Energy efficiency is critical in Wireless Sensor Networks(WSNs)due to the limited power supply.While clustering algorithms are commonly used to extend network lifetime,most of them focus on single-layer optimization.T...Energy efficiency is critical in Wireless Sensor Networks(WSNs)due to the limited power supply.While clustering algorithms are commonly used to extend network lifetime,most of them focus on single-layer optimization.To this end,an Energy-efficient Cross-layer Clustering approach based on the Gini(ECCG)index theory was proposed in this paper.Specifically,a novel mechanism of Gini Index theory-based energy-efficient Cluster Head Election(GICHE)is presented based on the Gini Index and the expected energy distribution to achieve balanced energy consumption among different clusters.In addition,to improve inter-cluster energy efficiency,a Queue synchronous Media Access Control(QMAC)protocol is proposed to reduce intra-cluster communication overhead.Finally,extensive simulations have been conducted to evaluate the effectiveness of ECCG.Simulation results show that ECCG achieves 50.6%longer the time until the First Node Dies(FND)rounds,up to 30%lower energy consumption compared with Low-Energy Adaptive Clustering Hierarchy(LEACH),and higher throughput under different traffic loads,thereby validating its effectiveness in improving energy efficiency and prolonging the network lifetime.展开更多
The lifetime of a wireless sensor network(WSN)is crucial for determining the maximum duration for data collection in Internet of Things applications.To extend the WSN's lifetime,we propose deploying an unmanned gr...The lifetime of a wireless sensor network(WSN)is crucial for determining the maximum duration for data collection in Internet of Things applications.To extend the WSN's lifetime,we propose deploying an unmanned ground vehicle(UGV)within the energy-hungry WSN.This allows nodes,including sensors and the UGV,to share their energy using wireless power transfer techniques.To optimize the UGV's trajectory,we have developed a tabu searchbased method for global optimality,followed by a clustering-based method suitable for real-world applications.When the UGV reaches a stopping point,it functions as a regular sensor with ample battery.Accordingly,we have designed optimal data and energy allocation algorithms for both centralized and distributed deployment.Simulation results demonstrate that the UGV and energy-sharing significantly extend the WSN's lifetime.This effect is especially prominent in sparsely connected WSNs compared to highly connected ones,and energy-sharing has a more pronounced impact on network lifetime extension than UGV mobility.展开更多
Due to their versatility and ease of movement,Unmanned Aerial Vehicles(UAVs)have become crucial tools in data collection for Wireless Sensor Networks(WSNs).While numerous UAV-based solutions exist,the focus often need...Due to their versatility and ease of movement,Unmanned Aerial Vehicles(UAVs)have become crucial tools in data collection for Wireless Sensor Networks(WSNs).While numerous UAV-based solutions exist,the focus often needs to be on optimizing flight trajectories and managing energy use,sometimes neglecting key factors affecting channel quality.In this article,we introduce a collaborative design framework designed to alleviate channel quality degradation caused by UAV flight distance in three-dimensional spaces.Our approach jointly optimizes UAV power schemes,positions,and flight trajectories.Firstly,we start by introducing a novel enhancing power model developed explicitly for rotary-wing UAVs gathering data,utilizing an alternating optimization method to achieve locally optimal solutions.Next,we frame an optimization problem aimed at maximizing the total average collection rate while achieving approximate optimal position relationships among UAVs.Additionally,we propose a new trajectory optimization model based on the Steiner Minimal Tree(SMT)concept,which is called the Circumcircle Steiner Minimal Tree Problem with Neighborhood(CSMTPN).Finally,we confirm our theoretical insights and numerical outcomes through extensive simulations demonstrating our framework's effectiveness.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.62461041Natural Science Foundation of Jiangxi Province under Grant No.20224BAB212016 and No.20242BA B25068China Scholarship Council under Grant No.202106825021.
文摘Energy efficiency is critical in Wireless Sensor Networks(WSNs)due to the limited power supply.While clustering algorithms are commonly used to extend network lifetime,most of them focus on single-layer optimization.To this end,an Energy-efficient Cross-layer Clustering approach based on the Gini(ECCG)index theory was proposed in this paper.Specifically,a novel mechanism of Gini Index theory-based energy-efficient Cluster Head Election(GICHE)is presented based on the Gini Index and the expected energy distribution to achieve balanced energy consumption among different clusters.In addition,to improve inter-cluster energy efficiency,a Queue synchronous Media Access Control(QMAC)protocol is proposed to reduce intra-cluster communication overhead.Finally,extensive simulations have been conducted to evaluate the effectiveness of ECCG.Simulation results show that ECCG achieves 50.6%longer the time until the First Node Dies(FND)rounds,up to 30%lower energy consumption compared with Low-Energy Adaptive Clustering Hierarchy(LEACH),and higher throughput under different traffic loads,thereby validating its effectiveness in improving energy efficiency and prolonging the network lifetime.
基金supported by the National Natural Science Foundation of China(No.62171486 and No.U2001213)the Guangdong Basic and Applied Basic Research Project(2022A1515140166)。
文摘The lifetime of a wireless sensor network(WSN)is crucial for determining the maximum duration for data collection in Internet of Things applications.To extend the WSN's lifetime,we propose deploying an unmanned ground vehicle(UGV)within the energy-hungry WSN.This allows nodes,including sensors and the UGV,to share their energy using wireless power transfer techniques.To optimize the UGV's trajectory,we have developed a tabu searchbased method for global optimality,followed by a clustering-based method suitable for real-world applications.When the UGV reaches a stopping point,it functions as a regular sensor with ample battery.Accordingly,we have designed optimal data and energy allocation algorithms for both centralized and distributed deployment.Simulation results demonstrate that the UGV and energy-sharing significantly extend the WSN's lifetime.This effect is especially prominent in sparsely connected WSNs compared to highly connected ones,and energy-sharing has a more pronounced impact on network lifetime extension than UGV mobility.
基金supported by the National Natural Science Foundation of China(Nos.62372266,62472251,61832012,and 62072273)the Natural Science Foundation of Shandong Province(Nos.ZR2022MF304,ZR2021MF075,and ZR2019ZD10)the Key Research and Development Program Project of Shandong Province(Nos.2022CXPT055 and 2019GGX1050).
文摘Due to their versatility and ease of movement,Unmanned Aerial Vehicles(UAVs)have become crucial tools in data collection for Wireless Sensor Networks(WSNs).While numerous UAV-based solutions exist,the focus often needs to be on optimizing flight trajectories and managing energy use,sometimes neglecting key factors affecting channel quality.In this article,we introduce a collaborative design framework designed to alleviate channel quality degradation caused by UAV flight distance in three-dimensional spaces.Our approach jointly optimizes UAV power schemes,positions,and flight trajectories.Firstly,we start by introducing a novel enhancing power model developed explicitly for rotary-wing UAVs gathering data,utilizing an alternating optimization method to achieve locally optimal solutions.Next,we frame an optimization problem aimed at maximizing the total average collection rate while achieving approximate optimal position relationships among UAVs.Additionally,we propose a new trajectory optimization model based on the Steiner Minimal Tree(SMT)concept,which is called the Circumcircle Steiner Minimal Tree Problem with Neighborhood(CSMTPN).Finally,we confirm our theoretical insights and numerical outcomes through extensive simulations demonstrating our framework's effectiveness.
