Wireless sensor networks （WSN） using cooperative multiple-input multiple-output （MIMO） communication are effective tools to collect data in several environments. However, how to apply cooperative MIMO in WSN remains a critical challenge, especially in sparse WSN. In this article, a novel clustering scheme is proposed for the application of cooperative MIMO in sparse WSN by extending the traditional low-energy adaptive clustering hierarchy （LEACH） protocol. This clustering scheme solves the problem that the cluster heads （CH） cannot find enough secondary cluster heads （SCH）, which are used to cooperate and inform multiple-antenna transmitters with CHs. On the basis of this protocol, the overall energy consumption of the networks model is developed, and the optimal number of CHs is obtained. The simulation results show that this protocol is feasible for the sparse WSN. The simulation results also illustrate that this protocol provides significant energy efficiencies, even after allowing for additional overheads.
WANG Qing-huaQU Yu-guiLIN Zhi-tingBAI Rong-gangZHAO Bao-huaPAN Quan-ke
in network packet processing, high-performance string lookup systems are very important. In this article, an extended Bloom filter data structure is introduced to support value retrieval string lookup, and to improve its performance, a weighted extended Bloom filter （WEBF） structure is generalized. The optimal configuration of the WEBF is then derived, and it is shown that it outperforms the traditional Bloom filter. Finally, an application-specific integrated circuit （ASIC）-based technique using WEBF is outlined.
