当前,无线传感网的广泛应用给人们带来便捷的同时,与日俱增的能耗也对全球环境造成了重大影响。因此,无线传感网的节能问题始终是业界关注的焦点。节点休眠调度策略有助于合理组织网络中众多传感器节点的工作状态,从而有效均衡节点负载...当前,无线传感网的广泛应用给人们带来便捷的同时,与日俱增的能耗也对全球环境造成了重大影响。因此,无线传感网的节能问题始终是业界关注的焦点。节点休眠调度策略有助于合理组织网络中众多传感器节点的工作状态,从而有效均衡节点负载和降低网络整体能耗。首先,对现存的无线传感网休眠调度策略进行了调研分析,并指出了存在的边界效应问题。然后,针对现有节点休眠调度策略存在的不足,面向无线传感网目标监测应用场景的需求,综合考量网络覆盖度和节点剩余能量,构造了节点进行休眠决策的优先级,并据此设计了一种基于优先级的分布式节点休眠调度机制(Priority Based Distributed Sleep Scheduling,PBDSS)。仿真实验结果表明,与典型的贪心休眠调度策略相比,PBDSS能够降低信息交互带来的能量开销,有效解决了边界效应问题,均衡了节点能量消耗,提高了节点能量效率,延长了网络寿命。展开更多
Sensing coverage is a fundamental design issue in wireless sensor networks(WSNs),while sensor scheduling ensures coverage degree to the monitored event and extends the network lifetime.In this paper,we address k-cover...Sensing coverage is a fundamental design issue in wireless sensor networks(WSNs),while sensor scheduling ensures coverage degree to the monitored event and extends the network lifetime.In this paper,we address k-coverage scheduling problem in dense WSNs,we maintain a connected k-coverage energy efficiently through a novel Hard-Core based Coordinated Scheduling(HCCS),in which hardcore is a thinning process in stochastic geometry that inhibits more than one active sensor covering any area redundantly in a minimum distance. As compared with existing coordinated scheduling,HCCS allows coordination between sensors with little communication overhead.Moreover,due to the traditional sensing models in k-coverage analysis is unsuitable to describe the characteristic of transmit channel in dense WSNs,we propose a novel sensing model integrating Rayleigh Fading and Distribution of Active sensors(RFDA),and derive the coverage measure and k-coverage probability for the monitored event under RFDA. In addition,we analyze the influence factors,i.e. the transmit condition and monitoring degree to the k-coverage probability. Finally,through Monte Carlo simulations,it is shown that the k-coverage probability of HCCS outperforms that of its random scheduling counterpart.展开更多
提出了一种基于接触概率的机会网络低时延休眠调度算法—LDSCP(an Low Delay Sleep Scheduling Algorithm base on Contact Probability for Opportunistic Networks).算法通过精准预测机制向前后预测错失相遇的下次唤醒时间,保证了预...提出了一种基于接触概率的机会网络低时延休眠调度算法—LDSCP(an Low Delay Sleep Scheduling Algorithm base on Contact Probability for Opportunistic Networks).算法通过精准预测机制向前后预测错失相遇的下次唤醒时间,保证了预测下次相遇的准确度,而且对重叠后的时间采用相遇概率最大化机制来提高相遇机会,减小消息投递时延.理论分析验证了LDSCP算法设计的有效性,仿真结果表明,LDSCP算法在消息投递成功率、消息平均时延和消息平均传输跳数等方面的性能均优于WS算法和Epidemic路由算法.展开更多
文摘当前,无线传感网的广泛应用给人们带来便捷的同时,与日俱增的能耗也对全球环境造成了重大影响。因此,无线传感网的节能问题始终是业界关注的焦点。节点休眠调度策略有助于合理组织网络中众多传感器节点的工作状态,从而有效均衡节点负载和降低网络整体能耗。首先,对现存的无线传感网休眠调度策略进行了调研分析,并指出了存在的边界效应问题。然后,针对现有节点休眠调度策略存在的不足,面向无线传感网目标监测应用场景的需求,综合考量网络覆盖度和节点剩余能量,构造了节点进行休眠决策的优先级,并据此设计了一种基于优先级的分布式节点休眠调度机制(Priority Based Distributed Sleep Scheduling,PBDSS)。仿真实验结果表明,与典型的贪心休眠调度策略相比,PBDSS能够降低信息交互带来的能量开销,有效解决了边界效应问题,均衡了节点能量消耗,提高了节点能量效率,延长了网络寿命。
基金supported by the National Science Foundation of China under Grant 61271186
文摘Sensing coverage is a fundamental design issue in wireless sensor networks(WSNs),while sensor scheduling ensures coverage degree to the monitored event and extends the network lifetime.In this paper,we address k-coverage scheduling problem in dense WSNs,we maintain a connected k-coverage energy efficiently through a novel Hard-Core based Coordinated Scheduling(HCCS),in which hardcore is a thinning process in stochastic geometry that inhibits more than one active sensor covering any area redundantly in a minimum distance. As compared with existing coordinated scheduling,HCCS allows coordination between sensors with little communication overhead.Moreover,due to the traditional sensing models in k-coverage analysis is unsuitable to describe the characteristic of transmit channel in dense WSNs,we propose a novel sensing model integrating Rayleigh Fading and Distribution of Active sensors(RFDA),and derive the coverage measure and k-coverage probability for the monitored event under RFDA. In addition,we analyze the influence factors,i.e. the transmit condition and monitoring degree to the k-coverage probability. Finally,through Monte Carlo simulations,it is shown that the k-coverage probability of HCCS outperforms that of its random scheduling counterpart.
文摘提出了一种基于接触概率的机会网络低时延休眠调度算法—LDSCP(an Low Delay Sleep Scheduling Algorithm base on Contact Probability for Opportunistic Networks).算法通过精准预测机制向前后预测错失相遇的下次唤醒时间,保证了预测下次相遇的准确度,而且对重叠后的时间采用相遇概率最大化机制来提高相遇机会,减小消息投递时延.理论分析验证了LDSCP算法设计的有效性,仿真结果表明,LDSCP算法在消息投递成功率、消息平均时延和消息平均传输跳数等方面的性能均优于WS算法和Epidemic路由算法.
