The coverage of sensing field is one among many noteworthy phase at the designing of Wireless sensor Networks (WSN). The coverage concern in WSNs depends on a number of aspects like topology of the network, sensing mo...
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ISBN:
(纸本)9781467368230
The coverage of sensing field is one among many noteworthy phase at the designing of Wireless sensor Networks (WSN). The coverage concern in WSNs depends on a number of aspects like topology of the network, sensing mode of sensors and most considerably is deployment. This methodology permits us to locate the sensornodes in our field of interest which refers to the preferred field of coverage. A novel methodology for deployment of Hybrid sensornodes has been proposed in this work. Hybrid implies that, this algorithm includes both static and mobilenodes. In order to triumph over the hurdle of coverage, mobilesensornodes get included to the previously deployed stationary nodes. A well-structured method of sensornodedeployment namely, grid deployment technique is proposed in this work which would generate supreme utilization of the covered area. The complete atmospheric region is partitioned into a number of individual grids along with which the weight value of each grid is estimated. Target grid of any mobilenode will be the one which possesses the minimum weightage value among all grids. The coverage ratio is the performance parameter evaluated in order to estimate the precision of the proposed method. The ultimate result of coverage is found to be getting enhanced swiftly along with the increase in number of sensornodes. When compared with the previously given deployment methodologies, this work has privileged performance in terms of coverage. Added advantages include lower value of computational cost.
mobile sensor node deployment and power management are important issues in the wireless sensor network system. This study designs a mobilesensornode platform to achieve a highly accurate localization mechanism by us...
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mobile sensor node deployment and power management are important issues in the wireless sensor network system. This study designs a mobilesensornode platform to achieve a highly accurate localization mechanism by using ultrasonic, dead reckoning, and radio frequency information which is processed through a particle filter algorithm. mobilesensornode with accurate localization ability is of great interest to basic research works and applications, such as sensordeployment, coverage management, dynamic power management, etc. In this paper, we propose an efficient mobile sensor node deployment method, grid deployment, where the map is divided into multiple individual grids and the weight of each grid is determined by environmental factors such as predeployed nodes, boundaries, and obstacles. The grid with minimum values is the goal of the mobilenode. We also design an asynchronous power management strategy in our sensornode to reduce power consumption of the sensor network. Several factors such as probability of event generation, battery status, coverage issues, and communication situations have also been taken into consideration. In network communication, we propose an asynchronous awakening scheme so that each node is free to switch on or off its components according to observed event statistics and make a tradeoff between communication and power consumption. The deepest sleep state period is determined by the residual power. By combining these methods, the power consumption of the sensornode can be reduced.
A mobile wireless sensor network (MWSN) consists of many sensornodes, which can move from one position to another and gather data from the environment, and such nodes are coordinated with the support of a sink node. ...
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A mobile wireless sensor network (MWSN) consists of many sensornodes, which can move from one position to another and gather data from the environment, and such nodes are coordinated with the support of a sink node. In recent years, the mobility behavior of sensornodes present in wireless sensor networks is used to form effective clustering and to perform cluster-based routing. Virtual force is an important phenomenon in sensornodes, which is used to model the mobility behavior. Production rules that use spatiotemporal constraints are able to make more accurate decisions on mobility speed, mobility area, and the required time. Routing in MWSNs under the mobility scenario will provide better performance if virtual force-based mobility modeling is used to form clusters. In this paper, an intelligent routing algorithm called virtual force-based intelligent clustering for energy-efficient routing in MWSNs has been proposed for effective and energy-efficient cluster-based routing of data packets collected by mobilesensornodes in a MWSN. This algorithm uses attractive and repulsive forces for finding the cluster members. Moreover, spatiotemporal constraints are used in the form of rules for clustering, reclustering, and cluster head election and to perform routing through the cluster heads using intelligent rules. The main advantage of the proposed algorithm is that it increases the network lifetime and packet delivery ratio. Moreover, it reduces the delay and the energy consumption.
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