Wireless sensor networks (WSNs) are very important for monitoring underground mine safety. Sensor node deployment affects the performances of WSNs. In our study, a chain-type wireless underground mine sensor network (...Wireless sensor networks (WSNs) are very important for monitoring underground mine safety. Sensor node deployment affects the performances of WSNs. In our study, a chain-type wireless underground mine sensor network (CWUMSN) is first pre- sented. A CWUMSN can monitor the environment and locate miners in underground mines. The lowest density deployment strate- gies of cluster head nodes are discussed theoretically. We prove that the lifetime of CWUMSN with a non-uniform deployment strategy is longer than with a uniform deployment strategy. Secondly, we present the algorithm of non-uniform lowest density de- ployment of cluster head nodes. Next, we propose a dynamic choice algorithm of cluster head nodes for CWUMSN which can im- prove the adaptability of networks. Our experiments of CWUMSN with both non-uniform lowest density and uniform lowest den- sity deployments are simulated. The results show that the lifetime of CWUMSN with non-uniform lowest density deployment is almost 2.5 times as long as that of the uniform lowest density deployment. This work provides a new deployment strategy for wire- less underground mine sensor networks and then effectively promotes the application of wireless sensor networks to underground mines.展开更多
Blackboard academic suite is an excellent teaching software,Design of the principle of remote sensing network course based on it includes five kernel parts:course content construction,experimental process recurrence,i...Blackboard academic suite is an excellent teaching software,Design of the principle of remote sensing network course based on it includes five kernel parts:course content construction,experimental process recurrence,interactive cooperation creation,exercises evaluation,course data evaluation and feedback.Teacher also should use some tactics to motivate students use blackboard academic suite,so as to improve students' learning interest and initiative,and teaching quality of the principle of remote sensing course.展开更多
基金Project 20070411065 supported by the China Postdoctoral Science Foundation
文摘Wireless sensor networks (WSNs) are very important for monitoring underground mine safety. Sensor node deployment affects the performances of WSNs. In our study, a chain-type wireless underground mine sensor network (CWUMSN) is first pre- sented. A CWUMSN can monitor the environment and locate miners in underground mines. The lowest density deployment strate- gies of cluster head nodes are discussed theoretically. We prove that the lifetime of CWUMSN with a non-uniform deployment strategy is longer than with a uniform deployment strategy. Secondly, we present the algorithm of non-uniform lowest density de- ployment of cluster head nodes. Next, we propose a dynamic choice algorithm of cluster head nodes for CWUMSN which can im- prove the adaptability of networks. Our experiments of CWUMSN with both non-uniform lowest density and uniform lowest den- sity deployments are simulated. The results show that the lifetime of CWUMSN with non-uniform lowest density deployment is almost 2.5 times as long as that of the uniform lowest density deployment. This work provides a new deployment strategy for wire- less underground mine sensor networks and then effectively promotes the application of wireless sensor networks to underground mines.
基金supported by Main Course "Principle of Remote Sensing" of Chuxiong Normal University~~
文摘Blackboard academic suite is an excellent teaching software,Design of the principle of remote sensing network course based on it includes five kernel parts:course content construction,experimental process recurrence,interactive cooperation creation,exercises evaluation,course data evaluation and feedback.Teacher also should use some tactics to motivate students use blackboard academic suite,so as to improve students' learning interest and initiative,and teaching quality of the principle of remote sensing course.
