Advanced Technologies in Ad Hoc and Sensor Networks: by Xue Wang, Li Cui, Zhongwen Guo (eds.)

By Xue Wang, Li Cui, Zhongwen Guo (eds.)

Advanced applied sciences in advert Hoc and Sensor Networks collects chosen papers from the seventh China convention on instant Sensor Networks (CWSN2013) held in Qingdao, October 17-19, 2013. The booklet beneficial properties cutting-edge stories on Sensor Networks in China with the subject matter of “Advances in instant sensor networks of China”. the chosen works can assist advertise improvement of sensor community know-how in the direction of interconnectivity, source sharing, flexibility and excessive potency. Researchers and engineers within the box of sensor networks can enjoy the book.

Xue Wang is a professor at Tsinghua college; Li Cui is a professor at Institute of Computing expertise, chinese language Academy of Sciences; Zhongwen Guo is a professor at Ocean collage of China.

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Advanced Technologies in Ad Hoc and Sensor Networks: Proceedings of the 7th China Conference on Wireless Sensor Networks

Complex applied sciences in advert Hoc and Sensor Networks collects chosen papers from the seventh China convention on instant Sensor Networks (CWSN2013) held in Qingdao, October 17-19, 2013. The ebook positive factors cutting-edge reports on Sensor Networks in China with the subject matter of “Advances in instant sensor networks of China”.

Additional resources for Advanced Technologies in Ad Hoc and Sensor Networks: Proceedings of the 7th China Conference on Wireless Sensor Networks

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To address this, for ease of statement, we assume that the sensors are uniformly distributed in the sensing field, and each node has a unique ID. The communication radio range of each node is assumed to be the same, denoted by r . For a sensor node p, let Nk ( p) be its k-hop neighbors, namely, the set of nodes at most k hops from p, and |Nk ( p)| denote the k-hop neighborhood size. Clearly, Nk ( p) is a discrete analog of the circle D( p, kr ) in continuous domain. The larger the value of k, the larger the area of D( p, kr ) is, and thus the larger the k-hop neighborhood size |Nk ( p)|.

That is, two nodes are connected if their separation is no greater than r . 5 by default. The average degrees are all below 7 where existing boundary recognition solutions do not work well. Note that MAP requires boundary information. For fair comparison, we manually identify the boundary nodes for MAP; in order to control boundary noise, in our simulations MAP regards the unstable skeleton nodes, whose nearest boundary nodes have a separation less than 6, as nonskeleton nodes. 34 D. Zhu et al.

Jianshu L, Renhou L, Hong C (2006) Multi-sensor data fusion based on correlation function and least square. Control Decis 21:714–717 13. Desai P, Rattan KS (2008) System level approach for surveillance using wireless sensor networks and ptz camera. In: Proceedings of IEEE conference on National aerospace and electronics 353–357 14. Comaniciu D, Ramesh V, PM (2003) Kernel based object tracking. Pattern analysis and machine intelligence, IEEE transactions on 25 564–577 15. Tang-wen Y, Jian-da H, Hong-bo W, Qiu-qi R (2009) Object measurement based on spatial geometric constrains with monocular camera.

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