TY - GEN
T1 - A robustness distributed system with sensing and fault detection for large-scale sensor networks
AU - Hattori, Kiyohiko
AU - Takadama, Keiki
AU - Murata, Satoshi
AU - Furuya, Hiroshi
PY - 2007
Y1 - 2007
N2 - In this paper, we propose a robustness data collection and fault detection method for large-scale sensor networks, which consist of ten thousand sensor nodes. The sensor network has some special features as multihop communication, data aggregation, and high error data rate caused by the huge number of nodes. To tackle this issue, we propose a distributed and self-organized method for data collecting and diagnosis. Our method has two features that are token nodes and limited broadcast for the data sharing and collecting. The token node is a special node that can make a limited broadcast packet for data collecting and sharing. Limited broadcast is a limited multihop number and we apply only two hops on this research. Those features can prevent a flood of broadcast packet. To clear the capability of our method, we make a few simulations and compare with other data collecting and diagnose method. As the result, our proposed method has better performance than other method.
AB - In this paper, we propose a robustness data collection and fault detection method for large-scale sensor networks, which consist of ten thousand sensor nodes. The sensor network has some special features as multihop communication, data aggregation, and high error data rate caused by the huge number of nodes. To tackle this issue, we propose a distributed and self-organized method for data collecting and diagnosis. Our method has two features that are token nodes and limited broadcast for the data sharing and collecting. The token node is a special node that can make a limited broadcast packet for data collecting and sharing. Limited broadcast is a limited multihop number and we apply only two hops on this research. Those features can prevent a flood of broadcast packet. To clear the capability of our method, we make a few simulations and compare with other data collecting and diagnose method. As the result, our proposed method has better performance than other method.
KW - Data aggregation
KW - Fault detection
KW - Sensor network
UR - http://www.scopus.com/inward/record.url?scp=50249094706&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=50249094706&partnerID=8YFLogxK
U2 - 10.1109/SICE.2007.4421160
DO - 10.1109/SICE.2007.4421160
M3 - Conference contribution
AN - SCOPUS:50249094706
SN - 4907764286
SN - 9784907764289
T3 - Proceedings of the SICE Annual Conference
SP - 1161
EP - 1165
BT - SICE Annual Conference, SICE 2007
T2 - SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
Y2 - 17 September 2007 through 20 September 2007
ER -