TY - GEN
T1 - Distributed compression and the blind zone recognition
AU - Wu, Shaochuan
AU - Pan, Siqi
AU - Ma, Kangjian
AU - Wei, Yuming
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/9/26
Y1 - 2016/9/26
N2 - Wireless sensor network (WSN) technology provides support infrastructure to solve blind zone coverage. Previous studies mainly focus on deployment and management of sensor nodes for enhancing signal coverage on a specific zone. But few of them are on coordinating several nodes to recognize blind zone. Moreover, it is a great challenge how to extract, transmit and process information energy efficiently in a decentralized way. In this paper, we propose a distributed algorithm for convenient and efficient blind zone recognition based on the early work on the unbiased broadcast gossip algorithm (UBGA) and the compressed sensing. Using UBGA, a faster consensus algorithm, the system can simultaneously compute the compressed data based on compressed sensing technique and disseminate them throughout the network. From these compressed data one can reconstruct the original data with approximate accuracy by querying any sensor values using the gradient projection strategy. Simulation results illustrate that our solution, proposed in this paper, can effectively recognize blind zone.
AB - Wireless sensor network (WSN) technology provides support infrastructure to solve blind zone coverage. Previous studies mainly focus on deployment and management of sensor nodes for enhancing signal coverage on a specific zone. But few of them are on coordinating several nodes to recognize blind zone. Moreover, it is a great challenge how to extract, transmit and process information energy efficiently in a decentralized way. In this paper, we propose a distributed algorithm for convenient and efficient blind zone recognition based on the early work on the unbiased broadcast gossip algorithm (UBGA) and the compressed sensing. Using UBGA, a faster consensus algorithm, the system can simultaneously compute the compressed data based on compressed sensing technique and disseminate them throughout the network. From these compressed data one can reconstruct the original data with approximate accuracy by querying any sensor values using the gradient projection strategy. Simulation results illustrate that our solution, proposed in this paper, can effectively recognize blind zone.
KW - Blind Zone Recognition
KW - Distributed Compression
KW - Gossip Algorithm
UR - https://www.scopus.com/pages/publications/84994097211
U2 - 10.1109/IWCMC.2016.7577075
DO - 10.1109/IWCMC.2016.7577075
M3 - 会议稿件
AN - SCOPUS:84994097211
T3 - 2016 International Wireless Communications and Mobile Computing Conference, IWCMC 2016
SP - 304
EP - 308
BT - 2016 International Wireless Communications and Mobile Computing Conference, IWCMC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2016
Y2 - 5 September 2016 through 9 September 2016
ER -