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http://dx.doi.org/10.3837/tiis.2014.03.001

Practical Swarm Optimization based Fault-Tolerance Algorithm for the Internet of Things  

Luo, Shiliang (GanNan Normal University)
Cheng, Lianglun (Guangdong University of Technology)
Ren, Bin (Dongguan University of Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.8, no.3, 2014 , pp. 735-748 More about this Journal
Abstract
The fault-tolerance routing problem is one of the most important issues in the application of the Internet of Things, and has been attracting growing research interests. In order to maintain the communication paths from source sensors to the macronodes, we present a hybrid routing scheme and model, in which alternate paths are created once the previous routing is broken. Then, we propose an improved efficient and intelligent fault-tolerance algorithm (IEIFTA) to provide the fast routing recovery and reconstruct the network topology for path failure in the Internet of Things. In the IEIFTA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is improved by the immune mechanism, which can improve the ability of global search and improve the converging rate of the algorithm. The simulation results indicate that the IEIFTA-based fault-tolerance algorithm outperforms the EARQ algorithm and the SPSOA algorithm due to its ability of fast routing recovery mechanism and prolonging the lifetime of the Internet of Things.
Keywords
System Security; Fault Diagnosis; Intelligence Algorithm; Internet of Things; Cyber-Physical Systems;
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