Research challenges in wireless networks of biomedical sensors
Proceedings of the 7th annual international conference on Mobile computing and networking
Determining the number of components in mixtures of linear models
Computational Statistics & Data Analysis
Journal of Global Optimization
Timing-sync protocol for sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
The flooding time synchronization protocol
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Sensor Networks
Fine-grained network time synchronization using reference broadcasts
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Wireless Sensor Networks: Technology, Protocols, and Applications
Wireless Sensor Networks: Technology, Protocols, and Applications
Health monitoring of civil infrastructures using wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Information Technologies and International Development
Underground coal mine monitoring with wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
A wireless sensor network for precision viticulture: The NAV system
Computers and Electronics in Agriculture
Nature-Inspired Algorithms for Optimisation
Nature-Inspired Algorithms for Optimisation
Mercury: a wearable sensor network platform for high-fidelity motion analysis
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Learning to play games using a PSO-based competitive learning approach
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Opposition-Based Differential Evolution
IEEE Transactions on Evolutionary Computation
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Time Synchronization is common requirement for most network applications. It is particularly essential in a Wireless Sensor Networks WSNs to allow collective signal processing, proper correlation of diverse measurements taken from a set of distributed sensor elements and for an efficient sharing of the communication channel. The Flooding Time Synchronization Protocol FTSP was developed explicitly for time synchronization of wireless sensor networks. In this paper, we optimized FTSP for clock drift management using Particle Swarm Optimization PSO, Variant of PSO and Differential Evolution DE. The paper estimates the clock offset, clock skew, generates linear line and optimizes the value of average time synchronization error using PSO, Variant of PSO and DE. In this paper we present implementation and experimental results that produces reduced average time synchronization error using PSO, Variant of PSO and DE, compared to that of linear regression used in FTSP.