parameters. In our simulations, comparison with the other recent results will be computed and it is shown that our results are better than others. It is shown that complexity of computation of model is decreased and consequently the speed of convergence is increased.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"260 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121886108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to decrease the interference in wireless communication networks. In this paper, we propose smart step closed-loop power control (SSPC) algorithm in wireless networks in a 2D urban environment with constrained least mean squared (CLMS) algorithm. This algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. Also, we present switched-beam (SB) technique for enhancing signal to interference plus noise ratio (SINR) in wireless networks. Also, we study an analytical approach for the evaluation of the impact of power control error (PCE) on wireless networks in a 2D urban environment. The simulation results indicate that the convergence speed of the SSPC algorithm is faster than other algorithms. Also, we observe that significant saving in total transmit power (TTP) are possible with our proposed algorithm. Finally, we discuss three parameters of the PCE, number of antenna elements, and path-loss exponent and their effects on capacity of the system via some computer simulations.
{"title":"Joint Closed-Loop Power Control and Adaptive Beamforming for Wireless Networks with Antenna Arrays in a 2D Urban Environment","authors":"M. D. Moghadam, H. Bakhshi, G. Dadashzadeh","doi":"10.4236/wsn.2010.211105","DOIUrl":"https://doi.org/10.4236/wsn.2010.211105","url":null,"abstract":"The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to decrease the interference in wireless communication networks. In this paper, we propose smart step closed-loop power control (SSPC) algorithm in wireless networks in a 2D urban environment with constrained least mean squared (CLMS) algorithm. This algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. Also, we present switched-beam (SB) technique for enhancing signal to interference plus noise ratio (SINR) in wireless networks. Also, we study an analytical approach for the evaluation of the impact of power control error (PCE) on wireless networks in a 2D urban environment. The simulation results indicate that the convergence speed of the SSPC algorithm is faster than other algorithms. Also, we observe that significant saving in total transmit power (TTP) are possible with our proposed algorithm. Finally, we discuss three parameters of the PCE, number of antenna elements, and path-loss exponent and their effects on capacity of the system via some computer simulations.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122281652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Considering the environmental protection, forest fire becomes a more and more serious problem and requires more concerns. This paper provides an efficient method for fire monitoring and detection in forests using wireless sensor network technology. The proposed technique estimates the location of a sensor node based on the current set of hop-count values, which are collected through the anchor nodes’ broadcast. Our algorithm incorporates two salient features; grid-based output and event-triggering mechanism, to improve the accuracy while reducing the power consumption. Through the computer simulation, the output region obtained from our algorithm can always cover the target node. In addition, the algorithm was implemented and tested with a set of Crossbow sensors. Experimental results demonstrated the high feasibility and worked well in real environment.
{"title":"3-D Grid-Based Localization Technique in Mobile Sensor Networks","authors":"Jia Li, Lei Sun, Wai Yee Leong, P. Chong","doi":"10.4236/wsn.2010.211100","DOIUrl":"https://doi.org/10.4236/wsn.2010.211100","url":null,"abstract":"Considering the environmental protection, forest fire becomes a more and more serious problem and requires more concerns. This paper provides an efficient method for fire monitoring and detection in forests using wireless sensor network technology. The proposed technique estimates the location of a sensor node based on the current set of hop-count values, which are collected through the anchor nodes’ broadcast. Our algorithm incorporates two salient features; grid-based output and event-triggering mechanism, to improve the accuracy while reducing the power consumption. Through the computer simulation, the output region obtained from our algorithm can always cover the target node. In addition, the algorithm was implemented and tested with a set of Crossbow sensors. Experimental results demonstrated the high feasibility and worked well in real environment.","PeriodicalId":251051,"journal":{"name":"Wirel. Sens. Netw.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125225652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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