This paper proposes a novel energy efficient unequal clustering algorithm for large scale wireless sensor network （WSN） which aims to balance the node power consumption and prolong the network lifetime as long as po...This paper proposes a novel energy efficient unequal clustering algorithm for large scale wireless sensor network （WSN） which aims to balance the node power consumption and prolong the network lifetime as long as possible. Our approach focuses on energy efficient unequal clustering scheme and inter-cluster routing protocol. On the one hand, considering each node＇s local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine one node＇s chance of becoming cluster head and hand, adaptive max-min ant colony optimization is used to estimate the corresponding competence radius. On the other construct energy-aware inter-cluster routing between cluster heads and base station （BS）, which balances the energy consumption of cluster heads and alleviates the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The confirmation experiment results have indicated the proposed clustering algorithm has more superior performance than other methods such as low energy adaptive clustering hierarchy （LEACH） and energy efficient unequal clustering （EEUC）.展开更多
Wireless sensor network(WSN)plays a vital part in real time tracking and data collection applications.WSN incorporates a set of numerous sensor nodes(SNs)commonly utilized to observe the target region.The SNs operate ...Wireless sensor network(WSN)plays a vital part in real time tracking and data collection applications.WSN incorporates a set of numerous sensor nodes(SNs)commonly utilized to observe the target region.The SNs operate using an inbuilt battery and it is not easier to replace or charge it.Therefore,proper utilization of available energy in the SNs is essential to prolong the lifetime of the WSN.In this study,an effective Type-II Fuzzy Logic with Butterfly Optimization Based Route Selection(TFL-BOARS)has been developed for clustered WSN.The TFL-BOARS technique intends to optimally select the cluster heads(CHs)and routes in the clustered WSN.Besides,the TFL-BOARS technique incorporates Type-II Fuzzy Logic(T2FL)technique with distinct input parameters namely residual energy(RE),link quality(LKQ),trust level(TRL),inter-cluster distance(ICD)and node degree(NDE)to select CHs and construct clusters.Also,the butterfly optimization algorithm based route selection(BOARS)technique is derived to select optimal set of routes in the WSN.In addition,the BOARS technique has computed afitness function using three parameters such as communication cost,distance and delay.In order to demonstrate the improved energy effectiveness and prolonged lifetime of the WSN,a wide-ranging simulation analysis was implemented and the experimental results reported the supremacy of the TFL-BOARS technique.展开更多
The objective of the recently proposed fuzzy based hierarchical routing protocol F-SCH is to improve the lifetime of a Wireless Sensor Network. Though the performance of F-SCH is better than LEACH, the randomness in C...The objective of the recently proposed fuzzy based hierarchical routing protocol F-SCH is to improve the lifetime of a Wireless Sensor Network. Though the performance of F-SCH is better than LEACH, the randomness in CH selection inhibits it from attaining enhanced lifetime. CBCH ensures maximum network lifetime when CH is close to the centroid of the cluster. However, for a widely distributed network, CBCH results in small sized clusters increasing the inter cluster communication cost. Hence, with an objective to enhance the network lifetime, a fuzzy based two-level hierarchical routing protocol is proposed. The novelty of the proposal lies in identification of appropriate parameters used in Cluster Head and Super Cluster Head selection. Experiments for different network scenarios are performed through both simulation and hardware to validate the proposal. The performance of the network is evaluated in terms of Node Death. The proposal is compared with F-SCH and the results reveal the efficacy of the proposal in enhancing the lifetime of network.展开更多
This article proposes a method of management and control of a continuous bus powered by renewable energies for autonomous applications. The DC bus is obtained from two systems of renewable sources (the solar system an...This article proposes a method of management and control of a continuous bus powered by renewable energies for autonomous applications. The DC bus is obtained from two systems of renewable sources (the solar system and the wind system) and storage battery (Lithium Ion). The continuous bus control and management procedure require efficiency in the control of the charge and discharge of the battery according to the load energy demand (DC Motor). The battery charging process is non-linear, varying over time with considerable delay, so it is difficult to achieve the best performance on control with energy management using traditional control approaches. A fuzzy control strategy is used in this article for battery control. To improve battery life, fuzzy control manages the desired state of charge (SOC). The entire system designed is modeled and simulated on MATLAB/Simulink Environment.展开更多
Energy management and packet delivery rate are the important factors in ad hoc networks.It is the major network where nodes share the information without administration.Due to the mobility of nodes,maximum energy is s...Energy management and packet delivery rate are the important factors in ad hoc networks.It is the major network where nodes share the information without administration.Due to the mobility of nodes,maximum energy is spent on transmission of packets.Mostly energy is wasted on packet dropping and false route discovery.In this research work,Fuzzy Based Reliable Load Balanced Routing Approach(RLRA)is proposed to provide high energy efficiency and more network lifetime using optimal multicast route discovery mechanism.It contains three phases.In first phase,optimal multicast route discovery is initiated to resolve the link failures.In second phase,the link quality is estimated and set to threshold value to meet the requirements of high energy efficiency.In third phase,energy model is shown to obtain total energy of network after transmission of packets.A multicast routing is established Based on path reliability and fault tolerant calculation is done and integrated with multicast routing.The routes can withstand the malicious issues.Fuzzy decision model is integrated with propose protocol to decide the performance of network lifetime.The network simulation tool is used for evaluating the RLRA with existing schemes and performance of RLRA is good compared to others.展开更多
In Wireless Multimedia Sensor Networks(WMSNs),nodes capable of retrieving video,audio,images,and small scale sensor data,tend to generate immense traffic of various types.The energy-efficient transmission of such a va...In Wireless Multimedia Sensor Networks(WMSNs),nodes capable of retrieving video,audio,images,and small scale sensor data,tend to generate immense traffic of various types.The energy-efficient transmission of such a vast amount of heterogeneous multimedia content while simultaneously ensuring the quality of service and optimal energy consumption is indispensable.Therefore,we propose a Power-Efficient Wireless Multimedia of Things(PE-WMoT),a robust and energy-efficient cluster-based mechanism to improve the overall lifetime of WMSNs.In a PE-WMoT,nodes declare themselves Cluster Heads(CHs)based on available resources.Once cluster formation and CH declaration processes are completed,the Sub-Cluster(SC)formation process triggers,in which application base nodes within close vicinity of each other organize themselves under the administration of a Sub-Cluster Head(SCH).The SCH gathers data from member nodes,removes redundancies,and forwards miniaturized data to its respective CH.PE-WMoT adopts a fuzzy-based technique named the analytical hierarchical process,which enables CHs to select an optimal SCH among available SCs.A PE-WMoT also devises a robust scheduling mechanism between CH,SCH,and child nodes to enable collision-free data transmission.Simulation results revealed that a PE-WMoT significantly reduces the number of redundant packet transmissions,improves energy consumption of the network,and effectively increases network throughput.展开更多
针对产品的性能退化轨迹呈现为非线性特性,且个体的性能退化数据为小样本的情形,为了充分利用同类产品的性能退化数据进行特定个体的实时寿命预测,从研究退化轨迹相似性的角度出发,提出一类基于小波支持向量回归机(Wavelet support vect...针对产品的性能退化轨迹呈现为非线性特性,且个体的性能退化数据为小样本的情形,为了充分利用同类产品的性能退化数据进行特定个体的实时寿命预测,从研究退化轨迹相似性的角度出发,提出一类基于小波支持向量回归机(Wavelet support vector regression,WSVR)和模糊C均值(Fuzzy c-means,FCM)聚类的实时寿命预测方法.该方法分为离线和实时两个阶段:离线阶段先采用WSVR对同类产品的性能退化数据进行规范化处理,接着对规范化数据进行FCM聚类,然后,基于WSVR建立各聚类中心的退化轨迹模型;在实时阶段,针对特定个体的历史测量数据是否规范化,分别提出两种实时退化轨迹建模和寿命预测方法—隶属度加权法和误差加权法.最后,通过两个实例分析验证了所提方法的有效性.展开更多
The particularities of Wireless Sensor Networks require specially designed protocols. Nodes in these networks often possess limited access to energy (usually supplied by batteries), which imposes energy constraints. A...The particularities of Wireless Sensor Networks require specially designed protocols. Nodes in these networks often possess limited access to energy (usually supplied by batteries), which imposes energy constraints. Additionally, WSNs are commonly deployed in monitoring applications, which may intend to cover large areas. Several techniques have been proposed to improve energy-balance, coverage area or both at the same time. In this paper, an alternative solution is presented. It consists of three main components: Fuzzy C-Means for network clustering, a cluster head rotation mechanism and a sleep scheduling algorithm based on a modified version of Particle Swarm Optimization. Results show that this solution is able to provide a configurable routing protocol that offers reduced energy consumption, while keeping highcoverage area.展开更多
基金supported by National Science and Technology Major Project of the Ministry of Science and Technology of China (2009ZX03006-006, 2009ZX03006-009)the National Natural Science Foundation of China (60902046, 60972079)
文摘This paper proposes a novel energy efficient unequal clustering algorithm for large scale wireless sensor network （WSN） which aims to balance the node power consumption and prolong the network lifetime as long as possible. Our approach focuses on energy efficient unequal clustering scheme and inter-cluster routing protocol. On the one hand, considering each node＇s local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine one node＇s chance of becoming cluster head and hand, adaptive max-min ant colony optimization is used to estimate the corresponding competence radius. On the other construct energy-aware inter-cluster routing between cluster heads and base station （BS）, which balances the energy consumption of cluster heads and alleviates the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The confirmation experiment results have indicated the proposed clustering algorithm has more superior performance than other methods such as low energy adaptive clustering hierarchy （LEACH） and energy efficient unequal clustering （EEUC）.
基金supported by the Researchers Supporting Program(TUMA-Project-2021-27)Almaarefa University,Riyadh,Saudi ArabiaTaif University Researchers Supporting Project number(TURSP-2020/161),Taif University,Taif,Saudi Arabia.
文摘Wireless sensor network(WSN)plays a vital part in real time tracking and data collection applications.WSN incorporates a set of numerous sensor nodes(SNs)commonly utilized to observe the target region.The SNs operate using an inbuilt battery and it is not easier to replace or charge it.Therefore,proper utilization of available energy in the SNs is essential to prolong the lifetime of the WSN.In this study,an effective Type-II Fuzzy Logic with Butterfly Optimization Based Route Selection(TFL-BOARS)has been developed for clustered WSN.The TFL-BOARS technique intends to optimally select the cluster heads(CHs)and routes in the clustered WSN.Besides,the TFL-BOARS technique incorporates Type-II Fuzzy Logic(T2FL)technique with distinct input parameters namely residual energy(RE),link quality(LKQ),trust level(TRL),inter-cluster distance(ICD)and node degree(NDE)to select CHs and construct clusters.Also,the butterfly optimization algorithm based route selection(BOARS)technique is derived to select optimal set of routes in the WSN.In addition,the BOARS technique has computed afitness function using three parameters such as communication cost,distance and delay.In order to demonstrate the improved energy effectiveness and prolonged lifetime of the WSN,a wide-ranging simulation analysis was implemented and the experimental results reported the supremacy of the TFL-BOARS technique.
文摘The objective of the recently proposed fuzzy based hierarchical routing protocol F-SCH is to improve the lifetime of a Wireless Sensor Network. Though the performance of F-SCH is better than LEACH, the randomness in CH selection inhibits it from attaining enhanced lifetime. CBCH ensures maximum network lifetime when CH is close to the centroid of the cluster. However, for a widely distributed network, CBCH results in small sized clusters increasing the inter cluster communication cost. Hence, with an objective to enhance the network lifetime, a fuzzy based two-level hierarchical routing protocol is proposed. The novelty of the proposal lies in identification of appropriate parameters used in Cluster Head and Super Cluster Head selection. Experiments for different network scenarios are performed through both simulation and hardware to validate the proposal. The performance of the network is evaluated in terms of Node Death. The proposal is compared with F-SCH and the results reveal the efficacy of the proposal in enhancing the lifetime of network.
文摘This article proposes a method of management and control of a continuous bus powered by renewable energies for autonomous applications. The DC bus is obtained from two systems of renewable sources (the solar system and the wind system) and storage battery (Lithium Ion). The continuous bus control and management procedure require efficiency in the control of the charge and discharge of the battery according to the load energy demand (DC Motor). The battery charging process is non-linear, varying over time with considerable delay, so it is difficult to achieve the best performance on control with energy management using traditional control approaches. A fuzzy control strategy is used in this article for battery control. To improve battery life, fuzzy control manages the desired state of charge (SOC). The entire system designed is modeled and simulated on MATLAB/Simulink Environment.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University,Kingdom of Saudi Arabia for funding this workthrough General Research Project Under the grant number(RGP.1/262/42).
文摘Energy management and packet delivery rate are the important factors in ad hoc networks.It is the major network where nodes share the information without administration.Due to the mobility of nodes,maximum energy is spent on transmission of packets.Mostly energy is wasted on packet dropping and false route discovery.In this research work,Fuzzy Based Reliable Load Balanced Routing Approach(RLRA)is proposed to provide high energy efficiency and more network lifetime using optimal multicast route discovery mechanism.It contains three phases.In first phase,optimal multicast route discovery is initiated to resolve the link failures.In second phase,the link quality is estimated and set to threshold value to meet the requirements of high energy efficiency.In third phase,energy model is shown to obtain total energy of network after transmission of packets.A multicast routing is established Based on path reliability and fault tolerant calculation is done and integrated with multicast routing.The routes can withstand the malicious issues.Fuzzy decision model is integrated with propose protocol to decide the performance of network lifetime.The network simulation tool is used for evaluating the RLRA with existing schemes and performance of RLRA is good compared to others.
基金This work was supported in part by the Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2018-0-01411,A Micro-Service IoTWare Framework Technology Development for Ultra small IoT Device)in part by 2021 Hongik University Innovation Support program Fund.
文摘In Wireless Multimedia Sensor Networks(WMSNs),nodes capable of retrieving video,audio,images,and small scale sensor data,tend to generate immense traffic of various types.The energy-efficient transmission of such a vast amount of heterogeneous multimedia content while simultaneously ensuring the quality of service and optimal energy consumption is indispensable.Therefore,we propose a Power-Efficient Wireless Multimedia of Things(PE-WMoT),a robust and energy-efficient cluster-based mechanism to improve the overall lifetime of WMSNs.In a PE-WMoT,nodes declare themselves Cluster Heads(CHs)based on available resources.Once cluster formation and CH declaration processes are completed,the Sub-Cluster(SC)formation process triggers,in which application base nodes within close vicinity of each other organize themselves under the administration of a Sub-Cluster Head(SCH).The SCH gathers data from member nodes,removes redundancies,and forwards miniaturized data to its respective CH.PE-WMoT adopts a fuzzy-based technique named the analytical hierarchical process,which enables CHs to select an optimal SCH among available SCs.A PE-WMoT also devises a robust scheduling mechanism between CH,SCH,and child nodes to enable collision-free data transmission.Simulation results revealed that a PE-WMoT significantly reduces the number of redundant packet transmissions,improves energy consumption of the network,and effectively increases network throughput.
文摘针对产品的性能退化轨迹呈现为非线性特性,且个体的性能退化数据为小样本的情形,为了充分利用同类产品的性能退化数据进行特定个体的实时寿命预测,从研究退化轨迹相似性的角度出发,提出一类基于小波支持向量回归机(Wavelet support vector regression,WSVR)和模糊C均值(Fuzzy c-means,FCM)聚类的实时寿命预测方法.该方法分为离线和实时两个阶段:离线阶段先采用WSVR对同类产品的性能退化数据进行规范化处理,接着对规范化数据进行FCM聚类,然后,基于WSVR建立各聚类中心的退化轨迹模型;在实时阶段,针对特定个体的历史测量数据是否规范化,分别提出两种实时退化轨迹建模和寿命预测方法—隶属度加权法和误差加权法.最后,通过两个实例分析验证了所提方法的有效性.
文摘The particularities of Wireless Sensor Networks require specially designed protocols. Nodes in these networks often possess limited access to energy (usually supplied by batteries), which imposes energy constraints. Additionally, WSNs are commonly deployed in monitoring applications, which may intend to cover large areas. Several techniques have been proposed to improve energy-balance, coverage area or both at the same time. In this paper, an alternative solution is presented. It consists of three main components: Fuzzy C-Means for network clustering, a cluster head rotation mechanism and a sleep scheduling algorithm based on a modified version of Particle Swarm Optimization. Results show that this solution is able to provide a configurable routing protocol that offers reduced energy consumption, while keeping highcoverage area.
