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Continuous Data Collection Capacity of Dual-Radio Multichannel Wireless Sensor Networks
Oct. 2012 (vol. 23 no. 10)
pp. 1844-1855
Shouling Ji, Georgia State University, Atlanta
Zhipeng Cai, Georgia State University, Atlanta
Yingshu Li, Georgia State University, Atlanta
Xiaohua Jia, City University of Hong Kong, Hong Kong
The performance of data collection in Wireless Sensor Networks (WSNs) can be measured by network capacity. However, few existing works dedicatedly consider the Continuous Data Collection (CDC) capacity for WSNs under the protocol interference model. In this paper, we propose a multipath scheduling algorithm for SDC in single-radio multichannel WSNs and derive its network capacity which is a tighter lower bound compared with the previously best result [CHECK END OF SENTENCE]. We also propose a novel CDC method for dual-radio multichannel WSNs. It significantly speeds up the data collection process, and achieves a capacity of {nW\over 12M\lceil (3.63\rho^2 + c_3 \rho + c_4)/H \rceil } when \Delta_e\le 12 or {nW\over M\Delta_e\lceil (3.63\rho^2 + c_3 \rho + c_4)/H \rceil } when \Delta_e >12, where n is the number of the sensors, M is a constant value and usually M \ll n, \Delta_e is the maximum number of the leaf nodes having a same parent in the data collection tree, W is the channel bandwidth, H is the number of available orthogonal channels, \rho is the ratio of the interference radius over the transmission radius, c_3 = {8\pi \over \sqrt{3}} + \pi + 2, and c_4 = {8\pi \over \sqrt{3}} + 2\pi + 6. Extensive simulation results indicate that the proposed algorithms improve network capacity significantly compared with existing works.
Index Terms:
Wireless sensor networks,Sensors,Scheduling algorithm,Interference,Routing,Pipelines,Schedules,capacity analysis,Wireless sensor networks,snapshot data collection,continuous data collection
Citation:
Shouling Ji, Zhipeng Cai, Yingshu Li, Xiaohua Jia, "Continuous Data Collection Capacity of Dual-Radio Multichannel Wireless Sensor Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 10, pp. 1844-1855, Oct. 2012, doi:10.1109/TPDS.2011.286
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