To efficiently complete a complex computation task,the complex task should be decomposed into subcomputation tasks that run parallel in edge computing.Wireless Sensor Network(WSN)is a typical application of parallel c...To efficiently complete a complex computation task,the complex task should be decomposed into subcomputation tasks that run parallel in edge computing.Wireless Sensor Network(WSN)is a typical application of parallel computation.To achieve highly reliable parallel computation for wireless sensor network,the network's lifetime needs to be extended.Therefore,a proper task allocation strategy is needed to reduce the energy consumption and balance the load of the network.This paper proposes a task model and a cluster-based WSN model in edge computing.In our model,different tasks require different types of resources and different sensors provide different types of resources,so our model is heterogeneous,which makes the model more practical.Then we propose a task allocation algorithm that combines the Genetic Algorithm(GA)and the Ant Colony Optimization(ACO)algorithm.The algorithm concentrates on energy conservation and load balancing so that the lifetime of the network can be extended.The experimental result shows the algorithm's effectiveness and advantages in energy conservation and load balancing.展开更多
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 researc...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.展开更多
The first tier of automotive manufacturers has faced to pressures about move,modify,updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor compan...The first tier of automotive manufacturers has faced to pressures about move,modify,updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements,it has to require absolutely lead time to re-wiring of physical interface for production equipment,needs for change existing program and test over again.For prepare this constraints,it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M(Man,Machine,Material, Method)group management which is supports from WSN (Wireless Sensor Network)of the open embedded device called M2M(Machine to Machine)and major functions of middleware including point manager for real-time device communication,real-time data management,Standard API (Application Program Interface)and application template management.To be application system to RMS (Reconfigurable Manufacturing System)for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.展开更多
Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware sol...Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware solution, In-Motes. In-Motes stands as a fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort the deployed applications to run in an energy efficient manner inside the network. The proposed scheme is evaluated through the In-Motes EYE application, aiming to test its merits under real time conditions. In-Motes EYE application which is an agent based real time In-Motes application developed for sensing acceleration variations in an environment. The application was tested in a prototype area, road alike, for a period of four months.展开更多
The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor comp...The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements, it has to require absolutely lead time to re-wiring of physical interface for production equipment, needs for change existing program and test over again. For prepare this constraints, it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M (Man, Machine, Material, Method) group management which is supports from WSN (Wireless Sensor Network) of the open embedded device called M2M (Machine to Machine) and major functions of middleware including point manager for real-time device communication, real-time data management, Standard API (Application Program Interface) and application template management. To be application system to RMS (Reconfigurable Manufacturing System) for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.展开更多
Wireless Sensor Networks （WSNs） have found more and more applications in a variety of pervasive computing environments. However, how to support the development, maintenance, deployment and execution of applications ...Wireless Sensor Networks （WSNs） have found more and more applications in a variety of pervasive computing environments. However, how to support the development, maintenance, deployment and execution of applications over WSNs remains to be a nontrivial and challenging task, mainly because of the gap between the high level requirements from pervasive computing applications and the underlying operation of WSNs. Middleware for WSN can help bridge the gap and remove impediments. In recent years, research has been carried out on WSN middleware from different aspects and for different purposes. In this paper, we provide a comprehensive review of the existing work on WSN middleware, seeking for a better understanding of the current issues and future directions in this field. We propose a reference framework to analyze the functionalities of WSN middleware in terms of the system abstractions and the services provided. We review the approaches and techniques for implementing the services. On the basis of the analysis and by using a feature tree, we provide taxonomy of the features of WSN middleware and their relationships, and use the taxonomy to classify and evaluate existing work. We also discuss open problems in this important area of research.展开更多
The Random Decrement Technique （RDT）, based on decentralized computing approaches implemented in wireless sensor networks （WSNs）, has shown advantages for modal parameter and data aggregation identification. Howev...The Random Decrement Technique （RDT）, based on decentralized computing approaches implemented in wireless sensor networks （WSNs）, has shown advantages for modal parameter and data aggregation identification. However, previous studies of RDT-based approaches from ambient vibration data are based on the assumption of a broad-band stochastic process input excitation. The process normally is modeled by filtered white or white noise. In addition, the choice of the triggering condition in RDT is closely related to data communication. In this project, research has been conducted to study the nonstationary white noise excitations as the input to verify the random decrement technique. A local extremum triggering condition is chosen and implemented for the purpose of minimum data communication in a RDT-based distributed computing strategy. Numerical simulation results show that the proposed technique is capable of minimizing the amount of data transmitted over the network with accuracy in modal parameters identification.展开更多
The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance.The longevity of the networks is mostly determined by the proportion of energy consumed and t...The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance.The longevity of the networks is mostly determined by the proportion of energy consumed and the sensor nodes’access network.The optimal or ideal positioning of sensors improves the portable sensor networks effectiveness.Coverage and energy usage are mostly determined by successful sensor placement strategies.Nature-inspired algorithms are the most effective solution for short sensor lifetime.The primary objective of work is to conduct a comparative analysis of nature-inspired optimization for wireless sensor networks(WSNs’)maximum network coverage.Moreover,it identifies quantity of installed sensor nodes for the given area.Superiority of algorithm has been identified based on value of optimized energy.The first half of the paper’s literature on nature-inspired algorithms is discussed.Later six metaheuristics algorithms(Grey wolf,Ant lion,Dragonfly,Whale,Moth flame,Sine cosine optimizer)are compared for optimal coverage of WSNs.The simulation outcomes confirm that whale opti-mization algorithm(WOA)gives optimized Energy with improved network coverage with the least number of nodes.This comparison will be helpful for researchers who will use WSNs in their applications.展开更多
The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure ...The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure domains like oil and gas supply,intelligent transportation,power grids,and autonomous agriculture,it is essential to guarantee the confidentiality,integrity,and authenticity of data collected and exchanged.However,the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques.Consequently,designing a lightweight secure data transmission scheme is becoming essential.In this article,we propose lightweight secure data transmission(LSDT)scheme for IoT environments.LSDT consists of three phases and utilizes an effective combination of symmetric keys and the Elliptic Curve Menezes-Qu-Vanstone asymmetric key agreement protocol.We design the simulation environment and experiments to evaluate the performance of the LSDT scheme in terms of communication and computation costs.Security and performance analysis indicates that the LSDT scheme is secure,suitable for IoT applications,and performs better in comparison to other related security schemes.展开更多
Established on the Intel Multi-Core Embedded platform, using 802.11 Wireless Network protocols as the communication medium, combining with Radio Frequency-Communication and Ultrasonic Ranging, imple-ment a mobile term...Established on the Intel Multi-Core Embedded platform, using 802.11 Wireless Network protocols as the communication medium, combining with Radio Frequency-Communication and Ultrasonic Ranging, imple-ment a mobile terminal system in an intellectualized building. It can provide its holder such functions: 1) Accurate Positioning 2) Intelligent Navigation 3) Video Monitoring 4) Wireless Communication. The inno-vative point for this paper is to apply the multi-core computing on the embedded system to promote its com-puting speed and give a real-time performance and apply this system into the indoor environment for the purpose of emergent event or rescuing.展开更多
In Wireless Sensor Networks (WSNs), it is necessary to predict computational overheads of security mechanisms without final implementations to provide guidelines for system design. This paper presents an accurate and ...In Wireless Sensor Networks (WSNs), it is necessary to predict computational overheads of security mechanisms without final implementations to provide guidelines for system design. This paper presents an accurate and flexible model to predict overheads of these mechanisms. This model is based on overheads of basic operations frequently used in cryptography algorithms, which are essential elements of security mechanisms. Several popular cryptography algorithms and security mechanisms are evaluated using this model. According to simulation results, relative prediction errors are less than 7% for most cryptography algorithms and security mechanisms.展开更多
Sensor networks are dense wireless networks of small, low-cost sensors, which collect and disseminate en-vironmental data. Wireless sensor networks facilitate monitoring and controlling of physical environments from r...Sensor networks are dense wireless networks of small, low-cost sensors, which collect and disseminate en-vironmental data. Wireless sensor networks facilitate monitoring and controlling of physical environments from remote locations with better accuracy. They have applications in a variety of fields such as environ-mental monitoring;military purposes and gathering sensing information in inhospitable locations. Sensor nodes have various energy and computational constraints because of their inexpensive nature and adhoc method of deployment. Considerable research has been focused at overcoming these deficiencies through more energy efficient routing, localization algorithms and system design. Our survey presents the funda-mentals of wireless sensor network, thus providing the necessary background required for understanding the organization, functionality and limitations of those networks. The middleware solution is also investigated through a critical presentation and analysis of some of the most well established approaches.展开更多
Numerous privacy-preserving issues have emerged along with the fast development of the Internet of Things. In addressing privacy protection problems in Wireless Sensor Networks （WSN）, secure multi-party computation ...Numerous privacy-preserving issues have emerged along with the fast development of the Internet of Things. In addressing privacy protection problems in Wireless Sensor Networks （WSN）, secure multi-party computation is considered vital, where obtaining the Euclidian distance between two nodes with no disclosure of either side＇s secrets has become the focus of location-privacy-related applications. This paper proposes a novel Privacy-Preserving Scalar Product Protocol （PPSPP） for wireless sensor networks. Based on PPSPP, we then propose a Homomorphic-Encryption-based Euclidean Distance Protocol （HEEDP） without third parties. This protocol can achieve secure distance computation between two sensor nodes. Correctness proofs of PPSPP and HEEDP are provided, followed by security validation and analysis. Performance evaluations via comparisons among similar protocols demonstrate that HEEDP is superior; it is most efficient in terms of both communication and computation on a wide range of data types, especially in wireless sensor networks.展开更多
The concept of Network Centric Therapy represents an amalgamation of wearable and wireless inertial sensor systems and machine learning with access to a Cloud computing environment. The advent of Network Centric Thera...The concept of Network Centric Therapy represents an amalgamation of wearable and wireless inertial sensor systems and machine learning with access to a Cloud computing environment. The advent of Network Centric Therapy is highly relevant to the treatment of Parkinson’s disease through deep brain stimulation. Originally wearable and wireless systems for quantifying Parkinson’s disease involved the use a smartphone to quantify hand tremor. Although originally novel, the smartphone has notable issues as a wearable application for quantifying movement disorder tremor. The smartphone has evolved in a pathway that has made the smartphone progressively more cumbersome to mount about the dorsum of the hand. Furthermore, the smartphone utilizes an inertial sensor package that is not certified for medical analysis, and the trial data access a provisional Cloud computing environment through an email account. These concerns are resolved with the recent development of a conformal wearable and wireless inertial sensor system. This conformal wearable and wireless system mounts to the hand with the profile of a bandage by adhesive and accesses a secure Cloud computing environment through a segmented wireless connectivity strategy involving a smartphone and tablet. Additionally, the conformal wearable and wireless system is certified by the FDA of the United States of America for ascertaining medical grade inertial sensor data. These characteristics make the conformal wearable and wireless system uniquely suited for the quantification of Parkinson’s disease treatment through deep brain stimulation. Preliminary evaluation of the conformal wearable and wireless system is demonstrated through the differentiation of deep brain stimulation set to “On” and “Off” status. Based on the robustness of the acceleration signal, this signal was selected to quantify hand tremor for the prescribed deep brain stimulation settings. Machine learning classification using the Waikato Environment for Knowledge Analysis (WEKA) was applied using the multilayer perceptron neural network. The multilayer perceptron neural network achieved considerable classification accuracy for distinguishing between the deep brain stimulation system set to “On” and “Off” status through the quantified acceleration signal data obtained by this recently developed conformal wearable and wireless system. The research achievement establishes a progressive pathway to the future objective of achieving deep brain stimulation capabilities that promote closed-loop acquisition of configuration parameters that are uniquely optimized to the individual through extrinsic means of a highly conformal wearable and wireless inertial sensor system and machine learning with access to Cloud computing resources.展开更多
Traditional Wireless Sensor Networks(WSNs)comprise of costeffective sensors that can send physical parameters of the target environment to an intended user.With the evolution of technology,multimedia sensor nodes have...Traditional Wireless Sensor Networks(WSNs)comprise of costeffective sensors that can send physical parameters of the target environment to an intended user.With the evolution of technology,multimedia sensor nodes have become the hot research topic since it can continue gathering multimedia content and scalar from the target domain.The existence of multimedia sensors,integrated with effective signal processing and multimedia source coding approaches,has led to the increased application of Wireless Multimedia Sensor Network(WMSN).This sort of network has the potential to capture,transmit,and receive multimedia content.Since energy is a major source in WMSN,novel clustering approaches are essential to deal with adaptive topologies of WMSN and prolonged network lifetime.With this motivation,the current study develops an Enhanced Spider Monkey Optimization-based Energy-Aware Clustering Scheme(ESMO-EACS)for WMSN.The proposed ESMO-EACS model derives ESMO algorithm by incorporating the concepts of SMO algorithm and quantum computing.The proposed ESMO-EACS model involves the design of fitness functions using distinct input parameters for effective construction of clusters.A comprehensive experimental analysis was conducted to validate the effectiveness of the proposed ESMO-EACS technique in terms of different performance measures.The simulation outcome established the superiority of the proposed ESMO-EACS technique to other methods under various measures.展开更多
Node localization is a fundamental problem in wireless sensor network.There are many existing algorithms to estimate the locations of the nodes.However,most of the methods did not consider the presence of obstacles.In...Node localization is a fundamental problem in wireless sensor network.There are many existing algorithms to estimate the locations of the nodes.However,most of the methods did not consider the presence of obstacles.In practice,obstacles will lead to blockage and reflection of communication signals between sensor nodes.Therefore,the presence of obstacles will greatly affect the localization result.In this paper,we implement an obstacle-handling algorithm based on the localization tool developed by MIT,The experimental result shows that the enhanced algorithm can reduce the average distance error by up to 46 %,compared to the original algorithm.展开更多
Wireless networks are key enablers of ubiquitous communication. With the evolution of networking technologies and the need for these to inter-operate and dynamically adapt to user requirements, intelligent networks ar...Wireless networks are key enablers of ubiquitous communication. With the evolution of networking technologies and the need for these to inter-operate and dynamically adapt to user requirements, intelligent networks are the need of the hour. Use of machine learning techniques allows these networks to adapt to changing environments and enables them to make decisions while continuing to learn about their environment. In this paper, we survey the various problems of wireless networks that have been solved using machine-learning based prediction techniques and identify additional problems to which prediction can be applied. We also look at the gaps in the research done in this area till date.展开更多
Artificial intelligence(AI)techniques have received significant attention among research communities in the field of networking,image processing,natural language processing,robotics,etc.At the same time,a major proble...Artificial intelligence(AI)techniques have received significant attention among research communities in the field of networking,image processing,natural language processing,robotics,etc.At the same time,a major problem in wireless sensor networks(WSN)is node localization,which aims to identify the exact position of the sensor nodes(SN)using the known position of several anchor nodes.WSN comprises a massive number of SNs and records the position of the nodes,which becomes a tedious process.Besides,the SNs might be subjected to node mobility and the position alters with time.So,a precise node localization(NL)manner is required for determining the location of the SNs.In this view,this paper presents a new quantum bird migration optimizer-based NL(QBMA-NL)technique for WSN.The goal of the QBMA-NL approach is for determining the position of unknown nodes in the network by the use of anchor nodes.The QBMA-NL technique is mainly based on the mating behavior of bird species at the time of mating season.In addition,an objective function is derived based on the received signal strength indicator(RSSI)and Euclidean distance from the known to unknown SNs.For demonstrating the improved performance of the QBMA-NL technique,a wide range of simulations take place and the results reported the supreme performance over the recent NL techniques.展开更多
The identification of an effective network which can efficiently meet the service requirements of the target,while maintaining ultimate performance at an increased level is significant and challenging in a fully inter...The identification of an effective network which can efficiently meet the service requirements of the target,while maintaining ultimate performance at an increased level is significant and challenging in a fully interconnected wireless medium.The wrong selection can contribute to unwanted situations like frustrated users,slow service,traffic congestion issues,missed and/or interrupted calls,and wastefulness of precious network components.Conventional schemes estimate the handoff need and cause the network screening process by a single metric.The strategies are not effective enough because traffic characteristics,user expectations,network terminology and other essential device metrics are not taken into account.This article describes an intelligent computing technique based on Multiple-Criteria Decision-Making(MCDM)approach developed based on integrated Fuzzy AHP-TOPSIS which ensures flexible usability and maximizes the experience of end-users in miscellaneous wireless settings.In different components the handover need is assessed and the desired network is chosen.Further,fuzzy sets provide effective solutions to address decision making problems where experts counter uncertainty to make a decision.The proposed research endeavor will support designers and developers to identify,select and prioritize best attributes for ensuring flexible usability in miscellaneous wireless settings.The results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the usability and experience of end-users.展开更多
Once deployed, sensor networks are capable of providing a comprehensive view of their environment. However, since the current sensor network paradigm promotes isolated networks that are statically tasked, the full pow...Once deployed, sensor networks are capable of providing a comprehensive view of their environment. However, since the current sensor network paradigm promotes isolated networks that are statically tasked, the full power of the harnessed data has yet to be exploited. In recent years, users have become mobile enti-ties that require constant access to data for efficient and autonomous processing. Under the current limita-tions of sensor networks, users would be restricted using only a subset of the vast amount of data being col-lected;depending on the networks they are able to access. Through reliance on isolated networks, prolifera-tion of sensor nodes can easily occur in any area that has high appeals to users. Furthermore, support for dy-namic tasking of nodes and efficient processing of data is contrary to the general view of sensor networks as subject to severe resource constraints. Addressing the aforementioned challenges requires the deployment of a system that allows users to take full advantage of data collected in the area of interest to their tasks. Such a system must enable interoperability of surrounding networks, support dynamic tasking, and swiftly react to stimuli. In light of these observations, we introduce a hardware-overlay system designed to allow users to efficiently collect and utilize data from various heterogeneous sensor networks. The hardware-overlay takes advantage of FPGA devices and the mobile agent paradigm in order to efficiently collect and process data from cooperating networks. The computational and power efficiency of the prototyped system are herein demonstrated. Furthermore, as a proof-of-concept, we present the implementation of a distributed and autonomous visual object tracker implemented atop the Reconfigurable and Interoperable Sensor Network (RISN) showcasing the network’s ability to support ad-hoc agent networks dedicated to user’s tasks.展开更多
基金supported by Postdoctoral Science Foundation of China(No.2021M702441)National Natural Science Foundation of China(No.61871283)。
文摘To efficiently complete a complex computation task,the complex task should be decomposed into subcomputation tasks that run parallel in edge computing.Wireless Sensor Network(WSN)is a typical application of parallel computation.To achieve highly reliable parallel computation for wireless sensor network,the network's lifetime needs to be extended.Therefore,a proper task allocation strategy is needed to reduce the energy consumption and balance the load of the network.This paper proposes a task model and a cluster-based WSN model in edge computing.In our model,different tasks require different types of resources and different sensors provide different types of resources,so our model is heterogeneous,which makes the model more practical.Then we propose a task allocation algorithm that combines the Genetic Algorithm(GA)and the Ant Colony Optimization(ACO)algorithm.The algorithm concentrates on energy conservation and load balancing so that the lifetime of the network can be extended.The experimental result shows the algorithm's effectiveness and advantages in energy conservation and load balancing.
文摘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.
基金supported by the Industry Foundation project from the Ministry of Knowledge Economy in the Korean Government.
文摘The first tier of automotive manufacturers has faced to pressures about move,modify,updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements,it has to require absolutely lead time to re-wiring of physical interface for production equipment,needs for change existing program and test over again.For prepare this constraints,it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M(Man,Machine,Material, Method)group management which is supports from WSN (Wireless Sensor Network)of the open embedded device called M2M(Machine to Machine)and major functions of middleware including point manager for real-time device communication,real-time data management,Standard API (Application Program Interface)and application template management.To be application system to RMS (Reconfigurable Manufacturing System)for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.
文摘Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware solution, In-Motes. In-Motes stands as a fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort the deployed applications to run in an energy efficient manner inside the network. The proposed scheme is evaluated through the In-Motes EYE application, aiming to test its merits under real time conditions. In-Motes EYE application which is an agent based real time In-Motes application developed for sensing acceleration variations in an environment. The application was tested in a prototype area, road alike, for a period of four months.
文摘The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements, it has to require absolutely lead time to re-wiring of physical interface for production equipment, needs for change existing program and test over again. For prepare this constraints, it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M (Man, Machine, Material, Method) group management which is supports from WSN (Wireless Sensor Network) of the open embedded device called M2M (Machine to Machine) and major functions of middleware including point manager for real-time device communication, real-time data management, Standard API (Application Program Interface) and application template management. To be application system to RMS (Reconfigurable Manufacturing System) for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.
基金Hong Kong Polytechnic University under the ICRG Grant No.G-YE57,Hong Kong RGC under the Grant of A Research Center Ubiquitous Computingthe National Hi-Tech Development 863 Program of China under Grant No.2006AA01Z231.
文摘Wireless Sensor Networks （WSNs） have found more and more applications in a variety of pervasive computing environments. However, how to support the development, maintenance, deployment and execution of applications over WSNs remains to be a nontrivial and challenging task, mainly because of the gap between the high level requirements from pervasive computing applications and the underlying operation of WSNs. Middleware for WSN can help bridge the gap and remove impediments. In recent years, research has been carried out on WSN middleware from different aspects and for different purposes. In this paper, we provide a comprehensive review of the existing work on WSN middleware, seeking for a better understanding of the current issues and future directions in this field. We propose a reference framework to analyze the functionalities of WSN middleware in terms of the system abstractions and the services provided. We review the approaches and techniques for implementing the services. On the basis of the analysis and by using a feature tree, we provide taxonomy of the features of WSN middleware and their relationships, and use the taxonomy to classify and evaluate existing work. We also discuss open problems in this important area of research.
基金National Key Technology R&D Program of China under Grant No.2014BAL05B06Guangdong Science&Technology Program under Grant No.2014A050503016the Shenzhen Science&Technology Program under Grant No.GJHZ20150312114346635
文摘The Random Decrement Technique （RDT）, based on decentralized computing approaches implemented in wireless sensor networks （WSNs）, has shown advantages for modal parameter and data aggregation identification. However, previous studies of RDT-based approaches from ambient vibration data are based on the assumption of a broad-band stochastic process input excitation. The process normally is modeled by filtered white or white noise. In addition, the choice of the triggering condition in RDT is closely related to data communication. In this project, research has been conducted to study the nonstationary white noise excitations as the input to verify the random decrement technique. A local extremum triggering condition is chosen and implemented for the purpose of minimum data communication in a RDT-based distributed computing strategy. Numerical simulation results show that the proposed technique is capable of minimizing the amount of data transmitted over the network with accuracy in modal parameters identification.
文摘The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance.The longevity of the networks is mostly determined by the proportion of energy consumed and the sensor nodes’access network.The optimal or ideal positioning of sensors improves the portable sensor networks effectiveness.Coverage and energy usage are mostly determined by successful sensor placement strategies.Nature-inspired algorithms are the most effective solution for short sensor lifetime.The primary objective of work is to conduct a comparative analysis of nature-inspired optimization for wireless sensor networks(WSNs’)maximum network coverage.Moreover,it identifies quantity of installed sensor nodes for the given area.Superiority of algorithm has been identified based on value of optimized energy.The first half of the paper’s literature on nature-inspired algorithms is discussed.Later six metaheuristics algorithms(Grey wolf,Ant lion,Dragonfly,Whale,Moth flame,Sine cosine optimizer)are compared for optimal coverage of WSNs.The simulation outcomes confirm that whale opti-mization algorithm(WOA)gives optimized Energy with improved network coverage with the least number of nodes.This comparison will be helpful for researchers who will use WSNs in their applications.
基金support of the Interdisciplinary Research Center for Intelligent Secure Systems(IRC-ISS)Internal Fund Grant#INSS2202.
文摘The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure domains like oil and gas supply,intelligent transportation,power grids,and autonomous agriculture,it is essential to guarantee the confidentiality,integrity,and authenticity of data collected and exchanged.However,the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques.Consequently,designing a lightweight secure data transmission scheme is becoming essential.In this article,we propose lightweight secure data transmission(LSDT)scheme for IoT environments.LSDT consists of three phases and utilizes an effective combination of symmetric keys and the Elliptic Curve Menezes-Qu-Vanstone asymmetric key agreement protocol.We design the simulation environment and experiments to evaluate the performance of the LSDT scheme in terms of communication and computation costs.Security and performance analysis indicates that the LSDT scheme is secure,suitable for IoT applications,and performs better in comparison to other related security schemes.
文摘Established on the Intel Multi-Core Embedded platform, using 802.11 Wireless Network protocols as the communication medium, combining with Radio Frequency-Communication and Ultrasonic Ranging, imple-ment a mobile terminal system in an intellectualized building. It can provide its holder such functions: 1) Accurate Positioning 2) Intelligent Navigation 3) Video Monitoring 4) Wireless Communication. The inno-vative point for this paper is to apply the multi-core computing on the embedded system to promote its com-puting speed and give a real-time performance and apply this system into the indoor environment for the purpose of emergent event or rescuing.
基金Supported by 863 Project of China (No.2006AA01Z224)
文摘In Wireless Sensor Networks (WSNs), it is necessary to predict computational overheads of security mechanisms without final implementations to provide guidelines for system design. This paper presents an accurate and flexible model to predict overheads of these mechanisms. This model is based on overheads of basic operations frequently used in cryptography algorithms, which are essential elements of security mechanisms. Several popular cryptography algorithms and security mechanisms are evaluated using this model. According to simulation results, relative prediction errors are less than 7% for most cryptography algorithms and security mechanisms.
文摘Sensor networks are dense wireless networks of small, low-cost sensors, which collect and disseminate en-vironmental data. Wireless sensor networks facilitate monitoring and controlling of physical environments from remote locations with better accuracy. They have applications in a variety of fields such as environ-mental monitoring;military purposes and gathering sensing information in inhospitable locations. Sensor nodes have various energy and computational constraints because of their inexpensive nature and adhoc method of deployment. Considerable research has been focused at overcoming these deficiencies through more energy efficient routing, localization algorithms and system design. Our survey presents the funda-mentals of wireless sensor network, thus providing the necessary background required for understanding the organization, functionality and limitations of those networks. The middleware solution is also investigated through a critical presentation and analysis of some of the most well established approaches.
基金sponsored by the National Natural Science Foundation of China(No.61373138)the Natural Science Key Fund for Colleges and Universities in Jiangsu Province(No.12KJA520002)+4 种基金the Key Research and Development Program of Jiangsu Province(Social Development Program)(No.BE2015702)the Postdoctoral Foundation(Nos.2015M570468 and2016T90485)the Sixth Talent Peaks Project of Jiangsu Province(No.DZXX-017)the Fund of Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks(WSNLBZY201516)the Science and Technology Innovation Fund for Postgraduate Education of Jiangsu Province(No.KYLX15 0853)
文摘Numerous privacy-preserving issues have emerged along with the fast development of the Internet of Things. In addressing privacy protection problems in Wireless Sensor Networks （WSN）, secure multi-party computation is considered vital, where obtaining the Euclidian distance between two nodes with no disclosure of either side＇s secrets has become the focus of location-privacy-related applications. This paper proposes a novel Privacy-Preserving Scalar Product Protocol （PPSPP） for wireless sensor networks. Based on PPSPP, we then propose a Homomorphic-Encryption-based Euclidean Distance Protocol （HEEDP） without third parties. This protocol can achieve secure distance computation between two sensor nodes. Correctness proofs of PPSPP and HEEDP are provided, followed by security validation and analysis. Performance evaluations via comparisons among similar protocols demonstrate that HEEDP is superior; it is most efficient in terms of both communication and computation on a wide range of data types, especially in wireless sensor networks.
文摘The concept of Network Centric Therapy represents an amalgamation of wearable and wireless inertial sensor systems and machine learning with access to a Cloud computing environment. The advent of Network Centric Therapy is highly relevant to the treatment of Parkinson’s disease through deep brain stimulation. Originally wearable and wireless systems for quantifying Parkinson’s disease involved the use a smartphone to quantify hand tremor. Although originally novel, the smartphone has notable issues as a wearable application for quantifying movement disorder tremor. The smartphone has evolved in a pathway that has made the smartphone progressively more cumbersome to mount about the dorsum of the hand. Furthermore, the smartphone utilizes an inertial sensor package that is not certified for medical analysis, and the trial data access a provisional Cloud computing environment through an email account. These concerns are resolved with the recent development of a conformal wearable and wireless inertial sensor system. This conformal wearable and wireless system mounts to the hand with the profile of a bandage by adhesive and accesses a secure Cloud computing environment through a segmented wireless connectivity strategy involving a smartphone and tablet. Additionally, the conformal wearable and wireless system is certified by the FDA of the United States of America for ascertaining medical grade inertial sensor data. These characteristics make the conformal wearable and wireless system uniquely suited for the quantification of Parkinson’s disease treatment through deep brain stimulation. Preliminary evaluation of the conformal wearable and wireless system is demonstrated through the differentiation of deep brain stimulation set to “On” and “Off” status. Based on the robustness of the acceleration signal, this signal was selected to quantify hand tremor for the prescribed deep brain stimulation settings. Machine learning classification using the Waikato Environment for Knowledge Analysis (WEKA) was applied using the multilayer perceptron neural network. The multilayer perceptron neural network achieved considerable classification accuracy for distinguishing between the deep brain stimulation system set to “On” and “Off” status through the quantified acceleration signal data obtained by this recently developed conformal wearable and wireless system. The research achievement establishes a progressive pathway to the future objective of achieving deep brain stimulation capabilities that promote closed-loop acquisition of configuration parameters that are uniquely optimized to the individual through extrinsic means of a highly conformal wearable and wireless inertial sensor system and machine learning with access to Cloud computing resources.
文摘Traditional Wireless Sensor Networks(WSNs)comprise of costeffective sensors that can send physical parameters of the target environment to an intended user.With the evolution of technology,multimedia sensor nodes have become the hot research topic since it can continue gathering multimedia content and scalar from the target domain.The existence of multimedia sensors,integrated with effective signal processing and multimedia source coding approaches,has led to the increased application of Wireless Multimedia Sensor Network(WMSN).This sort of network has the potential to capture,transmit,and receive multimedia content.Since energy is a major source in WMSN,novel clustering approaches are essential to deal with adaptive topologies of WMSN and prolonged network lifetime.With this motivation,the current study develops an Enhanced Spider Monkey Optimization-based Energy-Aware Clustering Scheme(ESMO-EACS)for WMSN.The proposed ESMO-EACS model derives ESMO algorithm by incorporating the concepts of SMO algorithm and quantum computing.The proposed ESMO-EACS model involves the design of fitness functions using distinct input parameters for effective construction of clusters.A comprehensive experimental analysis was conducted to validate the effectiveness of the proposed ESMO-EACS technique in terms of different performance measures.The simulation outcome established the superiority of the proposed ESMO-EACS technique to other methods under various measures.
文摘Node localization is a fundamental problem in wireless sensor network.There are many existing algorithms to estimate the locations of the nodes.However,most of the methods did not consider the presence of obstacles.In practice,obstacles will lead to blockage and reflection of communication signals between sensor nodes.Therefore,the presence of obstacles will greatly affect the localization result.In this paper,we implement an obstacle-handling algorithm based on the localization tool developed by MIT,The experimental result shows that the enhanced algorithm can reduce the average distance error by up to 46 %,compared to the original algorithm.
文摘Wireless networks are key enablers of ubiquitous communication. With the evolution of networking technologies and the need for these to inter-operate and dynamically adapt to user requirements, intelligent networks are the need of the hour. Use of machine learning techniques allows these networks to adapt to changing environments and enables them to make decisions while continuing to learn about their environment. In this paper, we survey the various problems of wireless networks that have been solved using machine-learning based prediction techniques and identify additional problems to which prediction can be applied. We also look at the gaps in the research done in this area till date.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under grant number(RGP 1/279/42)Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R114)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Artificial intelligence(AI)techniques have received significant attention among research communities in the field of networking,image processing,natural language processing,robotics,etc.At the same time,a major problem in wireless sensor networks(WSN)is node localization,which aims to identify the exact position of the sensor nodes(SN)using the known position of several anchor nodes.WSN comprises a massive number of SNs and records the position of the nodes,which becomes a tedious process.Besides,the SNs might be subjected to node mobility and the position alters with time.So,a precise node localization(NL)manner is required for determining the location of the SNs.In this view,this paper presents a new quantum bird migration optimizer-based NL(QBMA-NL)technique for WSN.The goal of the QBMA-NL approach is for determining the position of unknown nodes in the network by the use of anchor nodes.The QBMA-NL technique is mainly based on the mating behavior of bird species at the time of mating season.In addition,an objective function is derived based on the received signal strength indicator(RSSI)and Euclidean distance from the known to unknown SNs.For demonstrating the improved performance of the QBMA-NL technique,a wide range of simulations take place and the results reported the supreme performance over the recent NL techniques.
基金This work was supported by the King Abdul Aziz City for Science and Technology(KACST),under Grant No.(14-INF727-10).
文摘The identification of an effective network which can efficiently meet the service requirements of the target,while maintaining ultimate performance at an increased level is significant and challenging in a fully interconnected wireless medium.The wrong selection can contribute to unwanted situations like frustrated users,slow service,traffic congestion issues,missed and/or interrupted calls,and wastefulness of precious network components.Conventional schemes estimate the handoff need and cause the network screening process by a single metric.The strategies are not effective enough because traffic characteristics,user expectations,network terminology and other essential device metrics are not taken into account.This article describes an intelligent computing technique based on Multiple-Criteria Decision-Making(MCDM)approach developed based on integrated Fuzzy AHP-TOPSIS which ensures flexible usability and maximizes the experience of end-users in miscellaneous wireless settings.In different components the handover need is assessed and the desired network is chosen.Further,fuzzy sets provide effective solutions to address decision making problems where experts counter uncertainty to make a decision.The proposed research endeavor will support designers and developers to identify,select and prioritize best attributes for ensuring flexible usability in miscellaneous wireless settings.The results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the usability and experience of end-users.
文摘Once deployed, sensor networks are capable of providing a comprehensive view of their environment. However, since the current sensor network paradigm promotes isolated networks that are statically tasked, the full power of the harnessed data has yet to be exploited. In recent years, users have become mobile enti-ties that require constant access to data for efficient and autonomous processing. Under the current limita-tions of sensor networks, users would be restricted using only a subset of the vast amount of data being col-lected;depending on the networks they are able to access. Through reliance on isolated networks, prolifera-tion of sensor nodes can easily occur in any area that has high appeals to users. Furthermore, support for dy-namic tasking of nodes and efficient processing of data is contrary to the general view of sensor networks as subject to severe resource constraints. Addressing the aforementioned challenges requires the deployment of a system that allows users to take full advantage of data collected in the area of interest to their tasks. Such a system must enable interoperability of surrounding networks, support dynamic tasking, and swiftly react to stimuli. In light of these observations, we introduce a hardware-overlay system designed to allow users to efficiently collect and utilize data from various heterogeneous sensor networks. The hardware-overlay takes advantage of FPGA devices and the mobile agent paradigm in order to efficiently collect and process data from cooperating networks. The computational and power efficiency of the prototyped system are herein demonstrated. Furthermore, as a proof-of-concept, we present the implementation of a distributed and autonomous visual object tracker implemented atop the Reconfigurable and Interoperable Sensor Network (RISN) showcasing the network’s ability to support ad-hoc agent networks dedicated to user’s tasks.
