Learning from the conventional practice of network IP address format, this paper proposed an IP-format-based algorithm for ZigBee energy-balanced routing protocol optimization. The algorithm combines node’s cluster a...Learning from the conventional practice of network IP address format, this paper proposed an IP-format-based algorithm for ZigBee energy-balanced routing protocol optimization. The algorithm combines node’s cluster address and node’s network short address into a new address and divides the address’s field as IP-format. So that the address will contain information of the network’s topology and provide decision base for a routing algorithm to optimize the original algorithm selection criteria. Meanwhile, in order to improve the ratio of valid data packets and reduce routing overhead, the new algorithm controls the general direction and the number of hops of the RREQ packets to reduce unwarranted data packet transmission. Finally, the simulation carried out on NS platform demonstrates the algorithm’s superiority on network’s delay jitter, overhead and residual energy.展开更多
A large number of sparse signal reconstruction algorithms have been continuously proposed, but almost all greedy algorithms add a fixed number of indices to the support set in each iteration. Although the mechanism of...A large number of sparse signal reconstruction algorithms have been continuously proposed, but almost all greedy algorithms add a fixed number of indices to the support set in each iteration. Although the mechanism of selecting the fixed number of indexes improves the reconstruction efficiency, it also brings the problem of low index selection accuracy. Based on the full study of the theory of compressed sensing, we propose a dynamic indexes selection strategy based on residual update to improve the performance of the compressed sampling matching pursuit algorithm (CoSaMP). As an extension of CoSaMP algorithm, the proposed algorithm adopts a residual comparison strategy to improve the accuracy of backtracking selected indexes. This backtracking strategy can efficiently select backtracking indexes. And without increasing the computational complexity, the proposed improvement algorithm has a higher exact reconstruction rate and peak signal to noise ratio (PSNR). Simulation results demonstrate the proposed algorithm significantly outperforms the CoSaMP for image recovery and one-dimensional signal.展开更多
文摘Learning from the conventional practice of network IP address format, this paper proposed an IP-format-based algorithm for ZigBee energy-balanced routing protocol optimization. The algorithm combines node’s cluster address and node’s network short address into a new address and divides the address’s field as IP-format. So that the address will contain information of the network’s topology and provide decision base for a routing algorithm to optimize the original algorithm selection criteria. Meanwhile, in order to improve the ratio of valid data packets and reduce routing overhead, the new algorithm controls the general direction and the number of hops of the RREQ packets to reduce unwarranted data packet transmission. Finally, the simulation carried out on NS platform demonstrates the algorithm’s superiority on network’s delay jitter, overhead and residual energy.
文摘A large number of sparse signal reconstruction algorithms have been continuously proposed, but almost all greedy algorithms add a fixed number of indices to the support set in each iteration. Although the mechanism of selecting the fixed number of indexes improves the reconstruction efficiency, it also brings the problem of low index selection accuracy. Based on the full study of the theory of compressed sensing, we propose a dynamic indexes selection strategy based on residual update to improve the performance of the compressed sampling matching pursuit algorithm (CoSaMP). As an extension of CoSaMP algorithm, the proposed algorithm adopts a residual comparison strategy to improve the accuracy of backtracking selected indexes. This backtracking strategy can efficiently select backtracking indexes. And without increasing the computational complexity, the proposed improvement algorithm has a higher exact reconstruction rate and peak signal to noise ratio (PSNR). Simulation results demonstrate the proposed algorithm significantly outperforms the CoSaMP for image recovery and one-dimensional signal.
