Wireless sensor networks have several special characteristics which make against the network coverage, such as shortage of energy, difficulty with energy supply and so on. In order to prolong the lifetime of wireless ...Wireless sensor networks have several special characteristics which make against the network coverage, such as shortage of energy, difficulty with energy supply and so on. In order to prolong the lifetime of wireless sensor networks, it is necessary to balance the whole network load. As the energy consumption is related to the situation of nodes, the distribution uniformity must be considered. In this paper, a new model is proposed to evaluate the nodes distribution uniformity by considering some parameters which include compression discrepancy, sparseness discrepancy, self discrepancy, maximum cavity radius and minimum cavity radius. The simulation results show that the presented model could be helpful for measuring the distribution uniformity of nodes scattered randomly in wireless sensor networks.展开更多
Failure of one or multiple critical nodes may partition wireless sensor networks into disjoint segments, and thus brings negative effect on the applications. We propose DCRS, a Distributed Connectivity Restoration Str...Failure of one or multiple critical nodes may partition wireless sensor networks into disjoint segments, and thus brings negative effect on the applications. We propose DCRS, a Distributed Connectivity Restoration Strategy to tolerate the failure of one critical node. Because of the energy restriction of sensor nodes, the energy overhead of the recovery process should be minimized to extend the lifetime of the network. To achieve it, we first design a novel algorithm to identify 2-critical nodes only relying on the positional information of 1-hop neighbors and some 2-hop neighbors, and then we present the criteria to select an appropriate backup for each critical node. Finally, we improve the cascaded node movement algorithm by determining whether a node can move to another non-adjacent node directly or not to reduce the number of nodes moved. The effectiveness of DCRS is validated through extensive simulation experiments.展开更多
In this paper, a sensing model for the coverage analysis of wireless sensor networks is provided. Using this model and Monte Carlo method, the ratio of private range to sensing range required to obtain the desired cov...In this paper, a sensing model for the coverage analysis of wireless sensor networks is provided. Using this model and Monte Carlo method, the ratio of private range to sensing range required to obtain the desired coverage can be derived considering the scale of deployment area and the number of sensor nodes. Base on the coverage analysis, an energy-efficient distributed node scheduling scheme is proposed to prolong the network lifetime while maintaining the desired sensing coverage, which does not need the geographic or neighbor information of nodes. The proposed scheme can also handle uneven distribution, and it is robust against node failures. Theoretical and simulation results demonstrate its efficiency and usefulness.展开更多
Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typical...Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.展开更多
基金Supported by the National Natural Science Foundation of China （No. 60572035）
文摘Wireless sensor networks have several special characteristics which make against the network coverage, such as shortage of energy, difficulty with energy supply and so on. In order to prolong the lifetime of wireless sensor networks, it is necessary to balance the whole network load. As the energy consumption is related to the situation of nodes, the distribution uniformity must be considered. In this paper, a new model is proposed to evaluate the nodes distribution uniformity by considering some parameters which include compression discrepancy, sparseness discrepancy, self discrepancy, maximum cavity radius and minimum cavity radius. The simulation results show that the presented model could be helpful for measuring the distribution uniformity of nodes scattered randomly in wireless sensor networks.
文摘Failure of one or multiple critical nodes may partition wireless sensor networks into disjoint segments, and thus brings negative effect on the applications. We propose DCRS, a Distributed Connectivity Restoration Strategy to tolerate the failure of one critical node. Because of the energy restriction of sensor nodes, the energy overhead of the recovery process should be minimized to extend the lifetime of the network. To achieve it, we first design a novel algorithm to identify 2-critical nodes only relying on the positional information of 1-hop neighbors and some 2-hop neighbors, and then we present the criteria to select an appropriate backup for each critical node. Finally, we improve the cascaded node movement algorithm by determining whether a node can move to another non-adjacent node directly or not to reduce the number of nodes moved. The effectiveness of DCRS is validated through extensive simulation experiments.
基金Supported by China Scholarship Council(No.201306255014)
文摘In this paper, a sensing model for the coverage analysis of wireless sensor networks is provided. Using this model and Monte Carlo method, the ratio of private range to sensing range required to obtain the desired coverage can be derived considering the scale of deployment area and the number of sensor nodes. Base on the coverage analysis, an energy-efficient distributed node scheduling scheme is proposed to prolong the network lifetime while maintaining the desired sensing coverage, which does not need the geographic or neighbor information of nodes. The proposed scheme can also handle uneven distribution, and it is robust against node failures. Theoretical and simulation results demonstrate its efficiency and usefulness.
文摘Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.
