At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown ...At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.展开更多
Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This stu...Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.展开更多
1.Introduction It has been almost 60 years since the launch of Intelsat-I,the world’s first commercial satellite communications system.Over the past few decades,the development of satellite communications has been dr...1.Introduction It has been almost 60 years since the launch of Intelsat-I,the world’s first commercial satellite communications system.Over the past few decades,the development of satellite communications has been driven by both technological advancements and growing application demands,which have given rise to three primary services:broadcast,fixed satellite,and mobile satellite services[1].展开更多
In indoor environments,various batterypowered Internet of Things(IoT)devices,such as remote controllers and electronic tags on high-level shelves,require efficient energy management.However,manually monitoring remaini...In indoor environments,various batterypowered Internet of Things(IoT)devices,such as remote controllers and electronic tags on high-level shelves,require efficient energy management.However,manually monitoring remaining energy levels and battery replacement is both inadequate and costly.This paper introduces an energy management system for indoor IoT,which includes a mobile energy station(ES)for enabling on-demand wireless energy transfer(WET)in radio frequency(RF),some energy receivers(ERs),and a cloud server.By implementing a two-stage positioning system and embedding energy receivers into traditional IoT devices,we robustly manage their energy storage.The experimental results demonstrate that the energy receiver can harvest a minimum power of 58 mW.展开更多
During the past few decades,mobile wireless communications have experienced four generations of technological revolution,namely from 1 G to 4 G,and the deployment of the latest 5 G networks is expected to take place i...During the past few decades,mobile wireless communications have experienced four generations of technological revolution,namely from 1 G to 4 G,and the deployment of the latest 5 G networks is expected to take place in 2019.One fundamental question is how we can push forward the development of mobile wireless communications while it has become an extremely complex and sophisticated system.We believe that the answer lies in the huge volumes of data produced by the network itself,and machine learning may become a key to exploit such information.In this paper,we elaborate why the conventional model-based paradigm,which has been widely proved useful in pre-5 G networks,can be less efficient or even less practical in the future 5 G and beyond mobile networks.Then,we explain how the data-driven paradigm,using state-of-the-art machine learning techniques,can become a promising solution.At last,we provide a typical use case of the data-driven paradigm,i.e.,proactive load balancing,in which online learning is utilized to adjust cell configurations in advance to avoid burst congestion caused by rapid traffic changes.展开更多
This paper proposes fault tolerant algorithms for routing mobile agents in a single channel wireless sensor network which cover every node in the network. These algorithms use local knowledge (assume no knowledge of g...This paper proposes fault tolerant algorithms for routing mobile agents in a single channel wireless sensor network which cover every node in the network. These algorithms use local knowledge (assume no knowledge of global deployment or topology, etc). We propose the algorithms and show mathematical analysis to support our claims. The paper ends with simulation studies and discussion of results.展开更多
Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many applications.They provide pervasive computing services and techniques in various potential applications for the...Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many applications.They provide pervasive computing services and techniques in various potential applications for the Internet of Things(IoT).An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism(ACMDGTM)algorithm is proposed which would mitigate the problem of“hot spots”among sensors to enhance the lifetime of networks.The clustering process takes sensors’location and residual energy into consideration to elect suitable cluster heads.Furthermore,one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself.Related experimental results display that the presented method can avoid long distance communicate between sensor nodes.Furthermore,this algorithm reduces energy consumption effectively and improves package delivery rate.展开更多
The unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) architecture is expected to be a powerful technique to facilitate 5 G and beyond ubiquitous wireless connectivity and diverse vertical applications a...The unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) architecture is expected to be a powerful technique to facilitate 5 G and beyond ubiquitous wireless connectivity and diverse vertical applications and services, anytime and anywhere. Wireless power transfer(WPT) is another promising technology to prolong the operation time of low-power wireless devices in the era of Internet of Things(IoT). However, the integration of WPT and UAV-enabled MEC systems is far from being well studied, especially in dynamic environments. In order to tackle this issue, this paper aims to investigate the stochastic computation offloading and trajectory scheduling for the UAV-enabled wireless powered MEC system. A UAV offers both RF wireless power transmission and computation services for IoT devices. Considering the stochastic task arrivals and random channel conditions, a long-term average energyefficiency(EE) minimization problem is formulated.Due to non-convexity and the time domain coupling of the variables in the formulated problem, a lowcomplexity online computation offloading and trajectory scheduling algorithm(OCOTSA) is proposed by exploiting Lyapunov optimization. Simulation results verify that there exists a balance between EE and the service delay, and demonstrate that the system EE performance obtained by the proposed scheme outperforms other benchmark schemes.展开更多
With the rapid development of mobile Internet, people pay increasing attention to the wireless network security problem. But due to the specificity of the wireless network, at present it is rare to see the research of...With the rapid development of mobile Internet, people pay increasing attention to the wireless network security problem. But due to the specificity of the wireless network, at present it is rare to see the research of wireless intrusion alerts clustering method for mobile Internet. This paper proposes a Wireless Intrusion Alert Clustering Method(WIACM) based on the information of the mobile terminal. The method includes alert formatting, alert reduction and alert classification. By introducing key information of the mobile terminal device, this method aggregates the original alerts into hyper alerts. The experimental results show that WIACM would be appropriate for real attack scenarios of mobile Internet, and reduce the amount of alerts with more accuracy of alert analysis.展开更多
At present, most underwater positioning algorithms improve the positioning accuracy by increasing the number of anchor nodes which resulting in the increasing energy consumption. To solve this problem, the paper propo...At present, most underwater positioning algorithms improve the positioning accuracy by increasing the number of anchor nodes which resulting in the increasing energy consumption. To solve this problem, the paper proposes a localization algorithm assisted by mobile anchor node and based on region determination(LMRD), which not only improves the positioning accuracy of nodes positioning but also reduces the energy consumption. This algorithm is divided into two stages: region determination stage and location positioning stage. In the region determination stage, the target region is divided into several sub-regions by the region division strategy with the smallest overlap rate which can reduce the number of virtual anchor nodes and lock the target node to a sub-region, and then through the planning of mobile nodes to optimize the travel path, reduce the moving distance, and reduce system energy consumption. In the location positioning stage, the target node location can be calculated using the HILBERT path planning and trilateration. The simulation results show that the proposed algorithm can improve the positioning accuracy when the energy consumption is reduced.展开更多
The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytica...The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.展开更多
The problem of mobile localization for wireless sensor network has attracted considerable attention in recent years. The localization accuracy will drastically grade in non-line of sight(NLOS) conditions. In this pape...The problem of mobile localization for wireless sensor network has attracted considerable attention in recent years. The localization accuracy will drastically grade in non-line of sight(NLOS) conditions. In this paper, we propose a mobile localization strategy based on Kalman filter. The key technologies for the proposed method are the NLOS identification and mitigation. The proposed method does not need the prior knowledge of the NLOS error and it is independent of the physical measurement ways. Simulation results show that the proposed method owns the higher localization accuracy when compared with other methods.展开更多
Energy conservation in Wireless Sensor Networks (WSNs) has always been a crucial issue and has received increased attention in the recent years. A transmission scheme for energy-constrained WSNs is proposed in this pa...Energy conservation in Wireless Sensor Networks (WSNs) has always been a crucial issue and has received increased attention in the recent years. A transmission scheme for energy-constrained WSNs is proposed in this paper. The scheme, called MIHOP (MIMO and Multi-hop), combines cluster-based virtual MIMO and multi-hop technologies. The multihop mode is employed in transmitting data when the related sensors are located within a specific number of hops from the sink, and the virtual MIMO mode is used in transmitting data from the remaining sensor nodes. We compare the energy consumption of different transmission schemes and propose an algorithm for determining the optimal hop count in MIHOP. A controllable mobile sink that reduces the energy consumed in sensor transmission is also adopted for data collection. The theoretical analysis and the Monte Carlo simulation demonstrate that the proposed scheme significantly outperforms individual virtual MIMO, multi-hop technologies, and double-string networks in terms of energy conservation. The energy consumption levels under the MIHOP scheme are approximately 12.98%, 47.55% and 48.30% less than that under virtual MIMO schemes, multi-hop networks and doublestring networks, respectively.展开更多
In 5G era,it is expected to achieve wireless network coverage including offshore areas.Modeling of marine wireless channels is the basis of constructing a marine communication system.In this paper,a communication scen...In 5G era,it is expected to achieve wireless network coverage including offshore areas.Modeling of marine wireless channels is the basis of constructing a marine communication system.In this paper,a communication scene between an unmanned aerial vehicle(UAV)and a boat is simulated to study the marine wireless channel.Firstly,an improved spatial partitioning ray tracing algorithm is proposed to track the propagation path of electromagnetic waves at sea surface.Secondly,a mobile channel is simulated and modeled based on the track results.Finally,a loss measurement is carried out in the coastal waters based on the simple wireless channel loss measuring platform,and a path loss propagation model is built.Then we compare the actual measurement data with the simulation results and find that the two are have good consistency,which further verifies the reliability of the simulation.展开更多
Millimeter-wave(mm Wave) communications will be used in fifth-generation(5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell ra...Millimeter-wave(mm Wave) communications will be used in fifth-generation(5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell radii and complicated network architectures. A coverage extension scheme using large-scale antenna arrays(LSAAs) has been suggested and theoretically proven to be cost-efficient in combination with ultradense small cell networks. To analyze and optimize the LSAA-based network deployments, a comprehensive survey of recent advances in statistical mmWave channel modeling is first presented in terms of channel parameter estimation, large-scale path loss models, and small-scale cluster models. Next, the measurement and modeling results at two 5G candidate mmWave bands(e.g., 28 GHz and 39 GHz) are reviewed and compared in several outdoor scenarios of interest, where the propagation characteristics make crucial contributions to wireless network designs. Finally, the coverage behaviors of systems employing a large number of antenna arrays are discussed, as well as some implications on future mmWave cellular network designs.展开更多
Wireless sensor networks （WSNs） are based on monitoring or managing the sensing area by using the location information with sensor nodes. Most sensor nodes require hardware support or receive packets with location i...Wireless sensor networks （WSNs） are based on monitoring or managing the sensing area by using the location information with sensor nodes. Most sensor nodes require hardware support or receive packets with location information to estimate their locations, which needs lots of time or costs. In this paper we proposed a localization mechanism using a mobile reference node （MRN） and trilateration in WSNs to reduce the energy consumption and location error. The simulation results demonstrate that the proposed mechanism can obtain more unknown nodes locations by the mobile reference node moving scheme and will decreases the energy consumption and average ocation error.展开更多
The mobile object (MO) location determination technologies which can be used in intelligent transportation system (ITS) are studied in this paper. The principles and characteristics of wireless location determination ...The mobile object (MO) location determination technologies which can be used in intelligent transportation system (ITS) are studied in this paper. The principles and characteristics of wireless location determination technologies are introduced and the characteristics of GSM useful for location determination are also summarized. An experimental positioning system based on GSM is proposed, and the architecture is described. TOA method based on GSM signals and TDOA method are used in the experimental system. Moreover, the methods are simulated. The performance of the positioning methods is assessed in the simulation environment, and the accuracy for 67% mobile stations (MS) is 70m in urban areas.展开更多
Remote tracking for mobile targets is one of the most important applications in wireless sensor networks （WSNs）. A target tracking protoco–exponential distributed predictive tracking （EDPT） is proposed. To reduce...Remote tracking for mobile targets is one of the most important applications in wireless sensor networks （WSNs）. A target tracking protoco–exponential distributed predictive tracking （EDPT） is proposed. To reduce energy waste and response time, an improved predictive algorithm–exponential smoothing predictive algorithm （ESPA） is presented. With the aid of an additive proportion and differential （PD） controller, ESPA decreases the system predictive delay effectively. As a recovery mechanism, an optimal searching radius （OSR） algorithm is applied to calculate the optimal radius of the recovery zone. The simulation results validate that the proposed EDPT protocol performes better in terms of track failed ratio, energy waste ratio and enlarged sensing nodes ratio, respectively.展开更多
文摘At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.
基金supported by the Malaysia Ministry of Higher Education under Fundamental Research Grant Scheme with Project Code:FRGS/1/2024/TK07/USM/02/3.
文摘Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.
基金supported in part by the National Key Research and Development Program of China(2023YFB2904703).
文摘1.Introduction It has been almost 60 years since the launch of Intelsat-I,the world’s first commercial satellite communications system.Over the past few decades,the development of satellite communications has been driven by both technological advancements and growing application demands,which have given rise to three primary services:broadcast,fixed satellite,and mobile satellite services[1].
基金supported in part by the Natural Science Foundation of China(NSFC)under Grant 61971102in part by the Key Research and Development Program of Zhejiang Province under Grant 2022C01093.
文摘In indoor environments,various batterypowered Internet of Things(IoT)devices,such as remote controllers and electronic tags on high-level shelves,require efficient energy management.However,manually monitoring remaining energy levels and battery replacement is both inadequate and costly.This paper introduces an energy management system for indoor IoT,which includes a mobile energy station(ES)for enabling on-demand wireless energy transfer(WET)in radio frequency(RF),some energy receivers(ERs),and a cloud server.By implementing a two-stage positioning system and embedding energy receivers into traditional IoT devices,we robustly manage their energy storage.The experimental results demonstrate that the energy receiver can harvest a minimum power of 58 mW.
基金partially supported by the National Natural Science Foundation of China(61751306,61801208,61671233)the Jiangsu Science Foundation(BK20170650)+2 种基金the Postdoctoral Science Foundation of China(BX201700118,2017M621712)the Jiangsu Postdoctoral Science Foundation(1701118B)the Fundamental Research Funds for the Central Universities(021014380094)
文摘During the past few decades,mobile wireless communications have experienced four generations of technological revolution,namely from 1 G to 4 G,and the deployment of the latest 5 G networks is expected to take place in 2019.One fundamental question is how we can push forward the development of mobile wireless communications while it has become an extremely complex and sophisticated system.We believe that the answer lies in the huge volumes of data produced by the network itself,and machine learning may become a key to exploit such information.In this paper,we elaborate why the conventional model-based paradigm,which has been widely proved useful in pre-5 G networks,can be less efficient or even less practical in the future 5 G and beyond mobile networks.Then,we explain how the data-driven paradigm,using state-of-the-art machine learning techniques,can become a promising solution.At last,we provide a typical use case of the data-driven paradigm,i.e.,proactive load balancing,in which online learning is utilized to adjust cell configurations in advance to avoid burst congestion caused by rapid traffic changes.
文摘This paper proposes fault tolerant algorithms for routing mobile agents in a single channel wireless sensor network which cover every node in the network. These algorithms use local knowledge (assume no knowledge of global deployment or topology, etc). We propose the algorithms and show mathematical analysis to support our claims. The paper ends with simulation studies and discussion of results.
基金This work is supported by the National Natural Science Foundation of China(61772454,61811530332,61811540410,U1836208).
文摘Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many applications.They provide pervasive computing services and techniques in various potential applications for the Internet of Things(IoT).An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism(ACMDGTM)algorithm is proposed which would mitigate the problem of“hot spots”among sensors to enhance the lifetime of networks.The clustering process takes sensors’location and residual energy into consideration to elect suitable cluster heads.Furthermore,one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself.Related experimental results display that the presented method can avoid long distance communicate between sensor nodes.Furthermore,this algorithm reduces energy consumption effectively and improves package delivery rate.
基金supported in part by the U.S. National Science Foundation under Grant CNS-2007995in part by the National Natural Science Foundation of China under Grant 92067201,62171231in part by Jiangsu Provincial Key Research and Development Program under Grant BE2020084-1。
文摘The unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) architecture is expected to be a powerful technique to facilitate 5 G and beyond ubiquitous wireless connectivity and diverse vertical applications and services, anytime and anywhere. Wireless power transfer(WPT) is another promising technology to prolong the operation time of low-power wireless devices in the era of Internet of Things(IoT). However, the integration of WPT and UAV-enabled MEC systems is far from being well studied, especially in dynamic environments. In order to tackle this issue, this paper aims to investigate the stochastic computation offloading and trajectory scheduling for the UAV-enabled wireless powered MEC system. A UAV offers both RF wireless power transmission and computation services for IoT devices. Considering the stochastic task arrivals and random channel conditions, a long-term average energyefficiency(EE) minimization problem is formulated.Due to non-convexity and the time domain coupling of the variables in the formulated problem, a lowcomplexity online computation offloading and trajectory scheduling algorithm(OCOTSA) is proposed by exploiting Lyapunov optimization. Simulation results verify that there exists a balance between EE and the service delay, and demonstrate that the system EE performance obtained by the proposed scheme outperforms other benchmark schemes.
基金partially supported by the Zhejiang Provincial Natural Science Foundation of China(No.LY16F020010)the Zhejiang Key Discipline Fund of Computer Applied Technology(No.pd2013457)the Hangzhou Science&Technology Development Project of China(No.20140533B13)
文摘With the rapid development of mobile Internet, people pay increasing attention to the wireless network security problem. But due to the specificity of the wireless network, at present it is rare to see the research of wireless intrusion alerts clustering method for mobile Internet. This paper proposes a Wireless Intrusion Alert Clustering Method(WIACM) based on the information of the mobile terminal. The method includes alert formatting, alert reduction and alert classification. By introducing key information of the mobile terminal device, this method aggregates the original alerts into hyper alerts. The experimental results show that WIACM would be appropriate for real attack scenarios of mobile Internet, and reduce the amount of alerts with more accuracy of alert analysis.
基金supported by National Natural Science Foundation of China (Nos. U1806201, 61671261)Key Research and Development Program of Shandong Province (No. 2016GGX101007)+1 种基金China Postdoctoral Science Foundation (No. 2017T100490)University Science and Technology Planning Project of Shandong Province (Nos. J17KA058, J17KB154)
文摘At present, most underwater positioning algorithms improve the positioning accuracy by increasing the number of anchor nodes which resulting in the increasing energy consumption. To solve this problem, the paper proposes a localization algorithm assisted by mobile anchor node and based on region determination(LMRD), which not only improves the positioning accuracy of nodes positioning but also reduces the energy consumption. This algorithm is divided into two stages: region determination stage and location positioning stage. In the region determination stage, the target region is divided into several sub-regions by the region division strategy with the smallest overlap rate which can reduce the number of virtual anchor nodes and lock the target node to a sub-region, and then through the planning of mobile nodes to optimize the travel path, reduce the moving distance, and reduce system energy consumption. In the location positioning stage, the target node location can be calculated using the HILBERT path planning and trilateration. The simulation results show that the proposed algorithm can improve the positioning accuracy when the energy consumption is reduced.
基金Project(60873081)supported by the National Natural Science Foundation of ChinaProject(NCET-10-0787)supported by Program for New Century Excellent Talents in UniversityProject(11JJ1012)supported by the Natural Science Foundation of Hunan Province,China
文摘The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.
基金supported by the National Natural Science Foundation of China under Grant No. 61403068, No. 61232016, No. U1405254 and No. 61501100Fundamental Research Funds for the Central Universities of China under Grant No. N130323002 and No. N130323004+3 种基金Natural Science Foundation of Hebei Province under Grant No. F2015501097 and No. F2016501080Scientific Research Fund of Hebei Provincial Education Department under Grant No. Z2014078the PAPD fundNEUQ internal funding under Grant No. XNB201509 and XNB201510
文摘The problem of mobile localization for wireless sensor network has attracted considerable attention in recent years. The localization accuracy will drastically grade in non-line of sight(NLOS) conditions. In this paper, we propose a mobile localization strategy based on Kalman filter. The key technologies for the proposed method are the NLOS identification and mitigation. The proposed method does not need the prior knowledge of the NLOS error and it is independent of the physical measurement ways. Simulation results show that the proposed method owns the higher localization accuracy when compared with other methods.
基金funded by National Natural Science Foundation of China under Grant No.61171107Beijing Natural Science Foundation under Grant No.4122034+1 种基金863 Program of China under Grant No.2011AA100706the Fundamental Research Funds for the Central Universities under Grant No.G470519
文摘Energy conservation in Wireless Sensor Networks (WSNs) has always been a crucial issue and has received increased attention in the recent years. A transmission scheme for energy-constrained WSNs is proposed in this paper. The scheme, called MIHOP (MIMO and Multi-hop), combines cluster-based virtual MIMO and multi-hop technologies. The multihop mode is employed in transmitting data when the related sensors are located within a specific number of hops from the sink, and the virtual MIMO mode is used in transmitting data from the remaining sensor nodes. We compare the energy consumption of different transmission schemes and propose an algorithm for determining the optimal hop count in MIHOP. A controllable mobile sink that reduces the energy consumed in sensor transmission is also adopted for data collection. The theoretical analysis and the Monte Carlo simulation demonstrate that the proposed scheme significantly outperforms individual virtual MIMO, multi-hop technologies, and double-string networks in terms of energy conservation. The energy consumption levels under the MIHOP scheme are approximately 12.98%, 47.55% and 48.30% less than that under virtual MIMO schemes, multi-hop networks and doublestring networks, respectively.
基金National Natural Science Foundation of China(Grant number 61971365)National Natural Science Foundation of China(Grant number 61871339)+1 种基金National Natural Science Foundation of China(Grant number 61901403)Xiamen Science and Technology Plan Project(No.3502Z20183008).
文摘In 5G era,it is expected to achieve wireless network coverage including offshore areas.Modeling of marine wireless channels is the basis of constructing a marine communication system.In this paper,a communication scene between an unmanned aerial vehicle(UAV)and a boat is simulated to study the marine wireless channel.Firstly,an improved spatial partitioning ray tracing algorithm is proposed to track the propagation path of electromagnetic waves at sea surface.Secondly,a mobile channel is simulated and modeled based on the track results.Finally,a loss measurement is carried out in the coastal waters based on the simple wireless channel loss measuring platform,and a path loss propagation model is built.Then we compare the actual measurement data with the simulation results and find that the two are have good consistency,which further verifies the reliability of the simulation.
基金supported in part by the National Natural Science Foundation of China under Grant No.61671145the Key R&D Program of Jiangsu Province of China under Grant BE2018121
文摘Millimeter-wave(mm Wave) communications will be used in fifth-generation(5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell radii and complicated network architectures. A coverage extension scheme using large-scale antenna arrays(LSAAs) has been suggested and theoretically proven to be cost-efficient in combination with ultradense small cell networks. To analyze and optimize the LSAA-based network deployments, a comprehensive survey of recent advances in statistical mmWave channel modeling is first presented in terms of channel parameter estimation, large-scale path loss models, and small-scale cluster models. Next, the measurement and modeling results at two 5G candidate mmWave bands(e.g., 28 GHz and 39 GHz) are reviewed and compared in several outdoor scenarios of interest, where the propagation characteristics make crucial contributions to wireless network designs. Finally, the coverage behaviors of systems employing a large number of antenna arrays are discussed, as well as some implications on future mmWave cellular network designs.
文摘Wireless sensor networks （WSNs） are based on monitoring or managing the sensing area by using the location information with sensor nodes. Most sensor nodes require hardware support or receive packets with location information to estimate their locations, which needs lots of time or costs. In this paper we proposed a localization mechanism using a mobile reference node （MRN） and trilateration in WSNs to reduce the energy consumption and location error. The simulation results demonstrate that the proposed mechanism can obtain more unknown nodes locations by the mobile reference node moving scheme and will decreases the energy consumption and average ocation error.
文摘The mobile object (MO) location determination technologies which can be used in intelligent transportation system (ITS) are studied in this paper. The principles and characteristics of wireless location determination technologies are introduced and the characteristics of GSM useful for location determination are also summarized. An experimental positioning system based on GSM is proposed, and the architecture is described. TOA method based on GSM signals and TDOA method are used in the experimental system. Moreover, the methods are simulated. The performance of the positioning methods is assessed in the simulation environment, and the accuracy for 67% mobile stations (MS) is 70m in urban areas.
基金supported by the National Basic Research Program of China (973 Program) (2010CB731800)the National Natural Science Foundation of China (60934003+2 种基金 60974123 60804010)the Hebei Provincial Educational Foundation of China (2008147)
文摘Remote tracking for mobile targets is one of the most important applications in wireless sensor networks （WSNs）. A target tracking protoco–exponential distributed predictive tracking （EDPT） is proposed. To reduce energy waste and response time, an improved predictive algorithm–exponential smoothing predictive algorithm （ESPA） is presented. With the aid of an additive proportion and differential （PD） controller, ESPA decreases the system predictive delay effectively. As a recovery mechanism, an optimal searching radius （OSR） algorithm is applied to calculate the optimal radius of the recovery zone. The simulation results validate that the proposed EDPT protocol performes better in terms of track failed ratio, energy waste ratio and enlarged sensing nodes ratio, respectively.
