Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monito...Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN.展开更多
The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial operations.Ensuring the networks can overcome obstacles like power and communication r...The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial operations.Ensuring the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network optimization.Network infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node distribution.This work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and design.By using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and exploitation.Through implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network operation.We compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world problems.Being the most efficient in the optimization process,Biruni displays the lowest error rate at 0.00032.The two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific problems.Due to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be made.Through delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.展开更多
The Wireless Sensor Networks(WSN)is a self-organizing network with random deployment of wireless nodes that connects each other for effective monitoring and data transmission.The clustering technique employed to group...The Wireless Sensor Networks(WSN)is a self-organizing network with random deployment of wireless nodes that connects each other for effective monitoring and data transmission.The clustering technique employed to group the collection of nodes for data transmission and each node is assigned with a cluster head.The major concern with the identification of the cluster head is the consideration of energy consumption and hence this paper proposes an hybrid model which forms an energy efficient cluster head in the Wireless Sensor Network.The proposed model is a hybridization of Glowworm Swarm Optimization(GSO)and Artificial Bee Colony(ABC)algorithm for the better identification of cluster head.The performance of the proposed model is compared with the existing techniques and an energy analysis is performed and is proved to be more efficient than the existing model with normalized energy of 5.35%better value and reduction of time complexity upto 1.46%.Above all,the proposed model is 16%ahead of alive node count when compared with the existing methodologies.展开更多
We consider the extension of network lifetime of battery driven wireless sensor networks by splitting the sensing area into uniform clusters and implementing heterogeneous modulation schemes at different members of th...We consider the extension of network lifetime of battery driven wireless sensor networks by splitting the sensing area into uniform clusters and implementing heterogeneous modulation schemes at different members of the clusters. A cross-layer optimization has been proposed to reduce total energy expenditure of the network;at network layer, routing is done through uniform clusters;at MAC layer, each sensor node of the cluster is assigned fixed or variable time slots and at physical layer different member of the clusters is assigned different modulation techniques. MATLAB simulation proved substantial network lifetime gains.展开更多
Wireless sensor network(WSN)nodes exchange information via wireless signals,whose power can attenuate at different levels according to the propagation environment.The branches and leaves of young apple trees are much ...Wireless sensor network(WSN)nodes exchange information via wireless signals,whose power can attenuate at different levels according to the propagation environment.The branches and leaves of young apple trees are much sparser than that of adult apple trees.Propagation rules such as propagation distance and attenuation rate are the parameters necessary to know before applying a WSN to a young apple orchard.Field tests were performed,and propagation distance and packet loss rate(PLR)were computed and compared under the two cases:a young apple orchard in fruit period and an open space to find the effect of the apple trees on radio propagation.A model of antenna height and propagation distance was created to forecast the extra path loss caused by the young trees.Validation experiments were performed in a different young apple orchard,and the validation results showed that 70% of R^(2) were higher than 0.7,while the smallest being 0.65;80% RMSE were smaller than 5.The new model was also compared with some classical models such as Cost 235,FITU,ITU-R,and Weissberger model,and the new model was proved to be the best.展开更多
This work proposes an innovative approach to evaluate the functional characteristics of a heterogeneous underwater wireless acoustic sensor network(UWASN)using a stochastic model and the network connectivity criterion...This work proposes an innovative approach to evaluate the functional characteristics of a heterogeneous underwater wireless acoustic sensor network(UWASN)using a stochastic model and the network connectivity criterion.The connectivity criterion is probabilistic and considers inherently distinct groups of parameters:technical parameters that determine the network function at specific levels of the communication stack and physical parameters that describe the environment in the water area.The proposed approach enables researchers to evaluate the network characteristics in terms of energy efficiency and reliability while considering specific network and environmental parameters.Moreover,this approach is a simple and convenient tool for analyzing the effectiveness of protocols in various open systems interconnection model levels.It is possible to assess the potential capabilities of any protocol and include it in the proposed model.This work presents the results of modeling the critical characteristics of heterogeneous three-dimensional UWASNs of different scales consisting of stationary sensors and a wave glider as a mobile gateway,using specific protocols as examples.Several alternative routes for the wave glider are considered to optimize the network’s functional capabilities.Optimal trajectories of the wave glider’s movement have been determined in terms of ensuring the efficiency and reliability of the hybrid UWASN at various scales.In the context of the problem,an evaluation of different reference node placement was to ensure message transmission to a mobile gateway.The best location of reference nodes has been found.展开更多
With the development of CMOS and MEMS technologies, the implementation of a large number of wireless distributed micro-sensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad...With the development of CMOS and MEMS technologies, the implementation of a large number of wireless distributed micro-sensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad hoc sensor networks. To facilitate ease of deployment, these sensors operate on battery for extended periods of time. A particular challenge in maintaining extended battery lifetime lies in achieving communications with low power. For better understanding of the design tradeoffs of wireless sensor network （WSN）, a more accurate energy model for wireless sensor node is proposed, and an optimal design method of energy efficient wireless sensor node is described as well. Different from power models ever shown which assume the power cost of each component in WSN node is constant, the new one takes into account the energy dissipation of circuits in practical physical layer. It shows that there are some parameters, such as data rate, carrier frequency, bandwidth, Tsw, etc, which have a significant effect on the WSN node energy consumption per useful bit （EPUB）. For a given quality specification, how energy consumption can be reduced by adjusting one or more of these parameters is shown.展开更多
In the network field,Wireless Sensor Networks(WSN)contain prolonged attention due to afresh augmentations.Industries like health care,traffic,defense,and many more systems espoused the WSN.These networks contain tiny ...In the network field,Wireless Sensor Networks(WSN)contain prolonged attention due to afresh augmentations.Industries like health care,traffic,defense,and many more systems espoused the WSN.These networks contain tiny sensor nodes containing embedded processors,TinyOS,memory,and power source.Sensor nodes are responsible for forwarding the data packets.To manage all these components,there is a need to select appropriate parameters which control the quality of service of WSN.Multiple sensor nodes are involved in transmitting vital information,and there is a need for secure and efficient routing to reach the quality of service.But due to the high cost of the network,WSN components have limited resources to manage the network.There is a need to design a lightweight solution that ensures the quality of service in WSN.In this given manner,this study provides the quality of services in a wireless sensor network with a security mechanism.An incorporated hybrid lightweight security model is designed in which random waypoint mobility(RWM)model and grey wolf optimization(GWO)is used to enhance service quality and maintain security with efficient routing.MATLAB version 16 andNetwork Stimulator 2.35(NS2.35)are used in this research to evaluate the results.The overall cost factor is reduced at 60%without the optimization technique and 90.90%reduced by using the optimization technique,which is assessed by calculating the signal-to-noise ratio,overall energy nodes,and communication overhead.展开更多
文摘Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project.
文摘The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial operations.Ensuring the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network optimization.Network infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node distribution.This work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and design.By using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and exploitation.Through implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network operation.We compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world problems.Being the most efficient in the optimization process,Biruni displays the lowest error rate at 0.00032.The two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific problems.Due to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be made.Through delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.
文摘The Wireless Sensor Networks(WSN)is a self-organizing network with random deployment of wireless nodes that connects each other for effective monitoring and data transmission.The clustering technique employed to group the collection of nodes for data transmission and each node is assigned with a cluster head.The major concern with the identification of the cluster head is the consideration of energy consumption and hence this paper proposes an hybrid model which forms an energy efficient cluster head in the Wireless Sensor Network.The proposed model is a hybridization of Glowworm Swarm Optimization(GSO)and Artificial Bee Colony(ABC)algorithm for the better identification of cluster head.The performance of the proposed model is compared with the existing techniques and an energy analysis is performed and is proved to be more efficient than the existing model with normalized energy of 5.35%better value and reduction of time complexity upto 1.46%.Above all,the proposed model is 16%ahead of alive node count when compared with the existing methodologies.
文摘We consider the extension of network lifetime of battery driven wireless sensor networks by splitting the sensing area into uniform clusters and implementing heterogeneous modulation schemes at different members of the clusters. A cross-layer optimization has been proposed to reduce total energy expenditure of the network;at network layer, routing is done through uniform clusters;at MAC layer, each sensor node of the cluster is assigned fixed or variable time slots and at physical layer different member of the clusters is assigned different modulation techniques. MATLAB simulation proved substantial network lifetime gains.
基金financially supported by the National High Technology and Development Program of China(863):Model-based digital management platform for orchard and rape plants(2013AA102405).
文摘Wireless sensor network(WSN)nodes exchange information via wireless signals,whose power can attenuate at different levels according to the propagation environment.The branches and leaves of young apple trees are much sparser than that of adult apple trees.Propagation rules such as propagation distance and attenuation rate are the parameters necessary to know before applying a WSN to a young apple orchard.Field tests were performed,and propagation distance and packet loss rate(PLR)were computed and compared under the two cases:a young apple orchard in fruit period and an open space to find the effect of the apple trees on radio propagation.A model of antenna height and propagation distance was created to forecast the extra path loss caused by the young trees.Validation experiments were performed in a different young apple orchard,and the validation results showed that 70% of R^(2) were higher than 0.7,while the smallest being 0.65;80% RMSE were smaller than 5.The new model was also compared with some classical models such as Cost 235,FITU,ITU-R,and Weissberger model,and the new model was proved to be the best.
基金partially funded by the Ministry of Science and Higher Education of the Russian Federation as a part of World-class Research Center Program:Advanced Digital Technologies(contract No.075-15-2022-312 dated 20 April 2022).
文摘This work proposes an innovative approach to evaluate the functional characteristics of a heterogeneous underwater wireless acoustic sensor network(UWASN)using a stochastic model and the network connectivity criterion.The connectivity criterion is probabilistic and considers inherently distinct groups of parameters:technical parameters that determine the network function at specific levels of the communication stack and physical parameters that describe the environment in the water area.The proposed approach enables researchers to evaluate the network characteristics in terms of energy efficiency and reliability while considering specific network and environmental parameters.Moreover,this approach is a simple and convenient tool for analyzing the effectiveness of protocols in various open systems interconnection model levels.It is possible to assess the potential capabilities of any protocol and include it in the proposed model.This work presents the results of modeling the critical characteristics of heterogeneous three-dimensional UWASNs of different scales consisting of stationary sensors and a wave glider as a mobile gateway,using specific protocols as examples.Several alternative routes for the wave glider are considered to optimize the network’s functional capabilities.Optimal trajectories of the wave glider’s movement have been determined in terms of ensuring the efficiency and reliability of the hybrid UWASN at various scales.In the context of the problem,an evaluation of different reference node placement was to ensure message transmission to a mobile gateway.The best location of reference nodes has been found.
基金the National High-Tech Research and Development Plan of China (2006AA01Z223)the China Next Generation Internet (CNGI) Plan (2005-2137).
文摘With the development of CMOS and MEMS technologies, the implementation of a large number of wireless distributed micro-sensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad hoc sensor networks. To facilitate ease of deployment, these sensors operate on battery for extended periods of time. A particular challenge in maintaining extended battery lifetime lies in achieving communications with low power. For better understanding of the design tradeoffs of wireless sensor network （WSN）, a more accurate energy model for wireless sensor node is proposed, and an optimal design method of energy efficient wireless sensor node is described as well. Different from power models ever shown which assume the power cost of each component in WSN node is constant, the new one takes into account the energy dissipation of circuits in practical physical layer. It shows that there are some parameters, such as data rate, carrier frequency, bandwidth, Tsw, etc, which have a significant effect on the WSN node energy consumption per useful bit （EPUB）. For a given quality specification, how energy consumption can be reduced by adjusting one or more of these parameters is shown.
基金The authors are thankful to the Deanship of Scientific Research at Najran University for funding this work under the Research Collaboration Funding program grant code NU/RC/SERC/11/7。
文摘In the network field,Wireless Sensor Networks(WSN)contain prolonged attention due to afresh augmentations.Industries like health care,traffic,defense,and many more systems espoused the WSN.These networks contain tiny sensor nodes containing embedded processors,TinyOS,memory,and power source.Sensor nodes are responsible for forwarding the data packets.To manage all these components,there is a need to select appropriate parameters which control the quality of service of WSN.Multiple sensor nodes are involved in transmitting vital information,and there is a need for secure and efficient routing to reach the quality of service.But due to the high cost of the network,WSN components have limited resources to manage the network.There is a need to design a lightweight solution that ensures the quality of service in WSN.In this given manner,this study provides the quality of services in a wireless sensor network with a security mechanism.An incorporated hybrid lightweight security model is designed in which random waypoint mobility(RWM)model and grey wolf optimization(GWO)is used to enhance service quality and maintain security with efficient routing.MATLAB version 16 andNetwork Stimulator 2.35(NS2.35)are used in this research to evaluate the results.The overall cost factor is reduced at 60%without the optimization technique and 90.90%reduced by using the optimization technique,which is assessed by calculating the signal-to-noise ratio,overall energy nodes,and communication overhead.
