A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 17; no. 3; p. 541
Main Authors: Zhang, Lin, Yin, Na, Fu, Xiong, Lin, Qiaomin, Wang, Ruchuan
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 08.03.2017
MDPI
Subjects:
Algorithms
ant-colony optimization algorithm
Data transmission
MPASR
Pheromones
Reputations
Routing
Sensors
trusted secure routing algorithm
Wireless networks
wireless sensor network
trusted secure routing algorithm
ant-colony optimization algorithm
wireless sensor network
MPASR
ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s17030541